Abstract: Responsible Generative AI and Local LLMs Learning Generative AI During Live Coding This video series covers mastering the theory of Generative AI and using local LLMs like Mistral, llamafile, Candle, and Lorax. Lessons covered include: Profit Sharing Concepts Tragedy of the Commons Game Theory and Generative AI Perfect Competition Negative Externalities Fine-tuning Mistral with Ludwig Getting Started with llamafile Hello World in Candle Exploring Rust and Candle Transcribing Audio with Whisper Rust for LLMs Learning Objectives Learn about responsible and ethical uses of generative AI Getting hands-on with local LLMs like Mistral, llamafile, Candle, and Lorax Learning to build solutions by coding along during tutorials Learning the key syntax and features of the Rust Language Additional Popular Resources Assimilate OpenAI 52 Weeks of AWS-The Complete Series Microsoft Azure Fundamentals (AZ-900) Certification Rust Bootcamp Python Bootcamp Google Professional Machine Learning Engineer Course 2023 (Rough Draft) Rust Data Engineering Building with the GitHub EcoSystem: Copilot, CodeSpaces, and GitHub Actions Microsoft Azure Fundamentals (AZ-900) Certification Google Professional Cloud Architect Certification Course 2023 (Rough Draft) AWS Solutions Architect Professional (SAP-C02) 2023.

Abstract: Generative AI tools like ChatGPT are amazing--but how will their use impact our society? This book introduces the world-transforming technology and the strategies you need to use generative AI safely and effectively. Introduction to Generative AI gives you the hows-and-whys of generative AI in accessible language. In this easy-to-read introduction, you'll learn: How large language models (LLMs) work How to integrate generative AI into your personal and professional workflows Balancing innovation and responsibility The social, legal, and policy landscape around generative AI Societal impacts of generative AI Where AI is going Anyone who uses ChatGPT for even a few minutes can tell that it's truly different from other chatbots or question-and-answer tools. Introduction to Generative AI guides you from that first eye-opening interaction to how these powerful tools can transform your personal and professional life. In it, you'll get no-nonsense guidance on generative AI fundamentals to help you understand what these models are (and aren't) capable of, and how you can use them to your greatest advantage. About the Technology Generative AI tools like ChatGPT, Bing, and Bard have permanently transformed the way we work, learn, and communicate. This delightful book shows you exactly how Generative AI works in plain, jargon-free English, along with the insights you'll need to use it safely and effectively. About the Book Introduction to Generative AI guides you through benefits, risks, and limitations of Generative AI technology. You'll discover how AI models learn and think, explore best practices for creating text and graphics, and consider the impact of AI on society, the economy, and the law. Along the way, you'll practice strategies for getting accurate responses and even understand how to handle misuse and security threats. What's Inside How large language models work Integrate Generative AI into your daily work Balance innovation and responsibility About the Reader For anyone interested in Generative AI. No technical experience required. About the Authors Numa Dhamani is a natural language processing expert working at the intersection of technology and society. Maggie Engler is an engineer and researcher currently working on safety for large language models. The technical editor on this book was Maris Sekar. Quotes Essential for anyone eager to understand or work with this transformative technology. - Ron Green, Co-Founder & CTO, KUNGFU.AI Become an active participant in the conversation on the societal implications of generative AI. A must read! - Edgar Markevicius, Meta Clear and compelling. I highly recommend this book to anyone interested in generative AI and its impact on the world. - Kenneth R. Fleischmann, Founding Chair of Good Systems: Ethical AI at UT Austin Perfect. I can think of no defter guides to Generative AI and the promise and peril it portends. - Dr. Daniel Rogers, The Global Disinformation Index.

Abstract: GenAI and LLMs on AWS Learn to build machine learning pipelines leveraging large language models on AWS for natural language processing and generative AI. In this hands-on course, you will gain skills to: * Set up cloud-based Rust development environments * Construct serverless workflows with AWS Lambda and Step Functions * Generate text and code with models like Claude and CodeWhisperer * Orchestrate models and data workflows with Amazon Bedrock * By completing real-world coding projects, you will be prepared to operationalize LLMs for machine learning applications. Additional Popular Resources Assimilate OpenAI 52 Weeks of AWS-The Complete Series Microsoft Azure Fundamentals (AZ-900) Certification Rust Bootcamp Python Bootcamp Google Professional Machine Learning Engineer Course 2023 (Rough Draft) Rust Data Engineering Building with the GitHub EcoSystem: Copilot, CodeSpaces, and GitHub Actions Microsoft Azure Fundamentals (AZ-900) Certification Google Professional Cloud Architect Certification Course 2023 (Rough Draft) AWS Solutions Architect Professional (SAP-C02) 2023.

Abstract: Interactive Technical Projects A weekly updated series of tutorials on interactive technical projects Learning Objectives Learn practical skills by building real-world projects with cutting-edge technologies Learning to build full stack solutions with languages like Rust, Python, LLMs and Data Science Learning the key tools and techniques used by industry experts to create robust applications Get hands-on practice applying your core technical knowledge Understand how all the pieces fit together by building projects end-to-end Troubleshoot bugs and solve complex problems that appear in production systems Expand your portfolio and r©♭sum©♭ with impressive projects Additional Popular Resources Assimilate OpenAI 52 Weeks of AWS-The Complete Series Microsoft Azure Fundamentals (AZ-900) Certification Rust Bootcamp Python Bootcamp Google Professional Machine Learning Engineer Course 2023 (Rough Draft) Rust Data Engineering Building with the GitHub EcoSystem: Copilot, CodeSpaces, and GitHub Actions Microsoft Azure Fundamentals (AZ-900) Certification Google Professional Cloud Architect Certification Course 2023 (Rough Draft) AWS Solutions Architect Professional (SAP-C02) 2023.

Abstract: Introduction to Generative AI Get started with Generative AI and Large Language Models This introductory course is designed for beginners with no prior knowledge of generative AI. You will start by gaining a high-level understanding of what generative AI is and how it works. Through interactive lessons and hands-on examples, you will learn fundamental skills like providing effective prompts and iteratively improving the generated outputs. As the course progresses, you will dive deeper into specific major generative AI models, including their unique capabilities and limitations. Finally,, you will get practical experience using leading systems like GitHub Copilot, Qdrant, and OpenAI to generate code, and text. By the end, you will have developed core knowledge to start experimenting with generative AI in a responsible and effective way for a variety of applications. This course aims to provide a friendly introduction to prepare complete beginners for further exploration of this rapidly evolving technology. Learning objectives Learn to utilize Generative AI effectively Develop Generative AI software solutions Build solutions with Prompt Engineering to enhance Generative AI output Practice Labs Use the practice labs to test your knowledge and gain hands-on experience working with Python and Rust. These labs are based on GitHub templates that will help you to get started quickly and apply the knowledge in the course in building your own solutions. Learn Retrieval Augmented Generation: https://github.com/alfredodeza/learn-retrieval-augmented-generation Azure Chat with OpenAI: https://github.com/alfredodeza/azure-chat-demo Resources Azure LLMOps Practical MLOps book Rust Bootcamp Python Bootcamp.

Abstract: MySQL for Data Engineering Learning Linux Hacker Style Coding Description: Extract MySQL data through queries and bash pipelines Dump query results to CSV files. Build web services to serve data with Python standard library Analyze and process extracts with Linux utilities Chain MySQL, Python, and Linux together for quick data tasks Additional Popular Resources Assimilate OpenAI 52 Weeks of AWS-The Complete Series Microsoft Azure Fundamentals (AZ-900) Certification Rust Bootcamp Python Bootcamp Google Professional Machine Learning Engineer Course 2023 (Rough Draft) Rust Data Engineering Building with the GitHub EcoSystem: Copilot, CodeSpaces, and GitHub Actions Microsoft Azure Fundamentals (AZ-900) Certification Google Professional Cloud Architect Certification Course 2023 (Rough Draft) AWS Solutions Architect Professional (SAP-C02) 2023.

Abstract: Dive deep into the world of AI with our ChatGPT coding masterclass. Whether you're new to coding or seeking to expand your skillset, this course will guide you step by step, ensuring that you become proficient in leveraging the potential of ChatGPT across multiple programming languages. Course Highlights: A Comprehensive Introduction: Familiarize yourself with the inner workings of ChatGPT, its advantages and disadvantages in the realm of AI chatbots, and how it compares to other chatbots available in the market. Smooth Onboarding: Get up and running quickly with guided instructions on account setup, essential installations, and writing your first ChatGPT command. Gaming with Javascript and ChatGPT: Unearth the symbiotic relationship between JavaScript and ChatGPT. Craft engaging games such as timers and Tic-Tac-Toe, all powered by the intelligence of ChatGPT. Expand Your Web Development Skills: Dive into the React.JS ecosystem. From initial installations to understanding components in ChatGPT and mastering routing, this section melds the worlds of modern web development with conversational AI. Conversational Coding with C++: For those looking to venture into more traditional coding paradigms, the course provides a robust introduction to C++ in tandem with ChatGPT. Create intriguing applications like a guess-the-number game while honing your C++ skills. Advanced Bot Functions and Data Visualization: Go beyond chat and dive into practical, real-world applications. Develop an OTP password generator, visualize data with histograms, and work with aggregate and time series data plots--all while harnessing the power of ChatGPT. This masterclass is not just a course but a comprehensive journey, transforming you from a curious learner to a ChatGPT coding maestro. With its blend of foundational knowledge, practical applications, and forward-thinking integrations, this course is designed to appeal to a broad audience.

Abstract: This course is a comprehensive training program designed for IT beginners and network students eager to delve into the fundamentals of network security. In today's digital age, safeguarding information and data is of paramount importance, and this course equips participants with the essential knowledge and skills to excel in the field of cybersecurity. This course is ideal for individuals with a basic understanding of Linux programming, and it provides a solid foundation in network defense and information security. Our primary goal is to enable trainees to reach competency and expertise in network defense and information security skills, ensuring they are well-prepared to navigate the complexities of the digital landscape. The curriculum is thoughtfully structured and covers a wide range of topics, making it accessible and engaging for learners at various levels. By the end of this course, you'll possess a comprehensive understanding of network security and defense, preparing you to tackle real-world challenges in the field. Distributed by Manning Publications This course was created independently by Meta Brains and is distributed by Manning through our exclusive liveVideo platform.

Abstract: Embark on an exciting journey into the world of networking. Whether you're a novice looking to start your career in IT or an experienced professional seeking to enhance your knowledge, our CCNA Networking course is designed to provide you with comprehensive insights into the fundamentals and advanced aspects of networking. In this course, you will dive deep into the essential building blocks of networking. We begin with a thorough exploration of the TCP/IP protocol suite, which forms the backbone of the Internet and modern networks. You'll gain a solid understanding of IP addressing, subnetting, and the intricacies of both IPv4 and IPv6. Moving forward, we delve into VLANs, their configurations, and how they segment network traffic efficiently. You'll master the art of routing with a focus on routing protocols such as EIGRP and OSPF, enabling you to design and manage complex network infrastructures. Security is paramount in today's interconnected world, and our course covers this critical area extensively. You'll learn about access control lists (ACLs), port security, and other measures to protect your network from threats. By the end of this course, you'll have the knowledge and skills necessary to excel in the field of networking. Whether you aspire to obtain the prestigious Cisco Certified Network Associate (CCNA) certification or simply want to bolster your networking expertise, this course is your gateway to success. Distributed by Manning Publications This course was created independently by Meta Brains and is distributed by Manning through our exclusive liveVideo platform.

Abstract: Enter the Web Design Playground and start experimenting with all aspects of creating a web page--from design, to development, to publishing--in an easy-to-use free online workspace. This exciting second edition of Web Design Playground is fully updated with new technologies and thoughtful approaches for building modern websites. You'll have a blast experimenting with a landing page, photo gallery, portfolio site, and more while you learn important web design skills. In Web Design Playground, Second Edition you'll learn essential tools of the web design trade, such as: Structuring a web page with HTML Styling a web page with CSS Modern page layout techniques Using colors in web design Making text look awesome with typography HTML, CSS, and the principles of good web design are all you need to build something beautiful! You'll find them all inside this one-of-a-kind guide. Best of all, this book gives you free access to a custom online workspace, the "playground!" You can concentrate on core skills like page layout and adding images and video, as well as learning typography, responsive design, and the other modern web design techniques. About the Technology If you can use a web browser, you can create a web site! Web Design Playground, Second Edition shows you how, progressing step by step through fun and engaging projects. You learn the basics of HTML, CSS, and other important web skills. With its unique online "playground," the book helps you build a landing page, a photo gallery, a portfolio site, and more, all from scratch. No prior experience or knowledge of special tools is required. About the Book Web Design Playground, Second Edition takes a creative, visual approach and clear explanations of the components, concepts, and of each step you'll need to build your own web pages. You'll become a confident web designer as you practice each new skill in the Playground. The many small projects introduce everything from page layout basics to new tags and features like Flexbox and CSS Grid--all presented in author Paul McFedries's inimitably friendly style. Don't worry about setting up your own servers and domain names--the book comes with a free online "playground" to experiment with and get creative. You can concentrate on core skills like page layout and adding images and video, as well as learning typography, responsive design, and the other modern web design techniques. Before you know it, you'll be ready to create gorgeous pages that reflect your creativity and style. What's Inside Structure a web page with HTML Style a web page with CSS Modern page layout techniques How to use colors and typography About the Reader No web design experience required. About the Author Paul McFedries has written more than 100 books, which have sold over four million copies worldwide. Quotes A must-have book for learning HTML and CSS. - Adam Wan, Nexplore Excellent! A must-read for anyone who wants a great start in the art of web development! - Srikar Vedantam, Volvo Group.

Abstract: This comprehensive course, designed for budding developers and tech enthusiasts, delves deep into the fascinating world of AI chatbot development using two powerful tools: React.js and OpenAI's ChatGPT. With a focus on practical, hands-on learning, the course guides you through every step of creating a dynamic, AI-powered chatbot application. Spanning several detailed modules, the course begins with a solid foundation in React.js, a popular JavaScript library for building user interfaces. You'll learn to set up your development environment and understand the basics of React components, state management, and the overall architecture of a React application. This knowledge is crucial as you start to build the layout and interface of your chatbot. The heart of the course lies in the integration of ChatGPT, OpenAI's advanced AI language model. You'll explore how to seamlessly incorporate ChatGPT into your React application, creating a responsive, intelligent chatbot. The course covers essential topics like API integration, handling user inputs, and generating AI responses, ensuring your chatbot is both functional and engaging. API integration is a key focus, as you'll learn to connect your React app with ChatGPT through a backend, using Node.js and Express.js. This section includes practical exercises on setting up servers, managing API requests and responses, and ensuring smooth communication between your front end and the AI model. UI/UX design: you'll learn to create an intuitive, user-friendly interface for your chatbot, ensuring a seamless user experience. The course covers advanced UI topics such as styling, layout design, and incorporating interactive elements, making your chatbot not only smart but also visually appealing. By the end of this course, you'll have a fully functional AI chatbot, and more importantly, a deep understanding of integrating AI technologies with web development. Whether you;re a beginner looking to enter the world of AI and React, or a developer seeking to expand your skillset, this course offers valuable knowledge and hands-on experience in the cutting-edge field of AI chatbots. Distributed by Manning Publications This course was created independently by Skool of AI (Owned by Meta Brains) and is distributed by Manning through our exclusive liveVideo platform.

Abstract: Dive into the world of artificial intelligence with this comprehensive course designed to unravel the intricacies of Bard AI, Google's pioneering language model that stands at the forefront of AI technology. Spanning over seven insightful sections, the course offers a deep dive into Bard AI's capabilities, setting a foundation with an introduction to AI and language models, followed by an in-depth exploration of Bard AI's unique features. Discover the revolutionary aspects of text generation, contextual understanding, and multilingual support that Bard AI offers. These features not only enhance the efficiency of content creation but also pave the way for innovative applications in customer service, education, and more. The course meticulously compares Bard AI with other leading models like GPT-3 and GPT-4, highlighting its unique selling points and potential areas for development. A crucial section of the course is dedicated to programmers, where you'll learn how Bard AI can assist in coding practices, from generating code snippets to identifying errors and improving performance. The course also projects the prospects of Bard AI, envisioning its role in advancing society and technology. By the end of this course, you'll have a comprehensive understanding of Bard AI, equipped with the knowledge to apply its features in various sectors effectively. Whether you're a programmer, content creator, or simply an AI enthusiast, this course is your gateway to mastering one of the most versatile language models in the AI landscape. Distributed by Manning Publications This course was created independently by Skool of AI (Owned by Meta Brains) and is distributed by Manning through our exclusive liveVideo platform.

Abstract: Embark on a transformative odyssey through the intricacies of C++ programming with our meticulously crafted course. Tailored to both novice enthusiasts and seasoned developers alike, this comprehensive learning experience ventures deep into the nuances that differentiate C from C++, providing a solid foundation for learners. Immerse yourself in the intricate anatomy of the C++ language, and learn the concepts of data manipulation through variables and arrays. Delve into the multifaceted landscape of C++ operators, flow control mechanisms, and selection statements, and become adept at handling iteration and jump statements with finesse. Navigate the expansive realm of functions, pointers, and multidimensional arrays, unraveling the complexities inherent in dynamic memory allocation and file handling. Uncover the sophisticated world of user-defined data types, explore the elegance of structures, and dive headfirst into the bedrock of object-oriented programming principles, featuring classes, inheritance, polymorphism, encapsulation, and abstraction. Traverse the fundamentals of data structures, gaining proficiency in essential operations, linked lists, and the intricacies of stacks and queues. By the culmination of this enriching course, not only will you possess a profound understanding of C++, but you'll also wield the expertise necessary to tackle real-world programming challenges with confidence. Distributed by Manning Publications This course was created independently by Meta Brains and is distributed by Manning through our exclusive liveVideo platform.

Abstract: Secure your Azure applications the right way. The expert DevSecOps techniques you'll learn in this essential handbook make it easy to keep your data safe. As a Program Manager at Microsoft, Bojan Magusic has helped numerous Fortune 500 companies improve their security posture in Azure. Now, in Azure Security he brings his experience from the cyber security frontline to ensure your Azure cloud-based systems are safe and secure. In Azure Security you'll learn vital security skills, including how to: Set up secure access through Conditional Access policiesImplement Azure WAF on Application Gateway and Front Door Deploy Azure Firewall Premium for monitoring network activities Enable Microsoft Defender for Cloud to assess workload configurations Utilize Microsoft Sentinel for threat detection and analytics Establish Azure Policy for compliance with business rules Correctly set up out-of-the-box Azure services to protect your web apps against both common and sophisticated threats, learn to continuously assess your systems for vulnerabilities, and discover cutting-edge operations for security hygiene, monitoring, and DevSecOps. Each stage is made clear and easy to follow with step-by-step instructions, complemented by helpful screenshots and diagrams. About the Technology Securing cloud-hosted applications requires a mix of tools, techniques, and platform-specific services. The Azure platform provides built-in security tools to keep your systems safe, but proper implementation requires a foundational strategy and tactical guidance. About the Book Azure Security details best practices for configuring and deploying Azure's native security services--from a zero-trust foundation to defense in depth (DiD). Learn from a Microsoft security insider how to establish a DevSecOps program using Microsoft Defender for Cloud. Realistic scenarios and hands-on examples help demystify tricky security concepts, while clever exercises help reinforce what you've learned. What's Inside Set up secure access policies Implement a Web Application Firewall Deploy MS Sentinel for monitoring and threat detection Establish compliance with business rules About the Reader For software and security engineers building and securing Azure applications. About the Author Bojan Magusic is a Product Manager with Microsoft on the Security Customer Experience Engineering Team. Quotes Tells an end-to-end story, from introductory cyber-security foundations to advanced security tooling in Azure. - Yuri Diogenes, Microsoft Cloud Security Provides excellent coverage of key security capabilities in and around Azure, with valuable guidance for beginners and experts alike. - Prashant Dwivedi, National Informatics Centre, India The most comprehensive and up-to-date content that I have seen on Azure Security. This book covers it all. - Michael Heil, ai.dopt.

Abstract: In the rapidly evolving world of graphic design, the integration of Artificial Intelligence (AI) has been a game changer. Our course is meticulously designed to navigate this new terrain. Spanning eight comprehensive sections, this course offers an in-depth exploration of AI's influence on graphic design, focusing on advanced software such as DALL-E and MidJourney, as well as the robust capabilities of Figma. Section 1 lays the foundation, delving into the history and current trends of AI in graphic design. It predicts the future role of AI, setting the stage for practical applications. In Section 2, students will gain hands-on experience with AI design tools, including a detailed analysis of DALL-E and MidJourney, and mastering Figma's advanced features. This section emphasizes the seamless integration of AI into design workflows. Sections 3 and 4 focus on specific design tasks: creating AI-enhanced landing pages and crafting memorable logos using AI and Figma. These sections blend theoretical understanding with practical skills, ensuring students can effectively apply AI recommendations in their designs. In Section 5, the focus shifts to designing PowerPoint imagery, leveraging AI tools for enhanced presentation design. Following this, Section 6 introduces advanced design techniques where Figma meets AI, including animation and predictive design. Section 7 is crucial, addressing the ethical dimensions and best practices in AI design. This includes understanding AI biases and navigating the intellectual property challenges posed by AI-generated designs. The course culminates in a final project (Section 8), where students merge their AI and Figma skills to create a comprehensive branding page, followed by peer reviews and reflections. This course is not just about learning tools; it's about embracing a new design ethos where AI and human creativity coalesce to redefine the graphic design landscape. Whether you're a seasoned designer or a newcomer, this course equips you with the knowledge and skills to thrive in the AI-augmented world of graphic design. Distributed by Manning Publications This course was created independently by Skool of AI (Owned by Meta Brains) and is distributed by Manning through our exclusive liveVideo platform.

Abstract: This course offers a comprehensive exploration of prompt engineering, a critical skill in the evolving landscape of artificial intelligence (AI). Aimed at educators, developers, and technology enthusiasts, this curriculum bridges the gap between theoretical knowledge and practical application in the field of AI. Beginning with a foundational understanding, Lecture 1 delves into the essentials of prompts, their key features, and real-world examples, setting the stage for more advanced topics. Lecture 2 shifts the focus to text prompts, dissecting their structure and utility specifically for developers. This segment is crucial for understanding how language models like ChatGPT interpret and respond to textual inputs. The course then progresses to image prompts in Lecture 3, offering a deep dive into the intricate world of visual AI. Here, participants will explore Midjourney prompts, a term encompassing the journey from prompt creation to image generation. This lecture also covers custom preferences, and various parameters such as aspect ratio, chaos, seeds, style, and normalization, which are pivotal in tailoring image prompts to specific needs. Lecture 5 addresses a critical aspect of AI interaction: error handling. Participants will learn strategies to craft prompts that effectively manage errors, a skill particularly beneficial for student instruction and troubleshooting. The course culminates in a hands-on project, where participants will apply their knowledge to create a website using ChatGPT and Midjourney. This two-part project not only reinforces learning but also demonstrates practical applications of prompt engineering in website development. This course is designed to equip participants with the skills to navigate and utilize prompt engineering effectively, making it an indispensable resource for those seeking to integrate emerging technology into teaching and development in higher education. Distributed by Manning Publications This course was created independently by Skool of AI (Owned by Meta Brains) and is distributed by Manning through our exclusive liveVideo platform.

Abstract: Agile with AI Enhancing Agile Methodologies with Artificial Intelligence This video course explores the integration of Agile practices with Artificial Intelligence (AI) to streamline software development processes and improve productivity. By combining the principles of Agile and the capabilities of AI, you can unlock new levels of efficiency and innovation. Lessons Covered Include: 1.0 Course Introduction 2.1 Waterfall Planning 2.2 Playground vs. Plant Analogy 3.2 Pragmatic Agile 3.15 Productivity Techniques 4.1 AIOps (Artificial Intelligence for IT Operations) 4.2 Diagram Prompt Engineering 4.3 Summarizing Text with Claude 4.4 AI Pair Programming: Paradigm Shift 4.5 AWS CodeWhisperer for Rust 4.7 Serverless Bedrock Diagram 4.8 Bedrock Knowledge Agent: Retrieval-Augmented Generation (RAG) 4.9 Building Blocks for Generative AI: WhisperCPP RAW Learning Objectives Understand the foundations of Agile methodologies and their importance in software development Learn techniques for enhancing Agile practices with AI tools and techniques Explore AI-powered productivity techniques for streamlining development workflows Discover AI-driven approaches to pair programming, code generation, and prompt engineering Gain insights into cutting-edge AI applications in software development, such as AIOps and knowledge agents Learn to leverage AI tools like AWS CodeWhisperer and Retrieval-Augmented Generation (RAG) models Additional Popular Resources Assimilate OpenAI 52 Weeks of AWS-The Complete Series Microsoft Azure Fundamentals (AZ-900) Certification Rust Bootcamp Python Bootcamp Google Professional Machine Learning Engineer Course 2023 (Rough Draft) Rust Data Engineering Building with the GitHub EcoSystem: Copilot, CodeSpaces, and GitHub Actions Microsoft Azure Fundamentals (AZ-900) Certification Google Professional Cloud Architect Certification Course 2023 (Rough Draft) AWS Solutions Architect Professional (SAP-C02) 2023.

Abstract: Learn statistics by analyzing professional basketball data! In this action-packed book, you'll build your skills in exploratory data analysis by digging into the fascinating world of NBA games and player stats using the R language. Statistics Slam Dunk is an engaging how-to guide for statistical analysis with R. Each chapter contains an end-to-end data science or statistics project delving into NBA data and revealing real-world sporting insights. Written by a former basketball player turned business intelligence and analytics leader, you'll get practical experience tidying, wrangling, exploring, testing, modeling, and otherwise analyzing data with the best and latest R packages and functions. In Statistics Slam Dunk you'll develop a toolbox of R programming skills including: Reading and writing data Installing and loading packages Transforming, tidying, and wrangling data Applying best-in-class exploratory data analysis techniques Creating compelling visualizations Developing supervised and unsupervised machine learning algorithms Executing hypothesis tests, including t-tests and chi-square tests for independence Computing expected values, Gini coefficients, z-scores, and other measures If you're looking to switch to R from another language, or trade base R for tidyverse functions, this book is the perfect training coach. Much more than a beginner's guide, it teaches statistics and data science methods that have tons of use cases. And just like in the real world, you'll get no clean pre-packaged data sets in Statistics Slam Dunk. You'll take on the challenge of wrangling messy data to drill on the skills that will make you the star player on any data team. About the Technology Statistics Slam Dunk is a data science manual with a difference. Each chapter is a complete, self-contained statistics or data science project for you to work through--from importing data, to wrangling it, testing it, visualizing it, and modeling it. Throughout the book, you'll work exclusively with NBA data sets and the R language, applying best-in-class statistics techniques to reveal fun and fascinating truths about the NBA. About the Book Is losing basketball games on purpose a rational strategy? Which hustle statistics have an impact on wins and losses? Does spending more on player salaries translate into a winning record? You'll answer all these questions and more. Plus, R's visualization capabilities shine through in the book's 300 plots and charts, including Pareto charts, Sankey diagrams, Cleveland dot plots, and dendrograms. What's Inside Transforming, tidying, and wrangling data Applying best-in-class exploratory data analysis techniques Developing supervised and unsupervised machine learning algorithms Executing hypothesis tests and effect size tests About the Reader For readers who know basic statistics. No advanced knowledge of R--or basketball--required. About the Author Gary Sutton is a former basketball player who has built and led high-performing business intelligence and analytics organizations across multiple verticals. Quotes In this journey of exploration, every computer scientist will find a valuable ally in understanding the language of data. - Kim Lok©ıy, areo Transcends other R titles by revealing the hidden narratives that lie within the numbers. - Christian Sutton, Shell International Exploration and Production Seamlessly blending theory and practical insights, this book serves as an indispensable guide for those venturing into the field of data analytics. - Juan Delgado, Sodexo BRS.

Abstract: Get ready to code like a pro in Rust with insider techniques used by Rust veterans! Code Like a Pro in Rust dives deep into memory management, asynchronous programming, and the core Rust skills that make you a Rust pro! Plus, you'll find essential productivity techniques for Rust testing, tooling, and project management. You'll soon be writing high-quality code that needs way less maintenance overhead. In Code Like A Pro in Rust, you will learn: Essential Rust tooling Core Rust data structures Memory management Testing in Rust Asynchronous programming for Rust Optimized Rust Rust project management Code Like A Pro in Rust is a fast-track guide to building and delivering professional quality software in Rust. It skips the fluff and gets right to the heart of this powerful modern language. You'll learn how to sidestep common Rust pitfalls and navigate quirks you might never have seen before--even if you've been programming for many years! Plus, discover timeless strategies for navigating the evolving Rust ecosystem and ensure your skills can easily adapt to future changes. About the Technology Rust is famous for its safety, performance, and security, but it takes pro skills to make this powerful language shine. This book gets you up to speed fast, so you'll feel confident with low-level systems, web applications, asynchronous programming, concurrency, optimizations, and much more. About the Book Code Like a Pro in Rust will make you a more productive Rust programmer. This example-rich book builds on your existing know-how by introducing Rust-specific design patterns, coding shortcuts, and veteran skills like asynchronous programming and integrating Rust with other languages. You'll also meet amazing Rust tools for testing, code analysis, and application lifecycle management. It's all the good stuff in one place! What's Inside Core Rust data structures Memory management Creating effective APIs Rust tooling, testing, and more About the Reader Assumes you know Rust basics. About the Author Brenden Matthews is a software engineer, entrepreneur, and a prolific open source contributor who has been using Rust since the early days of the language. Quotes There's something for every Rust developer in here. Full of tips. - Tim McNamara, Founder of Accelerant.dev, Author of Rust in Action Wastes no time jumping headfirst into Rust development. It's a great resource to get up to speed in Rust quickly. - Patrick Walton, Meta With this book, you will become a Rust pro. - Jaume L©đpez Fundaci©đ, Institut Guttmann Hands-on, practical, and understandable. - Satej Kumar Sahu, Boeing For all aspiring Rustaceans. - Simon Tschoeke, German Edge Cloud.

Abstract: Proven techniques and principles for modernizing legacy systems into new architectures that deliver serious competitive advantage. For a business to thrive, it needs a modern software architecture that is aligned with its corporate architecture. This book presents concrete practices that sync software, product, strategy, team dynamics, and work practices. You'll evolve your technical and social architecture together, reducing needless dependencies and achieving faster flow of innovation across your organization. In Architecture Modernization: Socio-technical alignment of software, strategy, and structure you'll learn how to: Identify strategic ambitions and challenges using listening and mapping tours Visualize your business landscape and crucial capabilities with Wardley Mapping Create a product taxonomy as a framework for your architecture Run big picture EventStorming workshops to map business domains Apply Team Topologies patterns to identify and refine value streams Design loosely coupled, domain-aligned software architectures Build internal developer platforms for rapid, reliable evolution Implement data mesh principles and tools to revolutionize data engineering Deliver compelling modernization roadmaps focused on continuous value Architecture Modernization: Socio-technical alignment of software, strategy, and structure shows you how to turn the practice of architecting systems into a transformative process for your entire company. Chapter-by-chapter, you'll identify the reasons and benefits of modernization, design an architecture that works for your business, and then implement your new approach in a progressive and sustainable manner. Every technique is illustrated with insightful industry examples and an interactive Miro board that lets you dig deeper. About the Technology The decisions you make about your software are inherently connected to the decisions you make about your business. Why not turn the mundane task of modernizing legacy systems into a transformative process for your entire company? This book shows you how! It reveals a socio-technical approach to align your software and products with organizational dynamics and ways of working. About the Book Architecture Modernization: Socio-technical alignment of software, strategy, and structure presents a clear path for upgrading your entire organization when you re-imagine your software. In it, you'll learn to combine practices like Domain-Driven Design, Event Storming, and Wardley Mapping to discover user needs, design optimal architecture, and avoid falling back into old habits. Provocative examples from Danske, Salesforce, the UK Government, and others show the real-world result of each approach, identifying techniques you can apply effectively in your own business. What's Inside Uncover cross-org challenges and opportunities A product-centric approach to architecture Envision architecture as a portfolio to prioritize investment About the Reader For CTOs, tech leads, and principal engineers who decide on architecture and organization design. About the Authors Nick Tune helps organizations modernize their architectures through empowered product teams and continuous delivery. Jean-Georges Perrin builds innovative and modern data platforms. The technical editor on this book was Kamil Nicieja. Quotes Nick has a rare gift of making complex topics digestible and immediately actionable where the rubber meets the road. This book connects the dots of domain-driven design, Team Topologies, DevOps, product development, strategy, architecture, and leadership. - From the Foreword by Xin Yao, DDD consultant and socio-technical architect Helps you modernize your applications and organizational structures to support your business strategy and allow you to regain agility and momentum... I plan to use this approach in my work. - Eoin Woods, Endava Guides you through every twist and turn of your modernization journey. - Vlad Khononov, Technology Consultant.

Abstract: A clear and practical beginner's guide that shows you just how easy it can be to make the switch to Kubernetes! Kubernetes for Developers reveals practical and painless methods for deploying your apps on Kubernetes--even for small-to-medium sized applications! You'll learn how to migrate your existing apps onto Kubernetes without a rebuild, and implement modern cloud native architectures that can handle your future growth. Inside, you'll learn how to: Containerize a web application with Docker Host a containerized app on Kubernetes with a public cloud service Save money and improve performance with cloud native technologies Make your deployments reliable and fault tolerant Prepare your deployments to scale without a redesign Monitor, debug and tune application deployments on Kubernetes Designed for busy working developers, this hands-on guide helps your first steps into Kubernetes using the powerful Google Kubernetes Engine (GKE) service. Learn how the GKE's powerful automation tools can perform automatic checks and scaling, giving you more time to spend developing great applications. You'll soon see that you don't need to incur huge costs or have the manpower of an enterprise organization to get a productivity boost from Kubernetes! About the Technology Modern software needs to perform at scale while effectively handling load balancing, state and security. Kubernetes makes these tasks easier and more reliable for apps of any size. This book, written especially for software developers creating applications that run on Kubernetes, shows you exactly how to address these and other important issues. About the Book Kubernetes for Developers covers everything you need to know to containerize and deploy an app on Kubernetes from the developer's perspective. You'll start by creating a small application you can run on a cloud-based Kubernetes cluster. Then, you'll systematically explore best practices for stable long-term deployment, including scaling, capacity planning, and resource optimization. What's Inside Deploying reliable web applications using automated operations Scaling up without an application redesign Monitoring, debugging, and tuning workloads About the Reader For developers familiar with building or deploying web applications. No Docker or Kubernetes experience required. About the Author William Denniss is a product manager at Google working on Google Kubernetes Engine. Quotes A comprehensive and easy to consume guide with a focus on actually using Kubernetes. It speaks to the vast majority of developers who just want to get their work done and deployed. - Tim Hockin, Google A stand out in the crowd of Kubernetes resources. It's easy to follow, and provides highly focused practical examples. - Kevin Deggelman, San Francisco Giants Make your engineering team read this book. It shuts the door on any delays in adopting Kubernetes. - Dan Garfield, Codefresh The perfect complement to Kubernetes in Action. Developers need this book. - Pierre-Michel Ansel, 8x8.

Abstract: Practical methods for analyzing your data with graphs, revealing hidden connections and new insights. Graphs are the natural way to represent and understand connected data. This book explores the most important algorithms and techniques for graphs in data science, with concrete advice on implementation and deployment. You don't need any graph experience to start benefiting from this insightful guide. These powerful graph algorithms are explained in clear, jargon-free text and illustrations that makes them easy to apply to your own projects. In Graph Algorithms for Data Science you will learn: Labeled-property graph modeling Constructing a graph from structured data such as CSV or SQL NLP techniques to construct a graph from unstructured data Cypher query language syntax to manipulate data and extract insights Social network analysis algorithms like PageRank and community detection How to translate graph structure to a ML model input with node embedding models Using graph features in node classification and link prediction workflows Graph Algorithms for Data Science is a hands-on guide to working with graph-based data in applications like machine learning, fraud detection, and business data analysis. It's filled with fascinating and fun projects, demonstrating the ins-and-outs of graphs. You'll gain practical skills by analyzing Twitter, building graphs with NLP techniques, and much more. About the Technology A graph, put simply, is a network of connected data. Graphs are an efficient way to identify and explore the significant relationships naturally occurring within a dataset. This book presents the most important algorithms for graph data science with examples from machine learning, business applications, natural language processing, and more. About the Book Graph Algorithms for Data Science shows you how to construct and analyze graphs from structured and unstructured data. In it, you'll learn to apply graph algorithms like PageRank, community detection/clustering, and knowledge graph models by putting each new algorithm to work in a hands-on data project. This cutting-edge book also demonstrates how you can create graphs that optimize input for AI models using node embedding. What's Inside Creating knowledge graphs Node classification and link prediction workflows NLP techniques for graph construction About the Reader For data scientists who know machine learning basics. Examples use the Cypher query language, which is explained in the book. About the Author Toma¿ℓ Bratani♯⁻ works at the intersection of graphs and machine learning. Arturo Geigel was the technical editor for this book. Quotes Undoubtedly the quickest route to grasping the practical applications of graph algorithms. Enjoyable and informative, with real-world business context and practical problem-solving. - Roger Yu, Feedzai Brilliantly eases you into graph-based applications. - Sumit Pal, Independent Consultant I highly recommend this book to anyone involved in analyzing large network databases. - Ivan Herreros, talentsconnect Insightful and comprehensive. The author's expertise is evident. Be prepared for a rewarding journey. - Michal ¿ tefa¿⁸©Łk, Volke.

Abstract: Fully updated to Elixir 1.15, this authoritative bestseller reveals how Elixir tackles problems of scalability, fault tolerance, and high availability. Thousands of developers have learned to build applications in Elixir by using Sa¿Ła Juri♯⁷'s Elixir in Action. You'll skip the programming basics or 101 introductions; this book builds on your existing knowledge to get you quickly writing real Elixir code. Along the way, you'll develop an appreciation for, and considerable skill in, functional and concurrent programming. Inside Elixir in Action, Third Edition you'll find: Updates for Elixir 1.15 Elixir modules, functions, and type system Functional and concurrent programming Introduction to distributed system design Creating deployable releases Fully updated to Elixir 1.15, this book contains new coverage of working with application configuration and the latest OTP releases. It teaches you the underlying principles and functional concepts of Elixir, and how each piece fits into the bigger picture of building production-ready systems with Elixir, Erlang, and the OTP framework. About the Technology With best-in-class fault tolerance and concurrency, a pragmatic approach to functional programming, and the power to operate at scale, Elixir is the perfect choice for mission-critical software. Start reading Elixir in Action, and you'll quickly understand why Elixir creator Jos©♭ Valim says it "...tops the list" of Elixir books. About the Book Elixir in Action, Third Edition teaches you how to create distributed applications and server-side systems using Elixir and the Erlang VM. This Third Edition from Elixir expert Sa¿Ła Juri♯⁷ is fully updated to include the latest features of Elixir 1.15. In it, you'll master the foundations of the language, discover how the OTP framework minimizes tedious boilerplate code, and explore numerous examples that ensure you're learning hands-on. What's Inside Elixir modules, functions, and type system Functional and concurrent programming Introduction to distributed system design Creating deployable releases About the Reader For programmers comfortable with client/server applications. No experience with Elixir, Erlang, or functional programming required. About the Author Sa¿Ła Juri♯⁷ uses Elixir and Erlang to build fault-tolerant, scalable, highly concurrent systems. Technical editor on this book was Marius Butuc. Quotes Ask any Elixir developer about their favorite book, and Elixir in Action tops the list. It's a testament to the value it brings to the community. - Jos©♭ Valim, Creator of Elixir Powerful insights that deepen my understanding of Elixir systems and a wonderful voice that makes all of that goodness easy to consume. - Bruce Tate, Founder of Grox.io Learning Focused and packed with practical insight into the language and the new runtime you are learning. - Lars Wikman, Founder & CEO, Underjord Start on page 1 and read till the end. You won't regret it. - Simon Hewitt, Nebulon Inc.

Abstract: Small Language Models and LLamaFile Learning About Small Language Models and Running Them Locally with LLamaFile This video series covers small language models, their advantages, and how to run them locally using the LLamaFile tool. Lessons Covered Include: 1.1 Introduction to Small Language Models 1.2 Demo: Running Phi Small Language Model with LLamaFile 2.1 Getting Started with LLamaFile 2.2 Demo: Running Lava Multi-Modal Vision Model with LLamaFile Learning Objectives Understand what small language models are and their advantages Learn how to run local language models using the LLamaFile tool See demos of running different small language models like Phi and Lava Additional Popular Resources Assimilate OpenAI 52 Weeks of AWS-The Complete Series Microsoft Azure Fundamentals (AZ-900) Certification Rust Bootcamp Python Bootcamp Google Professional Machine Learning Engineer Course 2023 (Rough Draft) Rust Data Engineering Building with the GitHub EcoSystem: Copilot, CodeSpaces, and GitHub Actions Microsoft Azure Fundamentals (AZ-900) Certification Google Professional Cloud Architect Certification Course 2023 (Rough Draft) AWS Solutions Architect Professional (SAP-C02) 2023.

Abstract: Unit testing is more than just a collection of tools and practices--it's a state of mind! This bestseller reveals the master's secrets for delivering robust, maintainable, and trustworthy code. Thousands of developers have learned to hone their code quality under the tutelage of The Art of Unit Testing. This revised third edition updates an international bestseller to reflect modern development tools and practices, as well as to cover JavaScript. Inside The Art of Unit Testing, Third Edition you will learn how to: Create readable, maintainable, and trustworthy tests Work with fakes, stubs, mock objects, and isolation frameworks Apply simple dependency injection techniques Refactor legacy code with confidence Test both frontend and backend code Effective unit tests streamline your software development process and ensure you deliver consistent high-quality code every time. With practical examples in JavaScript and Node, this hands-on guide takes you from your very first unit tests all the way to comprehensive test suites, naming standards, and refactoring techniques. You'll explore test patterns and organization, working with legacy code and even "untestable" code. The many tool-agnostic examples are presented in JavaScript and carefully designed so that they apply to code written in any language. About the Technology The art of unit testing is more than just learning the right collection of tools and practices. It's about understanding what makes great tests tick, finding the right strategy for each unique situation, and knowing what to do when the testing process gets messy. This book delivers insights and advice that will transform the way you test your software. About the Book The Art of Unit Testing, Third Edition shows you how to create readable and maintainable tests. It goes well beyond basic test creation into organization-wide test strategies, troubleshooting, working with legacy code, and "merciless" refactoring. You'll love the practical examples and familiar scenarios that make testing come alive as you read. This third edition has been updated with techniques specific to object-oriented, functional, and modular coding styles. The examples use JavaScript. What's Inside Deciding on test types and strategies Test Entry & Exit Points Refactoring legacy code Fakes, stubs, mock objects, and isolation frameworks Object-Oriented, Functional, and Modular testing styles About the Reader Examples use JavaScript, TypeScript, and Node.js. About the Authors Roy Osherove is an internationally-recognized expert in unit testing and agile software methodology. Vladimir Khorikov is the author of Manning's Unit Testing Principles, Practices, and Patterns, a Pluralsight author, and a Microsoft MVP. Quotes Our testing bible. The JavaScript community is fortunate to have it adapted to our favorite language. - Yoni Goldberg, Node.js testing consultant, author of Node.js Best Practices A testing masterpiece! - Jaume L©đpez, Institut Guttmann Teaches you the philosophy as well as the nuts and bolts for effective unit testing. - Matteo Gildone, Springer Nature A proper view of what to test, when, and how to do it well. - Rich Yonts, Teradata.

Abstract: Introduction to LLM vulnerabilities This introductory course on vulnerabilities for Large Language Models (LLMs) and language models in general. It provides a deep dive into the practical applications of large language models (LLMs) using Azure's AI services. Upon completion, learners will be able to: Explain the concept of model replication or model shadowing as a potential attack vector in large language models, and describe methods to mitigate it through techniques like rate limiting and buffering. Analyze the potential benefits and limitations of using pre-trained LLMs Develop strategies for mitigating risks and ethical considerations when deploying LLM-powered applications. Describe the high-level process of creating a large language model, including data collection, cleaning, and training. Explain the role of security in large language models and recognize potential security vulnerabilities and attack vectors. Identify insecure plugin designs in large language model software development kits (SDKs) that could lead to remote execution and implement strategies to secure plugins. You will learn how to secure your large language model (LLM) applications by addressing potential vulnerabilities. You will explore strategies to mitigate risks from insecure plugin design, including proper input validation and sanitization. Additionally, you will discover techniques to protect against sensitive information disclosure, such as using a redaction service to remove personally identifiable data from prompts and model responses. Finally, you will learn how to actively monitor your application dependencies for security updates and vulnerabilities, ensuring your system remains secure over time. Week 1: Foundations of Language Models This week you will get a brief overview of LLMs and how do they work Learning Objectives Analyze common types of generative applications and their architectures, including multi-model applications, and understand their challenges and benefits. Explain the functioning of a multi-model application, including the role of the framework and specialized machine learning models. Identify the advantages of smaller, specialized models in terms of resource usage, interaction speed, and deployment agility. Compare and contrast different generative AI application types, such as API-based, embedded models, and multi-model applications, and understand their use cases and challenges. Recognize the importance of large language models in various real-world applications, including text-based chatting, customer service, content creation, and daily tasks. Evaluate the benefits and drawbacks of large language models, considering aspects like accuracy, privacy, and potential misuse. Understand the basics of tokenization, indexing, and probability machines in the context of large language models. Describe the high-level process of creating a large language model, including data collection, cleaning, and training. Explain the role of security in large language models and recognize potential security vulnerabilities and attack vectors. Week 2: Language Model Vulnerabilities This week focuses on model-based vulnerabilities that you can explore with prompts. Learning Objectives Explain the concept of model replication or model shadowing as a potential attack vector in large language models, and describe methods to mitigate it through techniques like rate limiting and buffering. Identify and demonstrate insecure output handling in large language models, and understand the potential security threats and attack vectors associated with it. Understand prompt injection and its implications for large language models, including how certain applications define the initial behavior of these models and how to exploit implicit system prompts. Recognize model theft vulnerabilities and understand how handling and access to system components can impact model security, particularly in the context of dynamically loaded models from external sources. Week 3: System vulnerabilities This week you will learn how to deal with environments and system-based vulnerabilities as they relate to LLMs. Learning Objectives Identify insecure plugin designs in large language model software development kits (SDKs) that could lead to remote execution and implement strategies to secure plugins. Explain the potential risks of sensitive information disclosure in large language models and implement measures to redact personal identifiable information using HTTP APIs and regular expressions. Monitor and update dependencies in large language model applications to prevent potential security vulnerabilities and automate the process using tools like GitHub's Dependabot. Evaluate application vulnerabilities based on the programming language and framework, and implement measures to prevent potential security threats. Week 4: Other types of vulnerabilities Learning Objectives Identify potential security threats and vulnerabilities associated with large and small language models. Implement strategies to prevent security situations and guard against making environments more secure. Recognize the concept of excessive agency in large language models and its potential impacts on functionality. Explain the denial of service threat for large language models and describe methods to guard against API misuse.% About your instructor Alfredo Deza has over a decade of experience as a Software Engineer doing DevOps, automation, and scalable system architecture. Before getting into technology he participated in the 2004 Olympic Games and was the first-ever World Champion in High Jump representing Peru. He currently works in Developer Relations at Microsoft and is an Adjunct Professor at Duke University teaching Machine Learning, Cloud Computing, Data Engineering, Python, and Rust. With Alfredo's guidance, you will gain the knowledge and skills to understand and work with vulnerabilities within language models. Resources Introduction to Generative AI Responsible Generative AI and Local LLMS Practical MLOps book.

Abstract: This video series covers key concepts and technologies for virtualizing and containerizing applications. It introduces the benefits of virtualization, compares virtual machines and containers, and provides a deep dive into working with Docker containers. Through live demonstrations, you'll learn to create and manage virtual machines, pull Docker images, and run containerized applications.

Abstract: This comprehensive course teaches you to leverage the power of cloud computing to develop production-ready machine learning solutions. Starting with the fundamentals of cloud storage, security, and infrastructure as code, you will gain a solid foundation in cloud computing concepts. The course then dives into serverless machine learning, teaching you to build and deploy ML models using popular cloud AutoML platforms like Google AutoML, Amazon SageMaker, Microsoft Azure ML, and CreateML. Through hands-on labs, you'll learn to train custom models with just a few lines of configuration, without needing deep ML expertise. Next, the course explores serverless technologies like AWS Lambda, Google Cloud Functions, and Azure Functions to cost-effectively operationalize your ML models at scale. You'll learn to expose your AutoML models as serverless microservices, automatically scaling to handle any load. The course also covers serverless data processing and ETL to build complete ML pipelines. Finally, you'll learn to apply DevOps best practices to your serverless ML applications using continuous integration and delivery (CI/CD), infrastructure as code, monitoring, and containerization technologies like Docker and Kubernetes. By the end, you'll have the skills to build highly scalable end-to-end machine learning solutions leveraging the latest cloud AutoML and serverless technologies.

Abstract: The Application Security Program course teaches you to implement a robust program of security throughout your development process. It goes well beyond the basics, detailing flexible security fundamentals that can adapt and evolve to new and emerging threats. Its service-oriented approach is perfectly suited to the fast pace of modern development. Your team will quickly switch from viewing security as a chore to seeing it as an essential part of their daily work. Follow the expert advice in this guide and you'll reliably deliver software that is free from security defects and critical vulnerabilities.

Abstract: When you work in IT cyber security, you are responsible for ensuring that all operating systems are fully secured. Guide to Security for Linux Systems introduces you to the parameters and policies that will help you fulfill this responsibility. You will gain an understanding of the procedures and steps needed to secure operating systems; learn about the different types of security breaches you may encounter; and get familiar with the tools and software you can use to ensure a safe Linux system.

Abstract: Vue has swiftly become one of the most popular JavaScript frameworks, as well as the most approachable, in our opinion. New frameworks, however, can be intimidating, and no one wants to waste time setting up a local development environment only to run a simple app. That's where Vue is different. To get started with Vue, place a script tag on a page, and you're ready. This preparation will allow you to integrate Vue into your current apps without investing in complex toolchains. All of the examples in this course may be completed by simply adding Vue to a single HTML file and writing a little JavaScript. A series of tutorials, exercises, and quizzes will help you learn how to construct Vue apps. This course will help novices get started with Vue JS and work toward mastery.

Abstract: Hands-on Python for MLOps Build powerful APIs, tools, and scripts with Python Use Python to create APIs and automation scripts for machine learning operations. Learn to leverage APIs, build CLI tools, and develop web services. If you are new to Machine Learning Operations or want to know more about the foundations of Python for MLOps, this course will walk you through the basics. In this course, you'll learn how to use Python for automation, APIs, and building useful command-line interfaces. We'll cover consuming APIs, creating CLI tools, packaging projects, and building web services to expose machine learning models. The course includes hands-on examples and projects so you can apply what you learn right away. By the end of the course, you'll have practical skills to automate workflows and develop interfaces for machine learning. This course includes GitHub repositories you can reference: Python CLI Examples Basic Python CLI Web API with Python and Hugging Face models Learn objectives Consume and use APIs and SDKs in Python Create command-line programs for automation Develop web services and APIs with Python frameworks Package Python projects for distribution Apply skills to build useful interfaces for ML models Lesson 1: Working with APIs in Python Lesson Outline Overview of APIs and SDKs Using the Requests Library Consuming REST APIs Python SDKs like NumPy and SciPy Project: Building a Python script using APIs Lesson 2: Building Command-line Interfaces Lesson Outline Intro to automation with CLI tools Parsing arguments and options Organizing code into modules Python packaging for distribution Project: CLI tool for machine learning Lesson 3: Developing Web APIs Lesson Outline REST API concepts Web frameworks like Flask and FastAPI Building an API with Flask Developing APIs with FastAPI OpenAPI specs and documentation Project: Web API for movie recommendations About your instructor Alfredo Deza has over a decade of experience as a Software Engineer doing DevOps, automation, and scalable system architecture. Before getting into technology he participated in the 2004 Olympic Games and was the first-ever World Champion in High Jump representing Peru. He currently works in Developer Relations at Microsoft and is an Adjunct Professor at Duke University. This solid background in technology and teaching, including his past experience as a Linux system administrator is seen throughout this course, where you will get a first-hand experience with high-level knowledge and practical examples. Resources Pytest Master Class Practical MLOps book.

Abstract: If you would like to master JavaScript and get a job as a full-stack web developer, start with this course. You'll learn full-stack JavaScript development with over 24 hours of HD video tutorials covering ReactJS, NodeJS, LoopbackJS, Redux, Material-UI, and socket programming. And you'll learn these by putting them to work on three hands-on coding projects. A working knowledge of HTML, CSS and JavaScript will be helpful when taking this course. You'll work on three coding projects: Calculator Application Building this app will teach you the basics of React, how to create components, and how to work within the React life cycle. Weblog You'll use React and LoopbackJS to build a feature-rich blog app. We begin to explore the full-stack elements of JavaScript by coding our own REST API, and see how the front end and back end can communicate with each other. Chat Application With a WebSocket you can keep clients connected on the server side. We will explore socket programming building a chat app where you can create a user account, add other users, and then message back and forth with them.

Abstract: This course is for people who want to get into ecommerce, selling goods or services online, but have no idea where to start. We show you everything you need to know to build your own store on Shopify, one of the most popular platforms across the globe. And you won't need to write a line of code. You don't need to know anything about Shopify to take this course; you don't even need to know what you want to sell. The video provides an in-depth introduction to the ecommerce platform including the different Shopify store types and how to create them. Once you set up your online shop, you learn how to operate it, whether you use a traditional physical store where you own your inventory, or take advantage of dropshipping, where you fulfill orders from a third party without ever purchasing the products directly. We also introduce you to profitable products you can sell on a Shopify store, including physical and digital goods, consultation services, and many others. No coding, no experience necessary. All you need is the zeal to learn, and you'll be up and running in no time.

Abstract: If you want to build professional websites, WordPress, the popular and free open-source website creation platform, is a great tool to have in your back pocket. This course teaches you the conceptual framework of a WordPress-based Content Management System (CMS), as well as the practical steps for building a modern website or a blog. We start with WordPress installation and building blocks, the principles of the WordPress CMS, and a tour of the admin panel. Next you learn about posts, pages, and forums before jumping into a unit on using plugin management to add cool galleries and videos to your website or blog. You will also get to know about SEO and meta tags. The WordPress Crash Course winds up with a unit on WordPress themes, which make your sites and blogs look professional. You will also learn to customize and design your own themes. Get up and running with this easy-to-follow guide to everything you need to know about WordPress, from installing your first blog to maintaining a website after launch.

Abstract: AWS Certified Security - Specialty Exam Prep This video series provides comprehensive preparation for the AWS Certified Security - Specialty (SCS-C02) exam. Lessons Covered Include: Domain 1: Threat Detection and Incident Response 1.0 Introduction 1.1 Designing and Implementing Incident Response Plans 1.2 Detecting Security Threats and Anomalies with AWS Services 1.3 Responding to Compromised Resources and Workloads 1.4 Automating Incident Response with AWS Lambda 1.5 Conducting Root Cause Analysis with Amazon Detective 1.6 Capturing Forensics Data from Compromised Resources 1.7 Querying Logs to Validate Security Events 1.8 Preserving Forensic Artifacts with S3 Object Lock 1.9 Preparing and Recovering Services After Incidents 1.10 Incident Response Case Study 1.11 Practice Exam - Threat Detection and Response 1.12 Threat Detection and Incident Response Summary Learning Objectives Understand best practices for incident response in the cloud Explore AWS services to detect security threats Learn how to respond to compromised resources Domain 2: Security Logging and Monitoring 2.0 Introduction 2.1 Designing and Implementing Monitoring and Alerting 2.2 Troubleshooting Security Monitoring and Alerting 2.3 Designing and Implementing Logging Solutions 2.4 Troubleshooting Logging Solutions 2.5 Designing Log Analysis Solutions 2.6 Configuring AWS CloudTrail for Logging 2.7 Analyzing Logs with Amazon Athena 2.8 Monitoring Case Study 2.9 Practice Exam - Logging and Monitoring 2.10 Optimizing Log Storage Lifecycles 2.11 Third Party Log Analysis Tools 2.12 Security Logging and Monitoring Summary Learning Objectives Understand how to set up monitoring and alerts for security Learn best practices for logging and log analysis Gain skills in troubleshooting logging and monitoring Domain 3: Infrastructure Security 3.0 Introduction 3.1 Designing and Implementing Edge Service Security 3.2 Designing and Implementing Network Security 3.3 Designing and Securing Compute Workloads 3.4 Troubleshooting Network Security 3.5 Securing EC2 Instances with SSM 3.6 Scanning Images for Vulnerabilities 3.7 Infrastructure Security Case Study 3.8 Practice Exam - Infrastructure Security 3.9 Integrating AWS Firewall Manager 3.10 Applying Security Best Practices to Lambdas 3.11 Hardening AMIs with EC2 Image Builder 3.12 Infrastructure Security Summary Learning Objectives Learn how to secure AWS network infrastructure Understand options for compute and workload security Gain skills in troubleshooting infrastructure issues Domain 4: Identity and Access Management 4.0 Introduction 4.1 Designing Authentication for AWS Resources 4.2 Designing Authorization for AWS Resources 4.3 Troubleshooting with IAM Access Analyzer 4.4 Enforcing Least Privilege Access 4.5 Separating Duties with IAM Roles 4.6 Identity and Access Management Case Study 4.7 Practice Exam - Identity and Access Management 4.8 Securing Root User Credentials 4.9 IAM Policy Simulator for Troubleshooting 4.10 Enabling Federated Access with SSO 4.11 Managing Credentials and Secrets 4.12 Identity and Access Management Summary Learning Objectives Master IAM best practices for authentication and authorization Understand how to apply least privilege and separation of duties Learn to troubleshoot IAM issues Domain 5: Data Protection 5.0 Introduction 5.1 Data in Transit Confidentiality and Integrity 5.2 Data at Rest Confidentiality and Integrity 5.3 Managing Data at Rest Lifecycles 5.4 Protecting Credentials, Secrets, and Keys 5.5 Encrypting Data with AWS KMS 5.6 Data Protection Case Study 5.7 Practice Exam - Data Protection 5.8 Enforcing Data Retention with Glacier 5.9 Preventing Data Deletion with S3 Object Lock 5.10 Rotating RDS Credentials 5.11 Encrypting Data in Transit with SSL/TLS 5.12 Data Protection Summary Learning Objectives Learn techniques to protect data in transit and at rest Understand how to manage data lifecycles Gain skills in managing credentials and secrets Domain 6: Management and Security Governance 6.0 Introduction 6.1 Strategies for Central Account Deployment 6.2 Secure and Consistent Cloud Deployment 6.3 Evaluating Compliance of AWS Resources 6.4 Identifying Security Gaps through Reviews and Cost 6.5 AWS Organizations SCP Best Practices 6.6 Governance Case Study 6.7 Practice Exam - Governance 6.8 Automating Security Deployments 6.9 Tagging Resources for Governance 6.10 AWS Config for Security Assessments 6.11 AWS Well Architected Tool 6.12 Governance and Security Management Summary Learning Objectives Understand best practices for governing accounts and resources Learn how to align security with organizational requirements Gain skills in compliance, auditing, and deployment Additional Popular Resources Assimilate OpenAI 52 Weeks of AWS-The Complete Series Microsoft Azure Fundamentals (AZ-900) Certification AWS Solutions Architect Professional (SAP-C02) 2023 Assimilate Python From Zero.

Abstract: The next generation of containers is here. Learn Podman directly from its creator, discover its exceptional security features, and start managing rootless containers that integrate easily into your systems. In Podman in Action you will learn how to: Build and run containers in rootless mode Develop and manage pods Use SystemD to oversee a container's lifecycle Work with the Podman service via Python Keep your containers confined using Podman security features Manage containerized applications on edge devices Podman in Action shows you how to deploy containerized applications on Linux, Windows, and MacOS systems using Podman. Written by Daniel Walsh, who leads the Red Hat Podman team, this book teaches you how to securely manage the entire application lifecycle without human intervention. You'll quickly get to grips with Podman's unique advantages over Docker, and learn how easy it is to migrate your Docker-based infrastructure. It also demonstrates how, with Podman, you can easily convert containerized applications into Kubernetes-based microservices. About the Technology It's time to upgrade your container engine! The Podman container manager delivers flexible image layer control, seamless Kubernetes compatibility, and rootless containers that can be created, run, and managed by users without admin rights. Plus, its OCI-compliant support for the Docker API lets you shift existing containers to Podman without breaking your scripts or changing the way you work. About the Book Podman in Action introduces the Podman container manager. The easy-to-follow explanations and examples give you a clear view of what containers are, how they work, and how to manage them using Podman's powerful features. You'll get a deep look at the Linux components Podman uses and even learn more about Docker along the way. You'll especially appreciate author Dan Walsh's unique insights into container security. What's Inside Develop and manage pods Key security concepts including SELinux and SECCOMP Use systemd to oversee a container's lifecycle Keep your containers confined using Podman security Manage containerized applications on edge devices Install and run Podman on MacOS and Windows About the Reader For developers or system administrators experienced with Linux and Docker. About the Author Daniel Walsh is a senior distinguished engineer at Red Hat, and leads the team that created Podman. Quotes Red Hat's own master of container security beautifully explains this important container ecosystem. - Michael Bright, mjbright Consulting Filled to the brim with examples and best practices. - Mladen Kne¿ℓi♯⁷, CROZ Showcases Podman's architecture, advanced security features, rootless containers, integration with systemd, and much more. I highly recommend it. - Andrea Monacchi, Chili.com A must-read for anyone who wants to harness the power of Podman and the nextgen container ecosystem. - Gowtham Sadasivam, Acceldata.

Abstract: A vital guide to building the platforms and systems that bring deep learning models to production. In Designing Deep Learning Systems you will learn how to: Transfer your software development skills to deep learning systems Recognize and solve common engineering challenges for deep learning systems Understand the deep learning development cycle Automate training for models in TensorFlow and PyTorch Optimize dataset management, training, model serving and hyperparameter tuning Pick the right open-source project for your platform Deep learning systems are the components and infrastructure essential to supporting a deep learning model in a production environment. Written especially for software engineers with minimal knowledge of deep learning's design requirements, Designing Deep Learning Systems is full of hands-on examples that will help you transfer your software development skills to creating these deep learning platforms. You'll learn how to build automated and scalable services for core tasks like dataset management, model training/serving, and hyperparameter tuning. This book is the perfect way to step into an exciting--and lucrative--career as a deep learning engineer. Designing Deep Learning Systems: A software engineer's guide teaches you everything you need to design and implement a production-ready deep learning platform. First, it presents the big picture of a deep learning system from the developer's perspective, including its major components and how they are connected. Then, it carefully guides you through the engineering methods you'll need to build your own maintainable, efficient, and scalable deep learning platforms. Chi Wang is a principal software developer in the Salesforce Einstein group. Donald Szeto was the co-founder and CTO of PredictionIO.

Abstract: Deliver software that does what it's supposed to do! Behavior-Driven Development guides your software projects to success with collaboration, communication techniques, and concrete requirements you can turn into automated tests. In BDD in Action, Second Edition you'll learn how to: Implement and improve BDD practices Prioritize features from business goals Facilitate an example mapping session Write automated acceptance tests Scale up your automated acceptance tests Deliver accurate reporting and documentation Around half of all software projects fail to deliver on requirements. Behavior-Driven Development (BDD) helps make sure that yours isn't one of them. Behavior-Driven Development in Action, Second Edition teaches you how to ensure that everyone involved in a software project--from developers to non-technical stakeholders--are in agreement on goals and objectives. It lays out the communication skills, collaborative practices, and useful automation tools that will let you seamlessly succeed with BDD. Now in its second edition, this revised bestseller has been extensively updated with new techniques for incorporating BDD into large-scale and enterprise development practices such as Agile and DevOps. About the Technology Behavior-Driven Development is a collaborative software design technique that organizes examples of an application's desired behavior into a concrete, testable specification. Because the BDD process gathers input from all areas of an organization, it maximizes the likelihood your software will satisfy both end users and business stakeholders. The established collaboration practices and automation strategies in this book will help you maximize the benefits of BDD for your dev team and your business clients. About the Book In BDD in Action, Second Edition, you'll learn to seamlessly integrate BDD into your existing development process. This thoroughly revised new edition now shows how to integrate BDD with DevOps and large-scale Agile systems. Practical examples introduce cross-functional team communication skills, leading a successful requirements analysis, and how to set up automated acceptance criteria. What's Inside How BDD positively affects teamwork, dynamics, and collaboration with stakeholders Help teams discover and analyze requirements, uncover assumptions, and reduce risks Make acceptance, integration, and unit testing more effective Automate reporting and living documentation to improve transparency About the Reader For all development teams. No experience with BDD required. Examples in Java, JavaScript, and TypeScript can be easily expressed in your chosen language. About the Author John Ferguson Smart is the creator of the Serenity BDD framework and founder of the Serenity Dojo training school. Jan Molak is the author of the Serenity/JS testing framework, Jenkins Build Monitor, and other CD and testing tools. Quotes John and Jan describe valuable techniques with their customary clarity and detail. I found myself nodding along, as well as having a couple of 'Aha!' moments myself. I am delighted that BDD still has this much traction and interest nearly 20 years on, and I am grateful to John and Jan for producing this new edition of such a comprehensive resource. - From the Foreword by Daniel Terhorst-North, practitioner consultant If understanding how your own software should work is ever a hard question, you should read this book. - Kevin Liao, Sotheby's An approachable and accessible introduction. I recommend it to developers who want to quickly adopt BDD for their projects. - Lorenzo De Leon, West Monroe Partners.

Abstract: Programming is a creative act. These techniques will help you maximize the power of creativity to improve your software and your satisfaction in creating it. Inside The Creative Programmer you'll discover: The seven dimensions of creativity in software engineering The scientific understanding of creativity and how it translates to programming Actionable advice and thinking exercises that will make you a better programmer Innovative communication skills for working more efficiently on a team Creative problem-solving techniques for tackling complex challenges In The Creative Programmer you'll learn the processes and habits of highly creative individuals and discover how you can build creativity into your programming practice. This fascinating new book introduces the seven domains of creative problem solving and teaches practical techniques that apply those principles to software development. Hand-drawn illustrations, reflective thought experiments, and brain-tickling example problems help you get your creative juices flowing--you'll even be able to track your progress against a scientifically validated Creative Programming Problem Solving Test. Before you know it, you'll be thinking up new and novel ways to tackle the big challenges of your projects. About the Technology Like composing music, starting a business, or designing a marketing campaign, programming is a creative activity. And just like technical skills, creativity can be learned and improved with practice! This thought-provoking book details practical methods to turn creativity into more effective problem solving, higher productivity, and better software. About the Book The Creative Programmer explores seven dimensions of creativity in software engineering--technical knowledge, collaboration, constraints, critical thinking, curiosity, a creative state of mind, and creative techniques. As you read, you'll apply insights about creativity from other disciplines to the challenges of software development. Numerous relevant examples and exercises drive each lesson home. You'll especially enjoy the unique Creative Programming Problem Solving Test that helps you assess how creative you've been with a programming task. What's Inside The scientific understanding of creativity and how it translates to programming Advice and exercises that will help you become a creative programmer Innovative communication skills for working more efficiently on a team Creative problem-solving techniques for tackling complex challenges About the Reader For programmers of all skill levels. About the Author Wouter Groeneveld is a software engineer and computer science education researcher at KU Leuven, where he researches the importance of creativity in software engineering. Quotes The Creative Programmer is a fantastic mix of engaging historical anecdotes, practical exercises, and extensive references to papers, books, and essays both in and outside of programming.... My own copy has now been filled with pages of scribbles and notes on which I could immediately apply Wouter's lessons, a sign that his exercises are truly engaging and encouraging! - From the Foreword by Dr. Felienne Hermans, Professor of Computer Science Education, Vrije Universiteit Amsterdam, author of The Programmer's Brain Beautifully written and utterly compelling. I love the research, the insight, and the sheer joy Wouter conveys in his writing. - Daniel Terhorst-North, Dan North & Associates.

Abstract: VBA (visual basic for application) is a language used for programming tasks and actions in Excel, and for developing additional functions in Excel worksheets that are customized to your work needs. If you want to learn how to program VBA for your business or yourself, then this course is for you. As a beginner course, it starts with the basics--understanding what VBA is and what it does. Next you'll record your first macro, and eventually you will know enough to create your own functional VBA modules. By the end of the course, you'll be creating custom Excel functions and making your user forms so other users can interact with them and input their data. You'll also be able to troubleshoot and debug your code, making it fast and efficient. Once you learn VBA, you'll know it forever, and eventually you can program it to do all your work.

Abstract: Rust Bootcamp Course Overview Welcome to our comprehensive Rust programming course! In this immersive learning experience, we will guide you through every aspect of Rust, empowering you to become a proficient developer. This course is ideal for beginners wanting to become proficient in Rust or from existing developers coming from languages like Python or JavaScript that want to learn Rust fundamentals. Get started by setting up your preferred text editor and installing Rust. We'll ensure that you have all the necessary tools to create a productive coding environment. By leveraging the capabilities of Visual Studio Code and enabling the Rust Analyzer, you'll unlock a feature-rich ecosystem that enhances your development workflow. Experience the game-changing potential of GitHub Copilot, an AI-powered assistant. Sign up for GitHub Copilot and witness its transformative impact on your coding experience. We'll guide you through the installation process and show you how to leverage its intelligent suggestions for accelerated programming. Master concepts and fundamentals like control flow, variable assignment, and immutability. Learn the intricacies of loops, conditional statements, and effective error handling techniques. With Rust's borrowing concept at your disposal, you'll develop secure and high-performance code. Build upon your foundation with advanced topics like structs, string manipulation, and working with vectors and enums. We'll explore real-world library development using Cargo, Rust's robust package manager. Effective documentation and debugging techniques will become second nature as you optimize your code. Organize your code effectively with modules, extending functionality and enhancing reusability. Dive into comprehensive testing methodologies to ensure the reliability and correctness of your programs. From writing tests for your code to handling private components, you'll gain expertise in developing robust software projects. Our immersive learning experience includes hands-on examples, interactive exercises, and practical projects. Rust's performance, safety, and expressiveness will be at your fingertips as you embrace its immense potential. Join us on this rewarding journey to unlock the power of Rust programming and propel your career forward. Enroll now and gain the skills, knowledge, and expertise to thrive in the world of Rust. Whether you're a beginner, coding novice, or an experienced developer seeking new horizons, our course is your gateway to writing elegant, reliable, and high-performance code. Embrace the possibilities of Rust and embark on a rewarding programming journey today with one of the most loved programming languages. Learning Objectives Gain a solid understanding of Rust's core concepts, including variable assignment, control flow, and immutability, to write efficient and reliable code. Master the utilization of powerful development tools such as Visual Studio Code and the Rust Analyzer, enhancing productivity and enabling seamless coding experiences. Explore GitHub Copilot and learn how to leverage its AI-driven suggestions to accelerate programming and boost code quality. Develop proficiency in working with advanced Rust features, such as structs, enums, and string manipulation, to build robust and flexible applications. Discover the intricacies of module organization and extend functionality through effective code structuring, promoting code reusability and maintainability. Acquire comprehensive testing skills, including writing tests for code components and handling private code, ensuring the reliability and correctness of Rust programs. Gain hands-on experience in real-world library development using Cargo, Rust's package manager, and become proficient in documenting code and debugging techniques. These compelling learning objectives will guide you through the course, helping you acquire essential skills and knowledge to become a confident Rust developer. Course Content This course is divided into 4 weeks with 3 lessons that contain about 6 videos each. Each video is about 5 minutes long and contains a hands-on demonstration of the concepts covered in the lesson. The course is designed to be taken in order, but you can jump to any lesson you want to learn more about. Week 1: Setting up your development environment Reference GitHub Repository Setting up your text editor Using GitHub Copilot with Rust Introduction to GitHub Codespaces for Rust Week 2: Rust fundamentals Reference GitHub Repository Introduction to Rust Loops and Control flow Function basics Week 3: Structs, Types, and Enums Reference GitHub Repository Using structured data Exploring strings and vectors Working with Enum and Variants Week 4: Applying Rust Reference GitHub Repository Building a real-world library Extending functionality with modules Testing Rust code About your instructor Alfredo Deza has over a decade of experience as a Software Engineer doing DevOps, automation, and scalable system architecture. Before getting into technology he participated in the 2004 Olympic Games and was the first-ever World Champion in High Jump representing Peru. He currently works in Developer Relations at Microsoft and is an Adjunct Professor at Duke University teaching Machine Learning, Cloud Computing, Data Engineering, Python, and Rust. With Alfredo's guidance, you will gain the knowledge and skills to build with the Rust programming language. Resources Deploy Rust on Azure Functions DevOps command-line tools in Python and Rust Switching to Rust from Python First Steps with Rust Learning Path.

Abstract: This is an introductory course for people who want to learn Linux system administration with an eye toward entering the IT field as a sys admin. We start by covering the very basics of using the Linux operating system and working with the command line interface (CLI). Then we move on to more advanced system skills, as well as the networking skills necessary to become a Linux administrator. Along the way we will configure a server, manage users, develop and deploy a web app, set up a code repository, and more.

Abstract: This course is designed for information security professionals who wish to take the Certified Ethical Hacker (CEH) exam and move on to a career as a professional pentester (or penetration tester). This course will teach you what you need to know to pass the CEH exam, and will also give you insight into the day-to-day workflow of a certified ethical hacker. Upon enrolling in this course, you will receive: 19+ Hours of HD Video Lessons on how to think like a hacker Hacking demonstrations with tools such as Maltego, FOCA, Harvester, Recon-ng, Nmap, masscan, tcpdump, Wireshark, Ettercap, Burp Suite, Scapy, Mimikatz, Hashcat, Konboot, Hydra, and more! A blueprint for conducting your own penetration test Links to additional resources to continue your education.

Abstract: Live Coding Rust Candle from Hugging Face Learning LLMOps This video series covers live coding Rust Candle from Hugging Face for LLMOps Lessons Covered Include: 1.0 Building binaries for Phi using AWS CodeBuild and Rust Candle Learning Objectives Run your own Rust LLMs Additional Popular Resources 52 Weeks of AWS-The Complete Series Microsoft Azure Fundamentals (AZ-900) Certification Rust Bootcamp Python Bootcamp Google Professional Machine Learning Engineer Course 2023 (Rough Draft) Rust Data Engineering Building with the GitHub EcoSystem: Copilot, CodeSpaces, and GitHub Actions Microsoft Azure Fundamentals (AZ-900) Certification Google Professional Cloud Architect Certification Course 2023 (Rough Draft) AWS Solutions Architect Professional (SAP-C02) 2023.

Abstract: Six Small Algorithm Projects with Python: Video Walkthrough Algorithms are the foundations of computer science. In this series of liveProjects, you'll watch as an expert uses specific algorithms to solve important programming problems. Six Small Algorithm Projects with Python is one of the most popular series on Manning's liveProject platform. Working though the series by hand takes weeks, but now there's a simpler way. In this series of videos, experienced data science lecturer Charles Rice guides you through the entire series, bringing you all the lessons in a fraction of the time. As you watch, you'll learn how to use recursion to draw complex shapes, search linked data structures, and layout and draw trees. You'll learn how to use network algorithms to find shortest paths and assign employees to jobs. As you master the projects in this series, you'll gain an understanding of a variety of algorithmic topics, data structures, and general programming techniques. Rod Stephens, series author Rod Stephens started out as a mathematician but discovered the fun of algorithms and has been programming ever since. Rod was a Microsoft Visual Basic Most Valuable Professional (MVP) for 15 years, has spoken to user groups and conferences, and has taught introductory programming courses. He has written more than 35 books including Essential Algorithms: A Practical Approach to Computer Algorithms Using Python and C# and Beginning Software Engineering, both of which include material related to this series of liveProjects. Charles Rice, video presenter Charles Rice is a Senior Data Science Instructor with the Flatiron School. He has worked in data science education for nearly a decade, teaching machine learning and statistical analysis to hundreds of students in the United States and abroad. In industry, he has worked as a Research Engineer for BlockScience, a blockchain R&D consultancy, and consults on data science and engineering for several FinTech organizations. He is a CompTIA Subject Matter Expert for the forthcoming DataX certification exam. Before getting into code and machine learning, he worked as a journalist and corporate communications professional.

Abstract: GitHub Enterprise - Certified Learning the GitHub Enterprise Certification Material This course covers all seven domains of the the GitHub Enterprise Certification Lessons Covered Include: Domain 1: Support GitHub Enterprise for users and key stakeholders Distinguish admin tasks vs needing GitHub Support Generate support bundles and diagnostics Identify underutilized features, integrations, active teams/repos Recommend standards for workflows, branching, code review, automation Explain tooling ecosystem and CI/CD strategy Recommend workflows and tooling to teams Use GitHub APIs to extend admin capabilities Find Marketplace assets for specific needs Contrast GitHub Apps vs actions Domain 2: Manage user identities and GitHub authentication Implications of enabling SAML SSO for orgs/enterprise Steps to enable and enforce SAML SSO Require two-factor authentication Supported identity providers GitHub identity management and authorization Authentication and authorization model Supported SCIM providers How SCIM and team sync works Domain 3: Describe deployment, distribution, licensing Capabilities of GHES, GHEC, GHAE Billing models including licenses, Actions, Packages License usage statistics for orgs, enterprise, machine accounts Consumption of metered products Domain 4: Manage access and permissions Enterprise permissions and policies Organization permissions Team permissions Repository permissions Domain 5: Enable secure development and compliance How GitHub supports enterprise security Scrubbing sensitive data Choosing policies for control required Impacts of policies Organization and enterprise policies Use audit log APIs to explain missing assets Security features of GitHub repositories Create security response plan SSH keys and deploy keys Domain 6: Manage GitHub Actions Distribute actions and workflows in enterprise Manage runners Manage encrypted secrets Domain 7: Manage GitHub Packages Supported Packages Accessing, writing, and sharing Packages Using Packages in workflows Contrasting Packages and releases Learning Objectives Manage user access and permissions across GitHub Enterprise environments through authentication, organizations, teams, and repositories. Establish secure development practices and compliance controls with GitHub features. Distribute and manage GitHub Actions across the enterprise. Additional Popular Resources 52 Weeks of AWS-The Complete Series Microsoft Azure Fundamentals (AZ-900) Certification Rust Bootcamp Python Bootcamp Google Professional Machine Learning Engineer Course 2023 (Rough Draft) Rust Data Engineering Building with the GitHub EcoSystem: Copilot, CodeSpaces, and GitHub Actions Microsoft Azure Fundamentals (AZ-900) Certification Google Professional Cloud Architect Certification Course 2023 (Rough Draft) AWS Solutions Architect Professional (SAP-C02) 2023.

Abstract: Build and upgrade an automated software delivery pipeline that supports containerization, integration testing, semantic versioning, automated deployment, and more. In Shipping Go you will learn how to: Develop better software based on feedback from customers Create a development pipeline that turns feedback into features Reduce bugs with pipeline automation that validates code before it is deployed Establish continuous testing for exceptional code quality Serverless, container-based, and server-based deployments Scale your deployment in a cost-effective way Deliver a culture of continuous improvement Shipping Go is a hands-on guide to shipping Go-based software. Author Joel Holmes shows you the easy way to set up development pipelines, fully illustrated with practical examples in the powerful Go language. You'll put continuous delivery and continuous integration into action, and discover instantly useful guidance on automating your team's build and reacting with agility to customer demands. Your new pipelines will ferry your projects through production and deployment, and also improve your testing, code quality, and production applications. About the Technology An effective software delivery pipeline automates all stages, from initial design, through development, deployment, and ultimately the usage experience that feeds back into new features and releases. Go embraces the best practices of Continuous Delivery, and adds a few language-specific tools and twists of its own. About the Book Shipping Go shows you how to build Go-specific software development pipelines. You'll have a basic CI/CD process up and running by the time you finish Chapter 3, along with an iterative process for designing, releasing, and revising your applications. Then, you'll systematically upgrade your pipeline to support containerization, integration testing, semantic versioning, and automated deployment. A set of handy appendices help you translate these valuable practices to Kotlin, Python, and JavaScript applications. What's Inside Create a development pipeline that turns feedback into features Automatically validate code before it is deployed Serverless, container-based, and server-based deployments Scale your deployment in a cost-effective way About the Reader For Go developers. About the Author Joel Holmes builds cloud native applications, helping to architect, design, and develop them. A Golang tech lead, Aliénor Latour was the technical editor for this book. Quotes Gets you from inception all the way to shipping with Golang. - Nathan B. Crocker, Core Systems/Galaxy Digital Provide continuous value to your end users and team, from design to shipping. - Laud Bentil, mPharma A-Z of building software in Go using a modern tooling ecosystem, full circle from accepting requirements to shipping the software. - Arun Saha, Cisco Teaches you step by step how to industrialize your software production. - Alain Lompo, ISO-Gruppe.

Abstract: If you would like to learn web development and get a job in the tech industry, this is the course for you. With more than sixteen hours of HD video, this course covers HTML, CSS, JavaScript, Bootstrap, and more. An extremely beginner-friendly course, we start with the very basics of HTML and use it to build a simple web page. By the end of the course, you will be able to develop and publish your very own Google Chrome extension. The course is light on lectures, instead stressing hands-on learning with coding exercises and projects. Upon completing this course, you will have a solid portfolio of development projects to show to potential employers. We'll work on three coding projects in this course: Simple text site This project will help you learn HTML structure and the essential elements. Fallout-inspired Pip-Boy We'll apply the CSS and Bootstrap sections of the course to code a Pip-Boy from the game Fallout. This project will help you learn the design elements of modern web development. Google Chrome extension We finish the course by programming a JavaScript-based Google Chrome extension. This project will help you understand the logical parts of web development.

Abstract: Hugging Face for MLOps Learn how to leverage Hugging Face and its powerful machine learning capabilities. Build, train, and deploy your own models using the Hugging Face platform and libraries. In this course you'll get hands-on with Hugging Face and learn how to: Access and use pre-trained models from the Hub Fine-tune models with your own data Build machine learning pipelines with Hugging Face Transformers Add and version your own datasets Containerize and deploy Hugging Face models Automate workflows with GitHub Actions By the end, you'll have practical experience building, training, and deploying Hugging Face models, including production deployment to the Azure cloud. Learning objectives Find and use pre-trained models Fine-tune models for custom tasks Build ML pipelines with Hugging Face libraries Create and version datasets Containerize models for production Automate workflows for MLOps Lesson 1: Getting Started with Hugging Face Lesson Outline Overview of Hugging Face Hub Browsing models and datasets Using Hugging Face repositories Managing spaces and access Lesson 2: Applying Hugging Face Models Lesson Outline Downloading models from the Hub Using models with PyTorch/TensorFlow Leveraging tokenizers and pipelines Performing inference with Hub models Lesson 3: Working with Datasets Lesson Outline Browsing datasets on Hugging Face Uploading and managing datasets Versioning datasets with dataset cards Loading datasets in PyTorch/TensorFlow Lesson 4: Model Serving and Deployment Lesson Outline Containerizing Hugging Face models Creating inference APIs with FastAPI Deploying to cloud services like Azure Automating with GitHub Actions About your instructor Alfredo Deza has over a decade of experience as a Software Engineer doing DevOps, automation, and scalable system architecture. Before getting into technology he participated in the 2004 Olympic Games and was the first-ever World Champion in High Jump representing Peru. He currently works in Developer Relations at Microsoft and is an Adjunct Professor at Duke University. This solid background in technology and teaching, including his experience teaching and authoring content about LOps will give you everything you need to get started applying these powerful concepts. Resources MLOps with Databricks Introduction to MLflow for MLOps Hands-on Python for MLOps.

Abstract: Rust AWS Lambda Build and deploy serverless applications with Rust and AWS Lambda This course will help you build and deploy serverless applications with Rust and AWS Lambda. You will learn how to create, deploy, and manage AWS Lambda functions using Rust, leveraging the power and performance of the language for serverless architecture, and apply it by building a real-world Lambda function as a part of a distributed application. What you will learn Understand the concept of serverless architecture and AWS Lambda. Create and deploy AWS Lambda functions written in Rust. Integrate Lambda functions with other AWS services. Monitor, test, and optimize Rust-based Lambda functions. Implement real-world applications using Rust and AWS Lambda. Lesson 1: Getting Started with Rust AWS Lambda and Serverless Introduction to Serverless and AWS Lambda Walk through Rust Firecracker Project Setting up VSCode AWS Toolkit and CodeWhisperer for Rust Introduction to Cargo Lambda Rust Cost Advantage AWS Lambda Using the AWS Lambda Console Using the Step Functions Console Invoking Step Functions from AWS CLI Lesson 2: Advanced Techniques with Rust and AWS Lambda Building a Rust AWS Lambda Add Function Building a Rust AWS Lambda Divide by Two Function Invoking AWS Step Function from CLI Building Chainable AWS Step Functions with Rust Serverless MLOPs with EFS mounted in AWS Lambda Using Rust AWS Lambda Function URLs Saving money with arm64 Rust AWS Lambdas Lesson 3: Building a Polars Rust AWS Lambda Solution Polars Rust AWS Lambda Build and Deploy Polars Rust AWS Lambda Using AWS Console with deployed Polars Rust AWS Lambda Analyzing Rust AWS Lambda code with CodeWhisperer and AWS Toolkit AWS Lambda Function URLs Build and Deploy Polars Rust AWS Lambda Function URLs.

Abstract: Rust LLMOps: A Rough Draft Course (Updated JIT) Learning During Live Coding This video series is a rough draft course being updated JIT (Just in Time) and covers the Rust language through live coding. We offer an iterative approach to understand and master the language, particularly focusing on its application in MLOps. Lessons Covered Include: Rust Hugging Face Candle Description This week, you will delve into the powerful combination of Rust with Candle, a minimalist ML framework, and explore how they can be used with Hugging Face's popular transformer models. You will apply these concepts by working on a series of hands-on labs that guide you through building, training, and deploying machine learning models using Rust, Candle, and Hugging Face. Learning Objectives By the end of this lesson, you will be able to: - Implement Candle in Rust to create and train machine learning models. - Utilize the various features of Candle, including syntax, GPU efficiency, and browser deployment. - Integrate Hugging Face transformers with Rust for natural language processing tasks. - Apply the principles of Rust and Candle to build real-world machine learning applications. - Evaluate the performance and scalability of Rust-based ML solutions using Candle and Hugging Face. Lesson Structure Original 4.1 Candle: A Minimalist ML Framework for Rust 4.2 Using GitHub Codespaces for GPU Inference with Rust Candle 4.3 VSCode Remote SSH development AWS Accelerated Compute 4.4 Building Hello World Candle 4.5 Exploring StarCoder: A State-of-the-Art LLM for Code 4.6 Using Whisper with Candle to Transcribe 4.7 Exploring Remote Dev Architectures on AWS.

Abstract: Rust For DevOps Learn how to use and apply DevOps principles using Rust This is an early release of the course. In this course, you will learn the basics of DevOps using the Rust programming language. DevOps helps you build, test, and deploy code faster while creating a robust foundation for your projects and teams. First, we will talk about what DevOps is. You will learn things like automation, monitoring, and working together as a team. Then, we will see how to use DevOps ideas in Rust code. You will learn about version control, testing, containers, and deploying Rust programs. Although this course explains the foundations of DevOps and using Rust which is ideal for beginners, experienced Rust developers will find solid advice in how to apply DevOps best practices to existing applications. Learning Objectives The core principles and practices of DevOps How to apply DevOps concepts to build, package, and deploy applications with Rust The basics of containerization and how to leverage containers for DevOps with Rust Course Content This course is divided into 4 weeks with 3 lessons that contain about 6 videos each. Each video is about 5 minutes long and contains a hands-on demonstration of the concepts covered in the lesson. The course is designed to be taken in order, but you can jump to any lesson you want to learn more about. Week 1: Introduction to DevOps Principles Introduction to DevOps Principles DevOps Considerations for Applications Basics of Containerization Week 2: Implementing monitoring and logging strategies Introduction to monitoring and logging strategies Tools and Services for monitoring and logging Logging with Rust About your instructor Alfredo Deza has over a decade of experience as a Software Engineer doing DevOps, automation, and scalable system architecture. Before getting into technology he participated in the 2004 Olympic Games and was the first-ever World Champion in High Jump representing Peru. He currently works in Developer Relations at Microsoft and is an Adjunct Professor at Duke University teaching Machine Learning, Cloud Computing, Data Engineering, Python, and Rust. With Alfredo's guidance, you will gain the knowledge and skills to build robust applications and infrastructure with the Rust programming language and for Rust applications. Resources Rust Bootcamp Deploy Rust on Azure Functions DevOps command-line tools in Python and Rust Switching to Rust from Python First Steps with Rust Learning Path.

Abstract: Effectively reading and understanding existing code is a developer's superpower. In this book, you'll master techniques for code profiling, advanced debugging, and log evaluation to find and fix bugs and performance problems. In Troubleshooting Java: Read, debug, and optimize JVM applications you will learn how to: Determine what code does the first time you see it Expose code logic problems Evaluate heap dumps to find memory leaks Monitor CPU consumption to optimize execution Use thread dumps to find and solve deadlocks Easily follow a service-oriented or microservices system Properly use logging to better understand Java app execution Use Java debuggers efficiently Searching for bugs, detangling messy legacy code, or evaluating your codebase for new features sucks up much of a developer's time. Troubleshooting Java: Read, debug, and optimize JVM applications teaches code investigation techniques that will help you efficiently understand how Java apps work, how to optimize them, and how to fix the bugs that break them. You'll go from the basics of debugging to advanced methods for locating problems in microservices architectures, and save yourself hours--or even days--of time. Each new technique is explained with lively illustrations and engaging real-world examples. About the Technology Fact: Over the course of your career, you'll spend far more time reading code than you will writing it. The code investigation skills in this book will radically improve your efficiency in understanding and improving Java applications. About the Book Troubleshooting Java: Read, debug, and optimize JVM applications presents practical techniques for exploring and repairing unfamiliar code. In it, you'll learn timesaving practices for discovering hidden dependencies, discovering the root causes of crashes, and interpreting unexpected results. Go beyond profiling and debugging and start understanding how Java applications really work. What's Inside Determine what code does the first time you see it Evaluate heap dumps to find memory leaks Monitor CPU consumption to optimize execution Use thread dumps to find and solve deadlocks Uncover glitches in code logic Locate intermittent runtime problems About the Reader For intermediate Java developers. About the Author Lauren€₎iu Spilc♯³ is a skilled Java and Spring developer and an experienced technology instructor. He is the author of Spring Start Here and Spring Security in Action. Quotes We spend more time trying to understand code than writing it. This book shows you how to use that time wisely. - Brent Honadel, Infor Finally a book that illustrates how to troubleshoot and reason about Java apps in production! It just might save the day! - Atul Shriniwas Khot, SquareOne Insights I wish I had this collection of efficient and usable techniques at the beginning of my career. - Andriy Stosyk, EPAM Systems A great book with deep explanations about debugging techniques. - C♯³t♯³lin Matei, Endava Understand how Java applications work under the hood. - Fernando Bernardino, Wise.

Abstract: Keep sensitive user data safe and secure without sacrificing the performance and accuracy of your machine learning models. In Privacy Preserving Machine Learning, you will learn: Privacy considerations in machine learning Differential privacy techniques for machine learning Privacy-preserving synthetic data generation Privacy-enhancing technologies for data mining and database applications Compressive privacy for machine learning Privacy Preserving Machine Learning is a comprehensive guide to avoiding data breaches in your machine learning projects. You'll get to grips with modern privacy-enhancing techniques such as differential privacy, compressive privacy, and synthetic data generation. Based on years of DARPA-funded cybersecurity research, ML engineers of all skill levels will benefit from incorporating these privacy-preserving practices into their model development. By the time you're done reading, you'll be able to create machine learning systems that preserve user privacy without sacrificing data quality and model performance. About the Technology Machine learning applications need massive amounts of data. It's up to you to keep the sensitive information in those data sets private and secure. Privacy preservation happens at every point in the ML process, from data collection and ingestion to model development and deployment. This practical book teaches you the skills you'll need to secure your data pipelines end to end. About the Book Privacy Preserving Machine Learning explores privacy preservation techniques through real-world use cases in facial recognition, cloud data storage, and more. You'll learn about practical implementations you can deploy now, future privacy challenges, and how to adapt existing technologies to your needs. Your new skills build towards a complete security data platform project you'll develop in the final chapter. What's Inside Differential and compressive privacy techniques Privacy for frequency or mean estimation, naive Bayes classifier, and deep learning Privacy-preserving synthetic data generation Enhanced privacy for data mining and database applications About the Reader For machine learning engineers and developers. Examples in Python and Java. About the Authors J. Morris Chang is a professor at the University of South Florida. His research projects have been funded by DARPA and the DoD. Di Zhuang is a security engineer at Snap Inc. G. Dumindu Samaraweera is an assistant research professor at the University of South Florida. The technical editor for this book, Wilko Henecka, is a senior software engineer at Ambiata where he builds privacy-preserving software. Quotes A detailed treatment of differential privacy, synthetic data generation, and privacy-preserving machine-learning techniques with relevant Python examples. Highly recommended! - Abe Taha, Google A wonderful synthesis of theoretical and practical. This book fills a real need. - Stephen Oates, Allianz The definitive source for creating privacy-respecting machine learning systems. This area in data-rich environments is so important to understand! - Mac Chambers, Roy Hobbs Diamond Enterprises Covers all aspects for data privacy, with good practical examples. - Vidhya Vinay, Streamingo Solutions.

Abstract: Guide machine learning projects from design to production with the techniques in this one-of-a-kind project management guide. No ML skills required In Managing Machine Learning Projects you'll learn essential machine learning project management techniques, including: Understanding an ML project's requirements Setting up the infrastructure for the project and resourcing a team Working with clients and other stakeholders Dealing with data resources and bringing them into the project for use Handling the lifecycle of models in the project Managing the application of ML algorithms Evaluating the performance of algorithms and models Making decisions about which models to adopt for delivery Taking models through development and testing Integrating models with production systems to create effective applications Steps and behaviors for managing the ethical implications of ML technology Managing Machine Learning Projects is an end-to-end guide for delivering machine learning applications on time and under budget. It lays out tools, approaches, and processes designed to handle the unique challenges of machine learning project management. You'll follow an in-depth case study through a series of sprints and see how to put each technique into practice. The book's strong consideration to data privacy, and community impact ensure your projects are ethical, compliant with global legislation, and avoid being exposed to failure from bias and other issues. About the Technology Ferrying machine learning projects to production often feels like navigating uncharted waters. From accounting for large data resources to tracking and evaluating multiple models, machine learning technology has radically different requirements than traditional software. Never fear! This book lays out the unique practices you'll need to ensure your projects succeed. About the Book Managing Machine Learning Projects is an amazing source of battle-tested techniques for effective delivery of real-life machine learning solutions. The book is laid out across a series of sprints that take you from a project proposal all the way to deployment into production. You'll learn how to plan essential infrastructure, coordinate experimentation, protect sensitive data, and reliably measure model performance. Many ML projects fail to create real value--read this book to make sure your project is a success. What's Inside Set up infrastructure and resource a team Bring data resources into a project Accurately estimate time and effort Evaluate which models to adopt for delivery Integrate models into effective applications About the Reader For anyone interested in better management of machine learning projects. No technical skills required. About the Author Simon Thompson has spent 25 years developing AI systems to create applications for use in telecoms, customer service, manufacturing and capital markets. He led the AI research program at BT Labs in the UK, and is now the Head of Data Science at GFT Technologies. Quotes Provides many examples of practical implementation issues including scoping, sprints, case studies, and request tickets. - Abi Aryan, MLOps Podcast Golden for all managers, even those with a less technical background. Lucid concept explanations. - Amrita Sarkar, Thomson Reuters Years of experience boiled down to workable checklists, handy anecdotes, and guidance on regulatory and legal frameworks. Ignore at your peril. - Dan Gilks, British Telecommunications.

Abstract: This A to Z course introduces newcomers to the world of data science and teaches the fundamental skills for using machine learning and artificial intelligence (AI) to glean meaning and insights from data. It covers Python's data types and shows how to use the must-have Python data science libraries, including Pandas for data analysis and Matplotlib for creating visuals of the results. Once you understand how to format and clean your data and perform exploratory data analysis, we move to the machine learning side. Here, we introduce you to supervised vs unsupervised learning, as well as the core algorithms, including simple and multiple linear regression. We finish up with a deep dive into a recommender system for movies, and a chance to put together all your new skills and knowledge. Each topic is described in plain English, and the course does its best to avoid mathematical notations and jargon. Once you have access to the source code, you can experiment with it and improve upon it, learning and applying these algorithms in the real world. The data science field is lucrative and growing. This course will introduce you to all the foundational skills that a data scientist must have. If you have no background in statistics, don't let that stop you from enrolling in this course!.

Abstract: Learning Generative AI with AWS CodeWhisperer During Live Coding This video series covers live coding in various languages iteratively, thus learning the language. Lessons Covered Include 1.0 Getting started with Bash and Rust using AWS CodeWhisperer, VSCode, and AWS Toolkit for VSCode Learning Objectives Learn the fundamentals of Generative AI Learn to build AI-powered solutions with Bash, Rust, and AWS services Master the key syntax and features of Bash and Rust languages Additional Popular Resources Assimilate OpenAI 52 Weeks of AWS-The Complete Series Microsoft Azure Fundamentals (AZ-900) Certification Rust Bootcamp Python Bootcamp Google Professional Machine Learning Engineer Course 2023 (Rough Draft) Rust Data Engineering Building with the GitHub EcoSystem: Copilot, CodeSpaces, and GitHub Actions Microsoft Azure Fundamentals (AZ-900) Certification Google Professional Cloud Architect Certification Course 2023 (Rough Draft) AWS Solutions Architect Professional (SAP-C02) 2023.

Abstract: Rust for Pythonistas What you'll learn-and how you can apply it A multi-hour jam session where you will learn to code in Rust. * Write efficient and safe Rust code * Leverage Rust libraries and tools in your projects * Combine Rust with Python for improved application performance Additional Popular Resources 52 Weeks of AWS-The Complete Series Microsoft Azure Fundamentals (AZ-900) Certification Rust Bootcamp Python Bootcamp Google Professional Machine Learning Engineer Course 2023 (Rough Draft) Rust Data Engineering Building with the GitHub EcoSystem: Copilot, CodeSpaces, and GitHub Actions Microsoft Azure Fundamentals (AZ-900) Certification Google Professional Cloud Architect Certification Course 2023 (Rough Draft) AWS Solutions Architect Professional (SAP-C02) 2023.

Abstract: Databases are crucial in the typical software development process, and developers use SQL (Structural Query Language) to communicate with databases. Released in 1989, Microsoft SQL Server is one of the most popular database engines in the world, and it's a must-learn for anyone who wants to work with databases. This course will teach everything you need to know about Microsoft SQL (Transact-SQL or T-SQL), from introductory topics like creating databases and tables to more complex ones like creating stored procedures and sorting data from multiple tables. While the course is designed for beginners, it's perfect for intermediate Microsoft SQL users looking to brush up their knowledge.

Abstract: GitHub Foundations: Privacy, Security and Administration (Rough Draft) Updated (JIT) as it is built About This Video Course Building Secure and Efficient GitHub Workflows This video series covers live coding the GitHub Administration and Security domain iteratively, thus learning the best practices and nuances of managing and securing GitHub projects. Lessons Covered Include: 1.0 Course Introduction: Building Secure and Efficient GitHub Workflows 1.1 Introduction to Authentication and Security: Ensuring Your GitHub Account's Integrity 1.2 Securing Account with 2FA 1.3 Understanding Access Permissions 1.4 Enterprise Managed Users (EMUs) Explained 1.5 Introduction to GitHub Administration: Configuring and Managing Repositories and Organizations 1.6 Enabling and Disabling Features 1.7 Repository Permission Levels Explained 1.8 Setting Repository Visibility Options 1.9 Repository Privacy Settings and Options 2.0 Features and Options in the Security Tab 2.1 Understanding Repository Insights 2.2 Managing Collaborators in GitHub 2.3 Managing Organization Settings 2.4 Members, Teams, and Roles in a GitHub Organization 2.5 Next Steps: Continuing Your GitHub Mastery Journey Learning Objectives Learn GitHub's authentication and security measures Learning to build solutions with robust repository management Learning the key syntax and features of GitHub Administration and Security Additional Popular Resources Assimilate OpenAI 52 Weeks of AWS-The Complete Series Microsoft Azure Fundamentals (AZ-900) Certification AWS Solutions Architect Professional (SAP-C02) 2023 Assimilate Python From Zero.

Abstract: Live Coding in Rust: Unleash the Power of Systems Programming Delve deep into the Rust ecosystem with this groundbreaking live coding series, focused on building robust and performant software, including cutting-edge topics like LLMOps and machine learning with Hugging Face's Candle library. What You'll Get Live coding sessions with expert commentary Weekly updates and continually expanding! High-impact projects and examples Exclusive discussions on Rust best practices Topics covering LLMOps, machine learning, and more A focus on performance, safety, and systems programming Course Outline (Future and Current Content) Rust Fundamentals Introduction to Rust Understanding Ownership & Borrowing Error Handling in Rust LLMOps in Rust Live Coding Rust: LLMOps in Rust--Exploring Hugging Face Candle Building Custom LLMOps Libraries Rust and LLVM: A Match Made in Heaven Machine Learning in Rust Implementing ML Algorithms in Rust Using Hugging Face Candle for NLP Deploying Rust ML Models in Production Systems Programming Writing File Systems in Rust Creating Web Servers with Actix Asynchronous Programming with async/await Rust in DevOps Automating CI/CD Pipelines with Rust Rust for Cloud Operations Rust in Containerized Environments Topics Covered LLMOps : The intersection of LLVM and DevOps Machine Learning : Building and deploying models in Rust Systems Programming : Low-level operations made easier and safer DevOps : Leverage Rust for automating operations tasks Additional Popular Resources Assimilate OpenAI 52 Weeks of AWS-The Complete Series Microsoft Azure Fundamentals (AZ-900) Certification Rust Bootcamp Python Bootcamp Google Professional Machine Learning Engineer Course 2023 (Rough Draft) Rust Data Engineering Building with the GitHub EcoSystem: Copilot, CodeSpaces, and GitHub Actions Microsoft Azure Fundamentals (AZ-900) Certification Google Professional Cloud Architect Certification Course 2023 (Rough Draft) AWS Solutions Architect Professional (SAP-C02) 2023.

Abstract: Rust Data Engineering: Course Description Are you a data engineer, software developer, or a tech enthusiast with a basic understanding of Rust, seeking to enhance your skills and dive deep into the realm of data engineering with Rust? Or are you a professional from another programming language background, aiming to explore the efficiency, safety, and concurrency features of Rust for data engineering tasks? If so, this course is designed for you. While a fundamental knowledge of Rust is expected, you should ideally be comfortable with the basics of data structures and algorithms, and have a working understanding of databases and data processing. Familiarity with SQL, the command line, and version control with git is advantageous. This four-week course focuses on leveraging Rust to create efficient, safe, and concurrent data processing systems. The journey begins with a deep dive into Rust's data structures and collections, followed by exploring Rust's safety and security features in the context of data engineering. In the subsequent week, you'll explore libraries and tools specific to data engineering like Diesel, async, Polars, and Apache Arrow, and learn to interface with data processing systems, REST, gRPC protocols, and AWS SDK for cloud-based data operations. The final week focuses on designing and implementing full-fledged data processing systems using Rust. By the end of this course, you will be well-equipped to use Rust for handling large-scale data engineering tasks, solving real-world problems with efficiency and speed. The hands-on labs and projects throughout this course will ensure you gain practical experience, putting your knowledge into action. This course is your gateway to mastering data engineering with Rust, preparing you for the next level in your data engineering journey. Learning Rust During Live Coding This video series covers live coding the Rust language iteratively, thus learning the language. Lessons Covered Include: Section 1: Rust Data Structures: Collections Lesson 1: Getting Started With The Modern Rust Development Ecosystem Meet the instructor & Course Overview: 1.0-meet-instructor-course-overview.mp4 Introduction to the AI Coding Paradigm Shift: 1.1-ai-pair-programming-paradigm-shift.mp4 Introduction to cloud-based development environments: 1.2-GitHub-Codespaces-Ecosystem-with-copilot-chat.mp4 Introduction to GitHub Copilot Ecosystem for Rust: 1.3-copilot-enabled-rust.mp4 Prompt Engineering with GCP BigQuery SQL: 1.4-big-query-prompt-engineering.mp4 Introduction to AWS CodeWhisperer for Rust: 1.5-aws-codewhisperer-for-rust.mp4 Using Google Bard to Enhance Productivity: 1.6-using-bard-to-enhance-productivity.mp4 Continuous Integration with Rust and GitHub Actions: 1.7-continuous-integration-rust-github-actions.mp4 Lesson 2: Rust Sequences and Maps Introducing Rust Sequences and Maps: 1.8-rust-sequences-maps.mp4 Print Rust data structures demo: 1.9-Print-Rust-data-structures-demo.mp4 Vector Fruit Salad demo: 1.10-Vector-Fruit-Salad-demo.mp4 VecDeque Fruit Salad demo: 1.11-VecDeque-Fruit-Salad-demo.mp4 Linkedin List Fruit Salad demo: 1.12-Linkedin-List-Fruit-Salad-demo.mp4 Fruit Salad CLI demo: 1.13-Fruit-Salad-CLI-demo.mp4 HashMap frequency counter demo: 1.14-HashMap-frequency-counter-demo.mp4 HashMap language comparison: 1.15-HashMap-language-comparison.mp4 Lesson 3: Rust Sets, Graphs and Miscellaneous Data Structures Analyzing UFC Fighter Network Using Graph Centrality in Rust: 1.16-ufc-graph-centrality.mp4 Storing Unique Fruits Using HashSet in Rust: 1.17-unique-fruits-with-hashset.mp4 Maintaining Sorted and Unique Fruits Using BTreeSet in Rust: 1.18-sorted-unique-fruits-with-btreeset.mp4 Creating a Fig Priority Fruit Salad Using Binary Heap in Rust: 1.19-fig-priority-fruit-salad-with-binary-heap.mp4 PageRank algorithm for sports data: 1.20-pagerank-sports.mp4 Showing shortest path with dijkstra: 1.21-shortest-path.mp4 Detecting Strongly Connected Components: A Deep Dive into Kosaraju's Algorithm: 1.22-strongly_connected_components_with_kosaraju.mp4 Simple Charting of Data Structures in Rust: 1.23-ascii-graphing.mp4 Section 2: Safety, Security and Concurrency with Rust Lesson 1: Rust Safety and Security Features Multi-Factor Authentication: 2.1_Multi-Factor_Authentication.mp4 Network Segmentation: 2.2_Network_Segmentation.mp4 Least Privilege Access: 2.3_Least_Privilege_Access.mp4 Encryption: 2.4_Encryption.mp4 Mutable fruit salad: 2.5-mutable-fruit-salad.mp4 Customize fruit salad with a CLI: 2.6-customize-csv-fruit-salad.mp4 Data Race example: 2.7-data-race.mp4 Lesson 2: Security Programming with Rust High Availability: 2.10-high-availability.mp4 Understanding the Homophonic Cipher: A Cryptographic Technique: 2.11-homphonic-cipher.mp4 Decoding the Secrets of the Caesar Cipher: 2.12-caesar-cipher.mp4 Building a Caesar Cipher Command Line Interface: 2.13-caesar-cipher-cli.mp4 Creating a Decoder Ring: A Practical Guide: 2.14-decoder-ring.mp4 Detecting Duplicates with SHA-3: A Data Integrity Tool: 2.15-sha3-dupe-detector.mp4 Incident Response: 2.16-incident-response.mp4 Compliance: 2.17-compliance.mp4 Lesson 3: Concurrency with Rust Core Concepts in Concurrency: 2.20-core-concepts-concurrency.mp4 Dining Philosophers: 2.21-dining-philosopher.mp4 Web Crawl Wikipedia with Rayon: 2.22-web-crawl-wikipedia-rayon.mp4 Intelligent Chatbot with Tokio: 2.23-tokio-chatbot.mp4 Multi-threaded deduplication with Rust: 2.24-data-eng-with-rust-dedupe.mp4 Energy Efficiency Python vs Rust: 2.25-energy-efficiency-python-rust.mp4 Concurrency Stress test with a GPU: 2.26-building-cuda-enabled-stress-test-with-rust-pytorch.mp4 Host Efficiency Serverless Optimization problem: 2.27-host-efficiency-optimization-problem.mp4 Section 3: Rust Data Engineering Libraries and Tools Lesson 1: Using Rust to Manage Data, Files and Network Storage Process CSV files in Rust: 2.31-process-csv-rust.mp4 Using Cargo Lambda with Rust: 2.33-cargo-lambda-rust.mp4 List files on AWS EFS with Rust: 2.34-rust-efs-lister.mp4 Use AWS S3 Storage: 2.35-use-s3-storage.mp4 Use AWS S3 Storage from Rust: 2.36-use-rust-for-s3-storage.mp4 Write encrypted data to tables or Parquet files: 2.37-Write-encrypted-data-to-tables-or-Parquet-files.mp4 Lesson 2: DataFrames with Rust, Python and Notebooks What is Colab?: 2.40-what-is-colab.mp4 Using Bard to enhance notebook development: 2.41-using-bard-to-enhance-productivity.mp4 Exploring Life Expectency in a Notebook: 2.42-life-expectancy-eda.mp4 Load a DataFrame with sensitive data: 2.43-Load-a-DataFrame-with-sensitive-information.mp4 Using MLFlow with Databricks Notebooks: 2.44-mlops-mlflow-tracking.mp4 End to End ML with MLFlow and Databricks: 2.45-end-to-end-ml-with-mlflow-and-databricks.mp4 Comparing DataFrame Libraries between Rust and Python: 2.46-comparing-dataframe-libs-rust-python.mp4 Lesson 3: Data Engineering Libraries and Tools with Rust Parquet file writing and reading with Rust: 2.50-parquet-read-write-rust.mp4 Arrow & Parquet in Rust: 2.51-arrow-parquet-rust.mp4 Serverless functions with Rust and AWS Lambda: 2.52-serverless-rust-aws-lambda.mp4 Polars library overview: 2.53-polars-library-overview.mp4 Building RESTful APIs with Rocket: 2.54-building-restful-apis-rocket.mp4 Utilizing Async Rust in Web Development: 2.55-utilizing-async-rust-web-development.mp4 Applying Data Cleaning Techniques with Rust: 2.56-applying-data-cleaning-rust.mp4 Deploying Rust Applications in a Kubernetes Environment: 2.57-deploying-rust-apps-kubernetes.mp4 Section 4: Designing Data Processing Systems in Rust Lesson 1: Getting Started with Rust Data Pipelines (Including ETL) Jack and the Beanstalk Data Pipelines: 4.1-jack-beanstalk-building-data-pipelines.mp4 Open Source Data Engineering - Pros and Cons: 4.2-open-source-de-pro-con.mp4 Core Components of Data Engineering Pipelines: 4.3-core-components-data-engineering-pipelines.mp4 Rust AWS Step Functions Pipeline: 4.4-rust-aws-step-functions.mp4 Rust AWS Lambda Async S3 Size Calculator: 4.5-rust-async-s3-size-calculator-lambda.mp4 What is Distroless: 4.6-what-is-distroless.mp4 Demo Deploying Rust Microservices on GCP: 4.7-demo-build-deploy-rust-microservice-cloud-run.mp4 Lesson 2: Using Rust and Python for LLMs, ONNX, Hugging Face, and PyTorch Pipelines Introduction to Hugging Face Hub: 4.10-intro-hugging-face-hub.mp4 Rust PyTorch Pre-trained Model Ecosystem: 4.11-rust-pytorch-pretrained-models-ecosystem.mp4 Rust GPU Hugging Face Translator: 4.12-rust-gpu-hugging-face-translator.mp4 Rust PyTorch High-Performance Options: 4.13-high-performance-pytorch-rust-demo.mp4 Rust CUDA PyTorch Stress Test: 4.14-building-cuda-enabled-stress-test-with-rust-pytorch.mp4 EFS ONNX Rust Inference with AWS Lambda: 4.15-efs-onnx-lambda-rust-inference-mlops.mp4 Theory behind model fine-tuning: 4.16-intro-fine-tuning-theory.mp4 Doing Fine Tuning: 4.17-doing-fine-tuning.mp4 Lesson 3: Building SQL Solutions with Rust, Generative AI and Cloud Selecting the correct database on GCP: 4.20-gcp-optimize-d...

Abstract: Using Rust with Python A Practical Guide to Rust for Python Developers Topics: Lesson 1: Introduction to Rust and Python Integration & PyO3 Basics Video 1.1 : Introduction to Rust and Python Video 1.2 : PyO3 Installation Video 1.3 : Basic Rust Library Video 1.4 : Rust to Python Video 1.5 : Rust Ownership Model Video 1.6 : Diagram PyO3 Project Video 1.7 : Python Calc CLI Video 1.8 : PyO3 Features Video 1.9 : PyO3 Exceptions Lesson 2: Advanced Rust and Python Mixing Techniques Video 1.10 : Call Python from Rust Video 1.11 : Run Python Embedded in Rust Video 1.12 : Embedded Rust CLI Diagram Video 1.13 : Embedded Rust CLI Video 1.14 : Embedded Rust CLI Test Video 1.15 : Rust-built Python Tools Video 1.16 : Using Rust Ruff Linter Lesson 3: Python and Rust Command-Line Tools & Recap Video 1.17 : Using Polars with Python and Rust Video 1.18 : Polars CLI in Rust Video 1.19 : Polars CLI Test in Rust Video 1.20 : Polars-CLI Integration Test Video 1.21 : Polars Criterion Benchmarking Learning Objectives Understand the need for Rust and Python integration. Explore the PyO3 library and its usage. Understand the Rust ownership model and its usage in PyO3. Who Should Take This Course Python developers who want to learn Rust and its integration with Python. Rust developers who want to learn how to integrate Rust with Python. Developers who want to learn how to build command-line tools using Rust and Python.

Abstract: This international bestseller has been revised with new exercises, annotations, and full coverage of Scala 3. In Functional Programming in Scala, Second Edition you will learn how to: Recognize and write purely functional code Work with errors without using exceptions Work with state and concurrency Interact with functional structures that define common behaviors Write code that performs I/O without sacrificing functional programming Functional Programming in Scala has helped over 30,000 developers discover the power of functional programming. You'll soon see why reviewers have called it "mindblowing"! The book smooths the complexity curve of functional programming, making it simple to understand the basics and intuitive to progress to more advanced topics. Concrete examples and exercises show you FP in the real world and reveal how it can improve your everyday coding practices. This second edition comes packed with the latest standards of FP, as well as full code updates to Scala 3, and its new language features. About the Technology Functional code is easy to test, reuse, and parallelize, and it's practically immune to whole categories of state-related bugs. With its strong functional features, familiar syntax, and seamless interoperability with Java, there's no better place to start learning functional programming than the flexible Scala language. About the Book In Functional Programming in Scala, Second Edition you'll learn functional programming from first principles. Hands-on exercises and examples make it easy to start thinking and coding functionally. This revised edition contains extensive exercise annotations to help you explore FP in depth, along with steps to build your own functional libraries in Scala. Once the functional lightbulb goes on, you'll never look at coding the same way again. What's Inside Recognize and write purely functional code Work with errors without using exceptions Work with state and concurrency Interact with functional structures that define common behaviors About the Reader For Java or Scala programmers. No knowledge of functional programming required. About the Authors Michael Pilquist is the lead maintainer of FS2, a functional streaming library, and contributes to the Typelevel ecosystem. Paul Chiusano and R©ðnar Bjarnason are recognized experts in functional programming and authors of the first edition of Functional Programming with Scala. Quotes Functional programming in Scala, both the technique and the book, have entrenched themselves firmly in the landscape of the language and ecosystem....This new edition is an effective companion for the community inventing tomorrow. - From the Foreword by Daniel Spiewak, Creator of Cats Effect Deepen your understanding of practical functional programming in Scala with this, the ultimate guide. - Bill Venners, Artima The first edition of FPiS was one of the turning points in my journey through the FP rabbit hole. It was eye-opening to be able to prove that one typeclass interface is equivalent to another. The book's second edition preserves the unique vision of FPiS: to guide readers via practical coding idioms towards a mathematically rigorous approach in FP. - Sergei Winitzki, Workday.

Abstract: Achieving Scalability with Vector, Graph, and Key/Value Databases Description This week we explore vector and graph databases, powerful tools for managing and extracting insights from large, complex datasets. As data volumes continue to grow, scalability is crucial. We'll learn how vector and graph databases can efficiently store data while maintaining relationships, enabling more advanced analytics. Through real-world examples, you'll see how these databases unlock scalability for machine learning, fraud detection, social networks, and more. Learning Objectives Learn Vector, Graph, SQLand Key/Value Databases Learning to build solutions with Rust, Vector, Graph, and Key/Value Databases Learning advanced data engineering Additional Popular Resources 52 Weeks of AWS-The Complete Series Microsoft Azure Fundamentals (AZ-900) Certification Rust Bootcamp Python Bootcamp Google Professional Machine Learning Engineer Course 2023 (Rough Draft) Rust Data Engineering Building with the GitHub EcoSystem: Copilot, CodeSpaces, and GitHub Actions Microsoft Azure Fundamentals (AZ-900) Certification Google Professional Cloud Architect Certification Course 2023 (Rough Draft) AWS Solutions Architect Professional (SAP-C02) 2023.

Abstract: The Cisco Certified Network Associate or CCNA exam validates your knowledge of fundamental networking concepts, and can help build your IT resume. Part 3: Layer 2 Concepts is the third part of the eight-part CCNA course. The course starts with the basics and guides you through the six domains of the CCNA exam: Network Fundamentals Network Access IP Connectivity IP Services Security Fundamentals Automation and Programmability Each lesson builds on the previous parts, guiding you seamlessly through all the topics you need to know to pass the CCNA exam. You'll also get these additional resources to ensure your success: Flashcard decks to help you remember what you have studied in each video Lesson slides in .PDF format to review after watching each video lesson Practical network simulation exercises using Cisco Packet Tracer to give you hands-on practice to develop your networking skills This course has already helped many students all over the world to pass the CCNA exam, and you can be the next one. The course teaches you not only what you need to know to pass the exam, but also fundamental networking knowledge that applies to all areas of IT.

Abstract: The Cisco Certified Network Associate or CCNA exam validates your knowledge of fundamental networking concepts, and can help build your IT resume. Part 4: Dynamic Routing and First-Hop Redundancy Protocols is the fourth part of the eight-part CCNA course. The course starts with the basics and guides you through the six domains of the CCNA exam: Network Fundamentals Network Access IP Connectivity IP Services Security Fundamentals Automation and Programmability Each lesson builds on the previous parts, guiding you seamlessly through all the topics you need to know to pass the CCNA exam. You'll also get these additional resources to ensure your success: Flashcard decks to help you remember what you have studied in each video Lesson slides in .PDF format to review after watching each video lesson Practical network simulation exercises using Cisco Packet Tracer to give you hands-on practice to develop your networking skills This course has already helped many students all over the world to pass the CCNA exam, and you can be the next one. The course teaches you not only what you need to know to pass the exam, but also fundamental networking knowledge that applies to all areas of IT.

Abstract: Are you interested in learning the skills and tools required to create modern, interactive, and responsive websites? The Front-End Web Developer Bootcamp is the course for you! In this comprehensive bootcamp, you'll learn HTML, CSS, JavaScript, and React--the building blocks of the web--and gain hands-on experience making dynamic and engaging web pages from scratch. This course is designed for beginners who want to pursue a career in web development or simply want to learn how to create beautiful and functional websites. You'll learn what the different tools can do, and then work on a series of projects so you can practice your new knowledge and skills. By the end of the course, you'll have a portfolio of projects to showcase your skills to potential employers or clients. In this course, you will: Gain in-demand skills Front-end web development is a highly sought-after skill in today's job market. By mastering HTML, CSS, JavaScript, and React, you'll be well-positioned to land a job in a rapidly growing field. Learn from expert instructors Our experienced instructors have years of experience in the field and are passionate about sharing their knowledge with you. They created this course to help you progress at your own pace and achieve your goals. Practice with hands-on learning The best way to learn front-end web development is through hands-on experience. This course emphasizes practical projects that simulate real-world scenarios. You'll come away with a solid understanding of the tools and techniques used by professional web developers. Build a portfolio As you complete projects throughout the course, you'll build a portfolio of work that showcases your skills to potential employers or clients. This portfolio will demonstrate your ability to create responsive and engaging websites, which is essential in today's job market.

Abstract: In Video Editions the narrator reads the book while the content, figures, code listings, diagrams, and text appear on the screen. Like an audiobook that you can also watch as a video. Master essential best practices for deploying and managing applications on Amazon Web Services. This revised bestseller is packed with techniques for building highly available and scalable architectures and automating deployment with Infrastructure as Code. Leverage globally distributed data centers to launch virtual machines with EC2 Store and archive large volumes of data with EBS, S3, and EFS Persist and query data with highly available and scalable database systems with RDS and DynamoDB Enhance performance with caching data in-memory with ElastiCache and MemoryDB Use Infrastructure as Code to automate your cloud infrastructure Secure workloads running in the cloud with VPC and IAM Build fault-tolerant web applications with ALB and SQS Automate common sysadmin tasks with Lambda, CLI, and SDK Build cloud-native applications based on containers with AppRunner, ECS, Fargate Thousands of developers have chosen Amazon Web Services in Action: An in-depth guide to AWS to help them succeed with the AWS cloud. Readers love this all-practical handbook for its complete introduction to computing, storage, and networking, along with best practices for all core AWS services. This revised third edition features new chapters on containerization, along with a variety of AWS innovations. You'll also learn how automating your infrastructure with IAC is a game changer for your cloud deployment, delivering a massive boost to efficiency and quality. About the Technology Amazon Web Services, the leading cloud computing platform, offers customers APIs for on-demand access to computing services. Rich in examples and best practices of how to use AWS, this Manning bestseller is now released in its third, revised, and improved edition. About the Book In Amazon Web Services in Action, Third Edition: An in-depth guide to AWS , the Wittig brothers give you a comprehensive, practical introduction to deploying and managing applications on the AWS cloud platform. With a sharp focus on the most important AWS tasks and services, they will save you hours of unproductive time. You'll learn hands-on as you complete real-world projects like hosting a WordPress site, setting up a private cloud, and deploying an app on containers. What's Inside Leverage globally distributed data centers to launch virtual machines Enhance performance with caching data in-memory Secure workloads running in the cloud with VPC and IAM Build fault-tolerant web applications with ALB and SQS About the Reader Written for mid-level developers, DevOps or platform engineers, architects, and system administrators. About the Author Andreas Wittig and Michael Wittig are software engineers and consultants focused on AWS. Together, they migrated the first bank in Germany to AWS in 2013. Quotes Up-to-date coverage. Code examples and configurations are all excellent. Even containerization is very well explained. This is the bible for Amazon Web Services. - Mohammad Shahnawaz Akhter, Bank of America It has never been so easy to learn AWS. - Jorge Ezequiel Bo, TravelX Essential for those who decide to embark on the Amazon cloud journey. - Matteo Rossi, UnipolSai Assicurazioni A complete introduction to the most important AWS Services with very useful practical examples. - Matteo Battista, GamePix.

Abstract: Master Python techniques and libraries to reduce run times, efficiently handle huge datasets, and optimize execution for complex machine learning applications. Fast Python is a toolbox of techniques for high performance Python including: Writing efficient pure-Python code Optimizing the NumPy and pandas libraries Rewriting critical code in Cython Designing persistent data structures Tailoring code for different architectures Implementing Python GPU computing Fast Python is your guide to optimizing every part of your Python-based data analysis process, from the pure Python code you write to managing the resources of modern hardware and GPUs. You'll learn to rewrite inefficient data structures, improve underperforming code with multithreading, and simplify your datasets without sacrificing accuracy. Written for experienced practitioners, this book dives right into practical solutions for improving computation and storage efficiency. You'll experiment with fun and interesting examples such as rewriting games in Cython and implementing a MapReduce framework from scratch. Finally, you'll go deep into Python GPU computing and learn how modern hardware has rehabilitated some former antipatterns and made counterintuitive ideas the most efficient way of working. About the Technology Face it. Slow code will kill a big data project. Fast pure-Python code, optimized libraries, and fully utilized multiprocessor hardware are the price of entry for machine learning and large-scale data analysis. What you need are reliable solutions that respond faster to computing requirements while using less resources, and saving money. About the Book Fast Python is a toolbox of techniques for speeding up Python, with an emphasis on big data applications. Following the clear examples and precisely articulated details, you'll learn how to use common libraries like NumPy and pandas in more performant ways and transform data for efficient storage and I/O. More importantly, Fast Python takes a holistic approach to performance, so you'll see how to optimize the whole system, from code to architecture_._ What's Inside Rewriting critical code in Cython Designing persistent data structures Tailoring code for different architectures Implementing Python GPU computing About the Reader For intermediate Python programmers familiar with the basics of concurrency. About the Author Tiago Antao is one of the co-authors of Biopython, a major bioinformatics package written in Python. Quotes A great resource for learning how to create performant Python code. - Or Golan, Qedma Quantum Computing If you think Python is too slow, this book is for you! Parallelization. Vectorization. Using Cython and Numba to compile to C. Putting code onto a GPU to massively parallelize it. Buy a copy for every data scientist in your org. - James Liu, Mediaocean The time you invest reading this book will be repaid multifold in your project's design and the performance you'll gain. - Ruud Gijsen, Simbeyond.

Abstract: The Cisco Certified Network Associate or CCNA exam validates your knowledge of fundamental networking concepts, and can help build your IT resume. Part 8: Wireless LANs and Network Automation is the eighth and final part of the eight-part CCNA course. The course starts with the basics and guides you through the six domains of the CCNA exam: Network Fundamentals Network Access IP Connectivity IP Services Security Fundamentals Automation and Programmability Each lesson builds on the previous parts, guiding you seamlessly through all the topics you need to know to pass the CCNA exam. You'll also get these additional resources to ensure your success: Flashcard decks to help you remember what you have studied in each video Lesson slides in .PDF format to review after watching each video lesson Practical network simulation exercises using Cisco Packet Tracer to give you hands-on practice to develop your networking skills This course has already helped many students all over the world to pass the CCNA exam, and you can be the next one. The course teaches you not only what you need to know to pass the exam, but also fundamental networking knowledge that applies to all areas of IT.

Abstract: The Cisco Certified Network Associate or CCNA exam validates your knowledge of fundamental networking concepts, and can help build your IT resume. Part 2: Routing Fundamentals and Subnetting is the second part of the eight-part CCNA course. The course starts with the basics and guides you through the six domains of the CCNA exam: Network Fundamentals Network Access IP Connectivity IP Services Security Fundamentals Automation and Programmability Each lesson builds on the previous parts, guiding you seamlessly through all the topics you need to know to pass the CCNA exam. You'll also get these additional resources to ensure your success: Flashcard decks to help you remember what you have studied in each video Lesson slides in .PDF format to review after watching each video lesson Practical network simulation exercises using Cisco Packet Tracer to give you hands-on practice to develop your networking skills This course has already helped many students all over the world to pass the CCNA exam, and you can be the next one. The course teaches you not only what you need to know to pass the exam, but also fundamental networking knowledge that applies to all areas of IT.

Abstract: The Cisco Certified Network Associate or CCNA exam validates your knowledge of fundamental networking concepts, and can help build your IT resume. Part 6: Network Services is the sixth part of the eight-part CCNA course. The course starts with the basics and guides you through the six domains of the CCNA exam: Network Fundamentals Network Access IP Connectivity IP Services Security Fundamentals Automation and Programmability Each lesson builds on the previous parts, guiding you seamlessly through all the topics you need to know to pass the CCNA exam. You'll also get these additional resources to ensure your success: Flashcard decks to help you remember what you have studied in each video Lesson slides in .PDF format to review after watching each video lesson Practical network simulation exercises using Cisco Packet Tracer to give you hands-on practice to develop your networking skills This course has already helped many students all over the world to pass the CCNA exam, and you can be the next one. The course teaches you not only what you need to know to pass the exam, but also fundamental networking knowledge that applies to all areas of IT.

Abstract: An effective Chief Technology Officer shapes almost every aspect of a modern business. This book shares the experience and advice of veteran CTOs and industry experts for handling IT crises, leading tech teams, and creating an inspiring vision for your company. In Think Like a CTO you will learn: Effective interaction and relationship-building with other C-level executives Creating long term visions and executing on short term goals Interviewing, hiring, and terminating team members Negotiating salaries and managing promotions Architecting future-proofed systems Handling security breaches and ransomware attacks Putting together budgets and working with your CFO Identifying and managing outsourced vendor opportunities Managing and communicating bad news by leading with data, not passion Being the kind of leader that employees want to follow and emulate Becoming a CTO is an incredible accomplishment. It's also one of the hardest transitions a technologist can make. This high-power and high-pressure role demands skills that are rarely developed as a software engineer. Think Like a CTO shines a light on all the areas an aspiring CTO needs to master to succeed. You'll learn how to build incredible working relationships with the rest of the C-suite, transform a company with private equity, and recruit and manage your development team. With this book as your guide, you'll quickly become a trusted leader figure with an inspiring vision for your company. About the Technology The Chief Technology Officer balances business needs with the constantly evolving world of technology. Think Like a CTO helps you develop the skills and mindset you need to take on this critical role and emerge as a successful leader. Packed with insights from industry experts and veteran CTOs, this book shares practical strategies for navigating the high-stakes world of technology leadership. About the Book Think Like a CTO shares hard-won lessons on how to thrive in the fast-paced role of Chief Technology Officer. Inside, you'll learn to establish successful technology platforms and teams, with practical frameworks for software selection and implementation, bias-free interviews and performance reviews, and earning your place at the table with other senior leaders. You'll appreciate the no-nonsense advice, insights, and war stories from CTO mentor Alan Williamson. What's Inside Building productive relationships with other C-level executives Negotiating salaries and managing promotions Architecting future-proof systems Handling security breaches and ransomware attacks About the Reader For technology leaders working in or aspiring towards a CTO role. About the Author Alan Williamson has advised numerous CTOs who were catapulted into the big leagues by private equity investment, acquisition, and rapid growth. Quotes Comprehensive and insightful views on becoming, and thriving as, a technology executive. Alan provides remarkable solutions to challenges every tech leader faces. - From the Foreword by Ankit Mathur, Co-Founder, Roundtrip Health and Founder, Press Play Technologies Interesting and very useful. I could have used this as I moved into CTO roles early in my career. - Jothy Rosenberg, Dover Microsystems An awesome collection of strategies and real-life stories! Every paragraph describes a situation many of us have experienced or an actionable step to deal with it. - Matt Ferderer, Mighty Gnomes.

Abstract: Databricks Certified Data Engineer Associate Course 1: Databricks Lakehouse Platform Description Learn foundational Databricks capabilities including compute, storage, notebooks, and jobs to build scalable data solutions. Learning Objectives Create clusters and configure runtime environments Perform exploratory analysis with notebooks Schedule and monitor multi-task workflows Course 2: Databricks SQL Description Master Spark SQL for reading, transforming, and loading data at scale. Learn techniques like data validation, custom business logic, and slowly changing dimensions. Learning Objectives Query data in notebooks with Spark SQL Handle complex data types Apply data quality rules Implement slowly changing dimensions Course 3: Databricks ML Description Build ML models with Python and Scala APIs in Databricks. Learn best practices for feature engineering, hyperparameter tuning, and model evaluation. Learning Objectives Engineer features from raw data Tune models with cross validation Evaluate model performance Operationalize models with MLflow Course 4: Databricks Data Engineering Description Architect reliable and performant data infrastructure with Delta Lake, streaming, and autoscaling. Learning Objectives Implement ACID transactions Build streaming ETL solutions Autoscale infrastructure to meet SLAs Migrate data warehouses to lakehouse Course 5: Workloads with Jobs Description Orchestrate workloads using multi-task Jobs with configurable scheduling, dependencies, and error handling. Learning Objectives Schedule notebooks, jobs and pipelines Set dependencies across tasks Handle and retry failures Monitor runs using the Jobs UI Course 6: Data Access with Unity Catalog Description Provide governed data access across storage like ADLS, S3, and GCS using Unity Catalog. Learning Objectives Deploy a Unity Catalog Manage credentials securely Apply object-level security Query data from storage tiers Additional Popular Resources Assimilate OpenAI 52 Weeks of AWS-The Complete Series Microsoft Azure Fundamentals (AZ-900) Certification Rust Bootcamp Python Bootcamp Google Professional Machine Learning Engineer Course 2023 (Rough Draft) Rust Data Engineering Building with the GitHub EcoSystem: Copilot, CodeSpaces, and GitHub Actions Microsoft Azure Fundamentals (AZ-900) Certification Google Professional Cloud Architect Certification Course 2023 (Rough Draft) AWS Solutions Architect Professional (SAP-C02) 2023.

Abstract: The Cisco Certified Network Associate or CCNA exam validates your knowledge of fundamental networking concepts, and can help build your IT resume. Part 7: Security Fundamentals and Network Architectures is the seventh part of the eight-part CCNA course. The course starts with the basics and guides you through the six domains of the CCNA exam: Network Fundamentals Network Access IP Connectivity IP Services Security Fundamentals Automation and Programmability Each lesson builds on the previous parts, guiding you seamlessly through all the topics you need to know to pass the CCNA exam. You'll also get these additional resources to ensure your success: Flashcard decks to help you remember what you have studied in each video Lesson slides in .PDF format to review after watching each video lesson Practical network simulation exercises using Cisco Packet Tracer to give you hands-on practice to develop your networking skills This course has already helped many students all over the world to pass the CCNA exam, and you can be the next one. The course teaches you not only what you need to know to pass the exam, but also fundamental networking knowledge that applies to all areas of IT.

Abstract: The Cisco Certified Network Associate or CCNA exam validates your knowledge of fundamental networking concepts, and can help build your IT resume. Part 5: Layer 4, IPv6 and IP Access Control Lists is the fifth p0art of the eight-part CCNA course. The course starts with the basics and guides you through the six domains of the CCNA exam: Network Fundamentals Network Access IP Connectivity IP Services Security Fundamentals Automation and Programmability Each lesson builds on the previous parts, guiding you seamlessly through all the topics you need to know to pass the CCNA exam. You'll also get these additional resources to ensure your success: Flashcard decks to help you remember what you have studied in each video Lesson slides in .PDF format to review after watching each video lesson Practical network simulation exercises using Cisco Packet Tracer to give you hands-on practice to develop your networking skills This course has already helped many students all over the world to pass the CCNA exam, and you can be the next one. The course teaches you not only what you need to know to pass the exam, but also fundamental networking knowledge that applies to all areas of IT.

Abstract: Learn how AI-assisted coding using ChatGPT and GitHub Copilot can dramatically increase your productivity (and fun) writing regular expressions and other programs. Regular Expression Puzzles and AI Coding Assistants is the story of two competitors. On one side is David Mertz, an expert programmer and the author of the Web's most popular Regex tutorial. On the other are the AI powerhouse coding assistants, GitHub Copilot and OpenAI ChatGPT. Here's how the contest works: David invents 24 Regex problems he calls puzzles and shows you how to tackle each one. When he's done, he has Copilot and ChatGPT work the same puzzles. What they produce intrigues him. Which side is likelier to get it right? Which will write simple and elegant code? Which makes smarter use of lesser known Regex library features? Read the book to find out. David also offers AI best practices, showing how smart prompts return better results. By the end, you'll be a master at solving your own Regex puzzles, whether you use AI or not. About the Technology Groundbreaking large language model research from OpenAI, Google, Amazon, and others have transformed expectations of machine-generated software. But how do these AI assistants, like ChatGPT and GitHub Copilot, measure up against regular expressions--a workhorse technology for developers used to describe, find, and manipulate patterns in text. Regular expressions are compact, complex, and subtle. Will AI assistants handle the challenge? About the Book Regular Expression Puzzles and AI Coding Assistants is the perfect starting point for programmers of any experience level who want to understand the capabilities--and the limitations--of these exciting new tools. Author David Mertz presents 24 challenging regex puzzles, their traditional human-made solutions, and the fascinating answers given by popular AI assistants. Alongside these eye-opening puzzles you'll learn how to write prompts, integrate AI-generated coding suggestions, and interact with the assistant to get the results you want. By the end of the book, you'll have a clear understanding of where AI assistants can reliably write code for you and where you'll still need a human touch. Plus, you'll learn a lot about regular expressions! About the Reader Code examples use simple Python and Regular Expressions. No experience with AI coding tools required. About the Author David Mertz is the founder of KDM Training and an acclaimed contributor to the Python community. He is also the author of The Puzzling Quirks of Regular Expressions, Cleaning Data for Effective Data Science: Doing the Other 80% of the Work, and other books. Quotes AI coding assistants are here, and they're transforming how programming is and will be done. If you know regular expressions, pick up this book and learn all about AI coding assistants. If you don't know regular expressions, well, pick it up anyway and experience how you learn with AI coding assistants. - Dr. Daniel Zingaro University of Toronto, author of Algorithmic Thinking How these tools can be both so very amazing in what they produce, and simultaneously so utterly doltish in their numerous failures, is the main thing this book tries to understand. For reasons I attempt to elucidate throughout, of all the domains of computer programming, games with regular expressions are particularly well suited for getting a grasp on the peculiar behaviors of AI. - From the Preface I am a strong believer in Augmented Intelligence and welcome tools such as ChatGPT & Co-Pilot. To take meaningful steps toward Augmented Intelligence, we will need to understand both Humans' and Machines' strengths and weaknesses. This is where David's book comes in. Through the puzzles, David was able to show it well. Strongly recommended for anyone who is looking to use Artificial Intelligence for their business, to tap into its strength and prepare for potential risks. - Koo Ping Shung, Data Science Rex.

Abstract: "Optimize the performance of your systems with practical experiments used by engineers in the world's most competitive industries. In Experimentation for Engineers: From A/B testing to Bayesian optimization you will learn how to: Design, run, and analyze an A/B test Break the ""feedback loops"" caused by periodic retraining of ML models Increase experimentation rate with multi-armed bandits Tune multiple parameters experimentally with Bayesian optimization Clearly define business metrics used for decision-making Identify and avoid the common pitfalls of experimentation Experimentation for Engineers: From A/B testing to Bayesian optimization is a toolbox of techniques for evaluating new features and fine-tuning parameters. You'll start with a deep dive into methods like A/B testing, and then graduate to advanced techniques used to measure performance in industries such as finance and social media. Learn how to evaluate the changes you make to your system and ensure that your testing doesn't undermine revenue or other business metrics. By the time you're done, you'll be able to seamlessly deploy experiments in production while avoiding common pitfalls. About the Technology Does my software really work? Did my changes make things better or worse? Should I trade features for performance? Experimentation is the only way to answer questions like these. This unique book reveals sophisticated experimentation practices developed and proven in the world's most competitive industries that will help you enhance machine learning systems, software applications, and quantitative trading solutions. About the Book Experimentation for Engineers: From A/B testing to Bayesian optimization delivers a toolbox of processes for optimizing software systems. You'll start by learning the limits of A/B testing, and then graduate to advanced experimentation strategies that take advantage of machine learning and probabilistic methods. The skills you'll master in this practical guide will help you minimize the costs of experimentation and quickly reveal which approaches and features deliver the best business results. What's Inside Design, run, and analyze an A/B test Break the "feedback loops" caused by periodic retraining of ML models Increase experimentation rate with multi-armed bandits Tune multiple parameters experimentally with Bayesian optimization About the Reader For ML and software engineers looking to extract the most value from their systems. Examples in Python and NumPy. About the Author David Sweet has worked as a quantitative trader at GETCO and a machine learning engineer at Instagram. He teaches in the AI and Data Science master's programs at Yeshiva University. Quotes Putting an 'improved' version of a system into production can be really risky. This book focuses you on what is important! - Simone Sguazza, University of Applied Sciences and Arts of Southern Switzerland A must-have for anyone setting up experiments, from A/B tests to contextual bandits and Bayesian optimization. - Maxim Volgin, KLM Shows a non-mathematical programmer exactly what they need to write powerful mathematically-based testing algorithms. - Patrick Goetz, The University of Texas at Austin Gives you the tools you need to get the most out of your experiments. - Marc-Anthony Taylor, Raiffeisen Bank International".

Abstract: Do you know what happens to your personal data when you are browsing, buying, or using apps? Discover how your data is harvested and exploited, and what you can do to access, delete, and monetize it. Data for All empowers everyone--from tech experts to the general public--to control how third parties use personal data. Read this eye-opening book to learn: The types of data you generate with every action, every day Where your data is stored, who controls it, and how much money they make from it How you can manage access and monetization of your own data Restricting data access to only companies and organizations you want to support The history of how we think about data, and why that is changing The new data ecosystem being built right now for your benefit The data you generate every day is the lifeblood of many large companies--and they make billions of dollars using it. In Data for All, bestselling author John K. Thompson outlines how this one-sided data economy is about to undergo a dramatic change. Thompson pulls back the curtain to reveal the true nature of data ownership, and how you can turn your data from a revenue stream for companies into a financial asset for your benefit. About the Technology Do you know what happens to your personal data when you're browsing and buying? New global laws are turning the tide on companies who make billions from your clicks, searches, and likes. This eye-opening book provides an inspiring vision of how you can take back control of the data you generate every day. About the Book Data for All gives you a step-by-step plan to transform your relationship with data and start earning a "data dividend"--hundreds or thousands of dollars paid out simply for your online activities. You'll learn how to oversee who accesses your data, how much different types of data are worth, and how to keep private details private. What's Inside The types of data you generate with every action, every day How you can manage access and monetization of your own data The history of how we think about data, and why that is changing The new data ecosystem being built right now for your benefit About the Reader For anyone who is curious or concerned about how their data is used. No technical knowledge required. About the Author John K. Thompson is an international technology executive with over 37 years of experience in the fields of data, advanced analytics, and artificial intelligence. Quotes An honest, direct, pull-no-punches source on one of the most important personal issues of our time....I changed some of my own behaviors after reading the book, and I suggest you do so as well. You have more to lose than you may think. - From the Foreword by Thomas H. Davenport, author of Competing on Analytics and The AI Advantage A must-read for anyone interested in the future of data. It helped me understand the reasons behind the current data ecosystem and the laws that are shaping its future. A great resource for both professionals and individuals. I highly recommend it. - Ravit Jain, Founder & Host of The Ravit Show, Data Science Evangelist.

Abstract: Ensemble machine learning combines the power of multiple machine learning approaches, working together to deliver models that are highly performant and highly accurate. Inside Ensemble Methods for Machine Learning you will find: Methods for classification, regression, and recommendations Sophisticated off-the-shelf ensemble implementations Random forests, boosting, and gradient boosting Feature engineering and ensemble diversity Interpretability and explainability for ensemble methods Ensemble machine learning trains a diverse group of machine learning models to work together, aggregating their output to deliver richer results than a single model. Now in Ensemble Methods for Machine Learning you'll discover core ensemble methods that have proven records in both data science competitions and real-world applications. Hands-on case studies show you how each algorithm works in production. By the time you're done, you'll know the benefits, limitations, and practical methods of applying ensemble machine learning to real-world data, and be ready to build more explainable ML systems. About the Technology Automatically compare, contrast, and blend the output from multiple models to squeeze the best results from your data. Ensemble machine learning applies a "wisdom of crowds" method that dodges the inaccuracies and limitations of a single model. By basing responses on multiple perspectives, this innovative approach can deliver robust predictions even without massive datasets. About the Book Ensemble Methods for Machine Learning teaches you practical techniques for applying multiple ML approaches simultaneously. Each chapter contains a unique case study that demonstrates a fully functional ensemble method, with examples including medical diagnosis, sentiment analysis, handwriting classification, and more. There's no complex math or theory--you'll learn in a visuals-first manner, with ample code for easy experimentation! What's Inside Bagging, boosting, and gradient boosting Methods for classification, regression, and retrieval Interpretability and explainability for ensemble methods Feature engineering and ensemble diversity About the Reader For Python programmers with machine learning experience. About the Author Gautam Kunapuli has over 15 years of experience in academia and the machine learning industry. Quotes An excellent guide to ensemble learning with concepts, code, and examples. - Peter V. Henstock, Machine Learning and AI Lead, Pfizer Inc.; Advanced AI/ML Lecturer, Harvard Extension School Extremely valuable for more complex scenarios that single models aren't able to accurately capture. - McHughson Chambers, Roy Hobbs Diamond Enterprise Ensemble methods are a valuable tool. I can aggregate the strengths from multiple methods while mitigating their individual weaknesses and increasing model performance. - Noah Flynn, Amazon Step by step and with clear descriptions. Very understandable. - Oliver Korten, ORONTEC.

Abstract: The Cisco Certified Network Associate or CCNA exam validates your knowledge of fundamental networking concepts, and can help build your IT resume. Part 1: Network Fundamentals is the first part of the eight-part CCNA course. The course starts with the basics and guides you through the six domains of the CCNA exam: Network Fundamentals Network Access IP Connectivity IP Services Security Fundamentals Automation and Programmability Each lesson builds on the previous parts, guiding you seamlessly through all the topics you need to know to pass the CCNA exam. You'll also get these additional resources to ensure your success: Flashcard decks to help you remember what you have studied in each video Lesson slides in .PDF format to review after watching each video lesson Practical network simulation exercises using Cisco Packet Tracer to give you hands-on practice to develop your networking skills This course has already helped many students all over the world to pass the CCNA exam, and you can be the next one. The course teaches you not only what you need to know to pass the exam, but also fundamental networking knowledge that applies to all areas of IT.

Abstract: Becoming a Kubernetes administrator is a big accomplishment--and passing the Certified Kubernetes Administrator (CKA) exam can be a big boost to your career! Learn the hands on skills you need to ace the exam with clear teaching and hands-on exercises that match the unique CKA test environment. In Acing the Certified Kubernetes Administrator Exam you'll learn how to: Administer an application running on Kubernetes Troubleshoot errors inside a Kubernetes cluster Authenticate users and machines to the Kubernetes API Create persistent storage in Kubernetes Add additional functionality to an existing Kubernetes cluster Acing the Certified Kubernetes Administrator Exam is your fast-track to becoming a Certified Kubernetes Administrator! Your expert exam tutor is Chad Crowell, whose courses have helped thousands of developers to understand Kubernetes and earn the coveted CKA certification. If you're familiar with Kubernetes, this book will ensure you're ready to pass in just one month of study. If you're brand new, this is the perfect primer to get started on your Kubernetes journey. Go hands-on with all the exam objectives, including deploying containerized applications to Kubernetes, accessing an application from an ingress resource, and backup and restore. Plus, essential exam tips and exercises help you work out your mental muscle memory. About the Technology The Certified Kubernetes Administrator (CKA) exam proves to your next employer that you can set up and manage Kubernetes clusters. In this rigorous test offered by the Linux Foundation, you'll configure and manage production-grade clusters hands-on as a proctor watches. Simply put, if you aren't ready, you won't pass. About the Book Acing the Certified Kubernetes Administrator Exam teaches every skill you need to pass the CKA. You can't "hack" this exam by learning a few test-taking tricks. Instead, you'll master vital techniques like load balancing and networking with carefully designed exercises that you practice using the CKA's command-line interface. With this book, you'll be confident and ready for exam day. What's Inside Administer an application on Kubernetes Troubleshoot errors in a Kubernetes cluster Authenticate users and machines Create persistent storage About the Reader For readers who know the basics of containers and Linux admin. No Kubernetes experience required. About the Author Chad M. Crowell is the author of dozens of courses on Kubernetes and DevOps with Pluralsight and INE. Chad is also a Microsoft Certified Trainer (MCT). Quotes As someone who helped establish the CKA, I'm impressed! Great explanations, great visuals, and excellent hands-on exercises. That's what counts to pass the CKA exam! - Michael Hausenblas, AWS Solution Engineering Lead and CNCF Ambassador An invaluable resource. All exam topics are covered in detail and clearly explained. - Rob Pacheco, Forward Financing I just passed CKA. Do you need a better recommendation? - David Moravec, Y Soft An absolute marvel. It's clear, instructive, and hands-on. Highly recommended! - Giang Ch©Øu, AppHub.

Abstract: Build cross-platform apps with .NET MAUI! This exciting new technology helps you create mobile and desktop apps using a common set of .NET tools. In .NET MAUI in Action you will learn how to: Set up your environment for cross-platform development Write an interactive UI in XAML using out-of-the-box controls Apply the MVVM pattern to build maintainable code Extend your control library with custom controls Structure your app using common navigation paradigms Use common device features like GPS Use DevOps tools to automate deployment and testing .NET MAUI in Action shows you how you can use the cutting-edge MAUI framework to write apps that will run on Windows, Android, macOS, and iOS platforms using your existing .NET development skills. This book reveals essential MAUI development techniques through hands-on example applications in every chapter. You'll learn cross-platform development quickly as you start building your own rich apps, from to-do list apps, to a movie recommender app, and eventually a full-stack solution using enterprise architecture patterns. You'll also learn how to use GitHub Actions to deploy robust, testable, and maintainable apps; and how to deliver a consistent look and feel across platforms. Throughout, you'll use the built-in controls of .NET MAUI and learn how to develop your own custom solutions. About the Technology Write your app once and deploy it on mobile, desktop, web, and cloud with .NET MAUI. This powerful multi-platform App UI framework saves time and money by eliminating tedious platform-specific rewrites. You just define your project in straightforward XAML markup and C#, and MAUI generates the native applications for iOS, Android, Windows, and macOS. About the Book .NET MAUI in Action teaches you how to build cross-platform applications using the .NET MAUI framework. You'll explore compelling examples while you work your way up from "Aloha World" to a full-stack enterprise solution. Along the way, you'll master the MVVM pattern and other essentials of mobile UI development. This practical book is perfect for .NET developers who have never created mobile apps. What's Inside Write interactive UIs in XAML using out-of-the-box controls Extend your control library with custom controls Use common device features like GPS Automate deployment and testing About the Reader For experienced .NET developers. No iOS or Android experience required. About the Author Matt Goldman is a Solution Architect at SSW, a regular speaker at user groups and conferences, and maintains open source libraries for use in .NET MAUI apps. Quotes This book stands apart by boldly exploring critical enterprise application development principles. It empowers readers to be self-sufficient by emphasizing best practices and offering practical tips that equip them to improve as cross-platform developers. - From the Foreword by Kym Phillpotts, Microsoft Does not get any better than Matt Goldman! His real-world scenarios set you up for success. - Sam Basu, Progress A gold mine, full of valuable information and examples! - Aleksander Rokic, ObjectEasy The section on upgrading a Xamarin.Forms app to .NET MAUI is worth the price of the book! - Mario Solomou, Appoint.AI.

Abstract: Learn multicloud deployment on Anthos directly from the Google development team! Anthos delivers a consistent management platform for deploying and operating Linux and Windows applications anywhere--multi-cloud, edge, on-prem, bare metal, or VMware. In Google Anthos in Action you will learn: How Anthos reduces your dependencies and stack-bloat Running applications across multiple clouds and platforms Handling different workloads and data Adding automation to speed up code delivery Modernizing infrastructure with microservices and Service Mesh Policy management for enterprises Security and observability at scale Google Anthos in Action demystifies Anthos with practical examples of Anthos at work and invaluable insights from the Google team that built it. You'll learn how to use this modern, Kubernetes-based cloud platform to balance costs, automate security, and run your software literally anywhere. The book is full of Google-tested patterns that will boost efficiency across the development lifecycle. It's an absolutely essential guide for anyone working with Anthos, or delivering software in a cloud-centric world. About the Technology The operations nightmare: modern applications run on-prem, in the cloud, at the edge, on bare metal, in containers, over VMs, in any combination. And you're expected to handle the rollouts, dataOps, security, performance, scaling, backup, and whatever else comes your way. Google Anthos feels your pain. This Kubernetes-based system simplifies hybrid and multicloud operations, providing a single platform for deploying and managing your applications, wherever they live. About the Book Google Anthos in Action introduces Anthos and shows you how it can simplify operations for hybrid cloud systems. Written by 17 Googlers, it lays out everything you can do with Anthos, from Kubernetes deployments to AI models and edge computing. Each fully illustrated chapter opens up a different Anthos feature, with exercises and examples so you can see Anthos in action. You'll appreciate the valuable mix of perspectives and insight this awesome team of authors delivers. What's Inside Reduce dependencies and stack-bloat Run applications across multiple clouds and platforms Speed up code delivery with automation Policy management for enterprises Security and observability at scale About the Reader For software and cloud engineers with experience using Kubernetes. About the Author Google Anthos in Action is written by a team of 17 Googlers involved with Anthos development, and Google Cloud Certified Fellows assisting customers in the field. Quotes Your guide into the world of multicloud at scale. A great read whether you are just starting out or a seasoned veteran. - Glen Yu, PwC Canada Great book for engineers who want to learn Anthos. - Bhagvan Kommadi, Quantica Computacao Google Anthos can be intimidating. This book is an essential guide to using and understanding it. - Jose San Leandro, ioBuilders Complete, easy to understand, with simple explanations, useful diagrams, and real-world examples. I recommend it. - Rambabu Posa, Sai AAshika Consultancy.

Abstract: Deploy Rust on Azure Functions Learn how to deploy Rust functions to Azure Functions with this comprehensive video course. You will start by creating a simple HTTP-triggered function, and then use GitHub Actions to automate your deployment. Deploying Rust in Azure can be frustrating because there is no first-class support yet for it. You will learn what are some of the caveats and what are some strategies you can use to properly deploy a very basic Rust HTTP API. Course Overview We will start by covering the basics of Azure Functions and Rust, and then dive into more advanced topics such as configuring your function's environment, application settings, and using external crates. By the end of this course, you will have a working knowledge of how to deploy and manage your Rust functions on Azure Functions using automation to quickly re-deploy or update your function. Course Content Introduction to Azure Functions - Learn the basics of Azure Functions and how they work with Rust. Creating Your First Azure Function in Rust - Create a simple HTTP-triggered function in Rust and deploy it to Azure Functions. Configuring Your Function Environment - Learn how to use environment variables to configure your function's behavior. Use GitHub Actions for automation About your instructor Alfredo Deza has over a decade of experience as a Software Engineer doing DevOps, automation, and scalable system architecture. Before getting into technology he participated in the 2004 Olympic Games and was the first-ever World Champion in High Jump representing Peru. He currently works in Developer Relations at Microsoft and is an Adjunct Professor at Duke University. With Alfredo's guidance, you will gain the knowledge and skills needed to deploy and manage your Rust functions on Azure Functions. Resources Deploying containers to Azure Practical MLOps book Automated Azure Resource Cleanup Azure Fundamentals Certification.

Abstract: Google Professional Machine Learning Engineer Course 2023 (Rough Draft) Certification Exam Guide Welcome to the Google Professional Machine Learning Engineer Course! This course is designed to help you prepare for the Google Professional Machine Learning Engineer certification exam. Learning Objectives Develop a deep understanding of Google Cloud technologies and various ML models and techniques to design, build, and productionize machine learning solutions that address specific business challenges while adhering to responsible AI practices. Collaborate effectively with cross-functional teams, including application developers, data engineers, and data governance professionals, to ensure the long-term success of ML models throughout their development, deployment, and maintenance. Master the skills required to design, implement, and manage ML architectures, data pipelines, and metric interpretations, as well as optimize model performance through training, retraining, deploying, scheduling, monitoring, and refining models in scalable and efficient ways. Learn how to use the Google Cloud Platform (GCP) to build and deploy ML models, including how to use GCP services such as BigQuery, Cloud Storage, Cloud AI Platform, and Cloud Functions to build and deploy ML models. Who Should Take This Course? Data scientists Data engineers Machine learning engineers Software engineers Data analysts Data architects Business analysts Anyone interested in learning about machine learning and Google Cloud Platform Course One: Framing ML Problems Course Two: Architecting ML solutions Course Three: Designing data preparation and processing systems Course Four: Developing ML models Course Five: Automating and orchestrating ML pipelines Course Six: Monitoring, optimizing, and maintaining ML solutions Additional Popular Resources Pytest Master Class AWS Solutions Architect Professional Course Github Actions and GitOps in One Hour Video Course Jenkins CI/CD and Github in One Hour Video Course AWS Certified Cloud Practitioner Video Course Advanced Testing with Pytest Video Course AWS Solutions Architect Certification In ONE HOUR Python for DevOps Master Class 2022: CI/CD, Github Actions, Containers, and Microservices MLOPs Foundations: Chapter 2 Walkthrough of Practical MLOps Learn Docker containers in One Hour Video Course Introduction to MLOps Walkthrough AZ-900 (Azure Fundamentals) Quick reference guide 52 Weeks of AWS Episode 8: Infrastructure as Code with CDK and AWS Lambda Learn GCP Cloud Functions in One Hour Video Course Python Devops in TWO HOURS! MLOps Platforms From Zero: DatMLOps Platforms From Zero: Databricks, MLFlow/MLRun/SKLearn AWS Machine Learning Certification In ONE HOUR Fast, documented Machine Learning APIs with FastAPI Zero to One: AWS Lambda with SAM and Python in One Hour AWS Storage Solutions 2022: EBS/S3/EFS/Glacier Python Bootcamp for Data Testing In Python book Minimal Python book Practical MLOps book Python for DevOps-Playlist.

Abstract: Learn the essential tools and techniques for hunting and exploiting vulnerabilities in web and Android applications. Equip yourself with the knowledge and skills to find and responsibly disclose vulnerabilities to companies, gaining rewards through existing bug bounty programs. Master the best practices of ethical hacking to detect bugs and improve security. This comprehensive, seven-hour course covers three key areas: Fundamentals of OWASP Top 10 Vulnerabilities We start the course with a look at the most common vulnerabilities currently present in web applications. The OWASP Top Ten, from the Open Web Application Security Project, helps bug bounty hunters to know what to look for in penetration tests. We break down these vulnerabilities and demonstrate what to look for in order to detect them. Kali Linux and Web Application Hacking Web applications are currently some of the most common targets for bug bounties, so we'll see how to create meaningful attacks against them. We'll use Kali Linux tools, which are popular with both attackers and the defenders trying to secure web apps against those attacks. We'll work with Nmap, SQLmap, Commix, Wfuzz, Metasploit, and many other tools to gather information about targets and launch attacks to expose their vulnerabilities. Foundations of Hacking and Penetration Testing Android Apps Most companies now have apps that are included in bug bounty programs. Learning how to scan and exploit these apps can often be a lucrative way to gain bounties. Given the new focus on application development, apps make a great target for bug bounties.

Abstract: Akka is a toolkit that simplifies the process of building concurrent, distributed, and fault-tolerant applications and systems without compromising performance. Written in Scala, Akka uses a module system for implementation and an approach to concurrency based on the actor model. This easy-to-follow course provides a great introduction to the basics of Akka and distributed computing. You will learn these fundamentals by working with hands-on examples so you can put the concepts into action and see how they work. By the end of this course, you will have experience working with: actors, futures, routing, scheduling, and more. If you are an Akka newbie looking to get a great foundation in Akka and distributed computing, you've come to the right place!.

Abstract: Every company uses software to function. From Fortune 500 technology companies to sole-proprietor landscaping firms, software is integral to businesses large and small. The right software, properly secured, can help organizations to move quickly and stay ahead of their competition. Business software provides a means to track employees, customers, inventory, and scheduling. Data moves from a myriad of systems, networks, and software applications, providing insights to businesses looking to stay competitive. Depending on the needs and resources of a company, it may develop and build its own software, or it may purchase ready-made software and integrate it into the business operations. What this means is that every organization, regardless of size and industry, has a software need. That is why there is an urgent need for people to develop and implement secure software. That's where this course comes in: it is designed to help you become one of those crucial people. This course will familiarize you with the common vulnerabilities that plague developed code, as outlined by the publications that set the industry standards, such as the OWASP Top 10 list of critical risks and the SANS Top 25 list of most dangerous flaws in software. You will understand what type of development behaviors lead to vulnerabilities and how to avoid those behaviors when creating secure code. You will learn how to perform a threat model on development features to understand what threats could impact your code, where they come from, and how to mitigate them. You will also learn to review and operate developer analysis tools to discover vulnerabilities, allowing you to correct them early in the development life cycle. Finally, you will understand how application security fits in an overall cyber security program.

Abstract: Discover how to land your dream IT job with the Complete IT Job Search Course. This course covers all aspects of the IT job search, starting with deciding which IT field you want to specialize in, researching your target companies and how to use that research to your advantage during the job search. You'll learn how to create an IT-focused resume, leverage LinkedIn, and have a successful interview. You will also learn how to develop your skills and build your brand, and how to stay on top of all the new technologies so you don't get left behind.

Abstract: Python is the #1 programming language for beginners due to its simple syntax, wide range of applications, and helpful community resources. This course, intended for absolute beginners, will start you on your coding journey with Python 3, the most recent version of the language. We start by setting up a Python environment and learning programming basics, then move on to cover object-oriented programming, regular expressions, interacting with HTTP (Hypertext Transfer Protocol), networking and more. Enroll now to receive over 17 hours of HD video tutorials with English captions, and a certificate of completion! Python calculator After learning Python basics, we will code our first program, a calculator. Web scraping We will code a simple web scraper to extract data rom a web site. This will demonstrate how to use Python to interact with HTTP. Chat program We will code a chat program using another communication protocol, WebSockets, to learn the basics of networking with Python.

Abstract: This is the course for people who want to get started programming with Python, and are interested in entering the fields of coding or data science. But it is comprehensive enough for more experienced Python coders who want to brush up on their skills or fill in missing gaps. With over 18 hours of HD video tutorials, this course is designed to fully immerse you in the Python language as you start from the basics of programming and go through to advanced Python concepts. We'll also cover web scraping, PyMongo, WebPy development, Django web framework, GUI programming, data visualization, machine learning, and much more. Get hands-on practice building these ten coding projects: Simple calculator RPG battle script Web scraper PyMongo database Webpy web app Django website PyQt calculator GUI PyQt web browser Data visualization with matplotlib and Pandas Speech recognition & AI.

Abstract: Master ethical hacking while working on practical Python coding projects. Learn Python hacking skills, ethical hacking principles, penetration testing, cybersecurity, and more with over 17 hours of video tutorials. Designed for those with intermediate- to advanced-level understanding of ethical hacking, this course is still taught in a step-by-step, beginner-friendly method. We begin with coding basic port and vulnerability scanning tools; move onto SSH, FTP, and spoofing attacks; take a look at network analysis; and finish up with coding a reverse shell, command and control center, and several website penetration testing tools. Upon completing this course, you will be prepared for a job in the cybersecurity industry. Learn all these skills while completing eight coding projects: Port and vulnerability scanner SSH brute-forcer MAC address changer ARP spoofer DNS spoofer Multi-functioning reverse shell Keylogger Command and control center.

Abstract: Assimilate ONNX Learning about ML Model portability During Live Coding This video series covers live coding the Language iteratively thus learning the language. Lessons Covered Include: 1.0 Getting started with ONNX. In this live coding session I was able to get both resnet and ONNX working in Rust with Sonos/Trac. Learning Objectives Learn to work with ONNX models Learning to build solutions with ONNX models in Rust Learning the key syntax and features ONNX models Additional Popular Resources Pytest Master Class AWS Solutions Architect Professional Course Github Actions and GitOps in One Hour Video Course Jenkins CI/CD and Github in One Hour Video Course AWS Certified Cloud Practitioner Video Course Advanced Testing with Pytest Video Course AWS Solutions Architect Certification In ONE HOUR Python for DevOps Master Class 2022: CI/CD, Github Actions, Containers, and Microservices MLOPs Foundations: Chapter 2 Walkthrough of Practical MLOps Learn Docker containers in One Hour Video Course Introduction to MLOps Walkthrough AZ-900 (Azure Fundamentals) Quick reference guide 52 Weeks of AWS Episode 8: Infrastructure as Code with CDK and AWS Lambda Learn GCP Cloud Functions in One Hour Video Course Python Devops in TWO HOURS! MLOps Platforms From Zero: DatMLOps Platforms From Zero: Databricks, MLFlow/MLRun/SKLearn AWS Machine Learning Certification In ONE HOUR Fast, documented Machine Learning APIs with FastAPI Zero to One: AWS Lambda with SAM and Python in One Hour AWS Storage Solutions 2022: EBS/S3/EFS/Glacier Python Bootcamp for Data Testing In Python book Minimal Python book Practical MLOps book Python for DevOps-Playlist.

Abstract: Knowing how databases work is a considerable benefit in every career path, whether you are interested in marketing, account management, research programming, or countless other fields. Even more valuable is knowing how to design and build databases, how to query them and analyze the output. In this course you will learn all this, using the popular MySQL database management system. You will be guided through the basics of the SQL query language and introduced to MySQL databases, and then you will practice making queries. By the end of the course, you will be confident creating and managing a database. MySQL is very fast and compact, so you can run it alongside your other applications on a laptop or desktop.Yet it is a powerful and valuable tool for the many data-driven tasks that need completing. Let's get started!.

Abstract: Linux for Absolute Beginners is a course designed for Linux certification that will help you gain experience in the command line and Linux administration. You will be taught how to use options to modify the way a command works and use the three types of help commands used in most Linux distributions. Some other key topics included are installing and configuring Linux, as well as the different system utility commands and more about Linux permissions.

Abstract: Getting Started with the Zig Programming Language Learning the Language During Live Coding This video series covers the basics of the Zig programming language through live coding, allowing viewers to learn the language iteratively as it is being used. Lessons Covered 1.0 Getting Started Learning Objectives Learn the fundamentals of the Zig programming language Learn to build solutions with Zig Learn the key syntax and features of Zig Additional Popular Resources Pytest Master Class AWS Solutions Architect Professional Course Github Actions and GitOps in One Hour Video Course Jenkins CI/CD and Github in One Hour Video Course AWS Certified Cloud Practitioner Video Course Advanced Testing with Pytest Video Course AWS Solutions Architect Certification In ONE HOUR Python for DevOps Master Class 2022: CI/CD, Github Actions, Containers, and Microservices MLOPs Foundations: Chapter 2 Walkthrough of Practical MLOps Learn Docker containers in One Hour Video Course Introduction to MLOps Walkthrough AZ-900 (Azure Fundamentals) Quick reference guide 52 Weeks of AWS Episode 8: Infrastructure as Code with CDK and AWS Lambda Learn GCP Cloud Functions in One Hour Video Course Python Devops in TWO HOURS! MLOps Platforms From Zero: DatMLOps Platforms From Zero: Databricks, MLFlow/MLRun/SKLearn AWS Machine Learning Certification In ONE HOUR Fast, documented Machine Learning APIs with FastAPI Zero to One: AWS Lambda with SAM and Python in One Hour AWS Storage Solutions 2022: EBS/S3/EFS/Glacier Python Bootcamp for Data Testing In Python book Minimal Python book Practical MLOps book Python for DevOps-Playlist.

Abstract: Google Professional Cloud Architect Certification Course 2023 (Rough Draft) Welcome to the Google Professional Cloud Architect Certification Course! This course is designed to help you prepare for the Google Cloud Certified Professional Cloud Architect certification exam. As a professional cloud architect, you will be responsible for designing, developing, and managing secure, scalable, and highly available cloud solutions using Google Cloud Platform. Course Overview Course One: Designing and planning a cloud solution architecture 1.0 Rough Draft Introduction Introduction to Google Professional Architect Course Onboarding to GCP Cloud Designing a solution infrastructure that meets business requirements Designing a solution infrastructure that meets technical requirements Designing network, storage, and compute resources Using Google Cloud Functions Running Minikube Running Minikube with FastAPI for Kubernetes development Getting Started with Google Cloud Run Load testing with locust Design technical solutions for evolution and migration SRE Mindset Conclusion and Next Steps Course Two: Managing and provisioning a solution infrastructure Introduction to Google Professional Architect Course Two Exploring Network Topologies in GCP: A Demonstration Embracing Hybrid Networking in Google Cloud Platform Overview of GCP Storage Demo of using the SDK and CLI to manage storage Data lifecycle management Data security Demo of building Rust deduplication finder Compute volatility configuration (preemptible vs. standard) Demo Build and Deploy Rust Actix Microservice Cloud Run Container orchestration with GKE Demo of extending Google Cloud Functions Conclusion Course Two Course Three: Designing for Security and Compliance Introduction to Google Professional Architect Course Three Mastering Identity and Access Management in GCP Data Security Best Practices for GCP Secrets Manager API: A Hands-on Guide Exploring a data poisoning attack Meeting Industry Certification Requirements in GCP Auditing GCP Security with Log Analysis Creating Custom Log Dashboards for GCP Security Monitoring Scanning Web Applications with GCP's Cloud Web Security Scanner Analyzing GCP Logs with BigQuery GCP Security: Conclusion and Next Steps Course Four: Designing and optimizing technical and business processes Introduction to Google Professional Architect Course Four Continuous Delivery: An Introduction Hands-on with Continuous Integration in GCP Troubleshooting Techniques: The Five Whys Implementing Simple GitHub Actions for CI/CD The Three Most Important Files in a Python Project Utilizing Trello for Effective Project Management Leveraging Spreadsheets for Project Management Exploring the MLOps Maturity Model Building Bespoke Systems for Core Business Functions Data Science on Windows: Virtualenv and Pip Site Reliability Engineering (SRE) in GCP Performing Load Testing in GCP: A Demo Course Five: Managing and optimizing cloud solution Implementation Introduction to Google Professional Architect Course Five Makefiles Made Easy: A Comprehensive Guide Configuring Your Bashrc for an Optimal Environment Implementing Continuous Integration for Rust with GitHub Actions Unit Testing in Rust: A Hands-on Demonstration Supercharging Rust Development with Copilot Setting Up a GCP Workstation for Python Development Mastering Google Cloud Shell: A Practical Guide Streamline Your Development with Google Cloud Editor Getting Started with the Google Cloud CLI SDK Unleashing the Power of Google Cloud's 'gcloud' Command-Line Tool Deploying Rust Applications to App Engine: A Step-by Course Six: Ensuring solution and operations reliability Introduction to Google Professional Architect Course Six Monitoring and Logging Rust App Engine Applications: A Demo Uncovering the Advantages of Cloud Developer Workspaces Operationalizing Microservices in the Cloud Introducing GitHub Codespaces for Streamlined Development Compiling Python Projects in GitHub Codespaces Mastering Continuous Integration in GCP Course Wrap-up and Future Steps in Your GCP Journey Learning Objectives Design and optimize cloud solutions Analyze and optimize technical and business processes Manage and provision cloud infrastructure Ensure solution and operations reliability By the end of this course, you will have the knowledge and skills needed to pass the Google Cloud Certified Professional Cloud Architect exam and to effectively design and manage cloud solutions using Google Cloud Platform. Additional Popular Resources Pytest Master Class AWS Solutions Architect Professional Course Github Actions and GitOps in One Hour Video Course Jenkins CI/CD and Github in One Hour Video Course AWS Certified Cloud Practitioner Video Course Advanced Testing with Pytest Video Course AWS Solutions Architect Certification In ONE HOUR Python for DevOps Master Class 2022: CI/CD, Github Actions, Containers, and Microservices MLOPs Foundations: Chapter 2 Walkthrough of Practical MLOps Learn Docker containers in One Hour Video Course Introduction to MLOps Walkthrough AZ-900 (Azure Fundamentals) Quick reference guide 52 Weeks of AWS Episode 8: Infrastructure as Code with CDK and AWS Lambda Learn GCP Cloud Functions in One Hour Video Course Python Devops in TWO HOURS! MLOps Platforms From Zero: DatMLOps Platforms From Zero: Databricks, MLFlow/MLRun/SKLearn AWS Machine Learning Certification In ONE HOUR Fast, documented Machine Learning APIs with FastAPI Zero to One: AWS Lambda with SAM and Python in One Hour AWS Storage Solutions 2022: EBS/S3/EFS/Glacier Python Bootcamp for Data Testing In Python book Minimal Python book Practical MLOps book Python for DevOps-Playlist.