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: Perplexed by concurrency? Don’t be. This engaging, fully-illustrated beginner’s guide gets you writing the kind of high-performance code your apps deserve. Inside, you’ll find thorough explanations of concurrency’s core concepts—all explained with interesting illustrations, insightful examples, and detailed techniques you can apply to your own projects. Grokking Concurrency is a perfectly paced introduction to the fundamentals of concurrent, parallel, and asynchronous programming. In it, you’ll learn the practices you’ll need to program multicore processors, GPUs, and other high-performance systems. Author Kirill Bobrov skips the math, jargon, and academic language and concentrates on clear, plain-English explanations.

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: Cloud Observability in Action gives you the background and techniques you need to successfully introduce observability into cloud-based serverless and Kubernetes environments. In it, you’ll learn to use open standards and tools like OpenTelemetry, Prometheus, and Grafana to build your own observability system and end reliance on proprietary software. You’ll discover insights from different telemetry signals, including logs, metrics, traces, and profiles. Plus, the book’s rigorous cost-benefit analysis ensures you’re getting a real return on your observability investment.

Abstract: Distributing machine learning systems allow developers to handle extremely large datasets across multiple clusters, take advantage of automation tools, and benefit from hardware accelerations. This book reveals best practice techniques and insider tips for tackling the challenges of scaling machine learning systems. Inside Distributed Machine Learning Patterns you’ll learn to apply established distributed systems patterns to machine learning projects—plus explore cutting-edge new patterns created specifically for machine learning. Firmly rooted in the real world, this book demonstrates how to apply patterns using examples based in TensorFlow, Kubernetes, Kubeflow, and Argo Workflows. Hands-on projects and clear, practical DevOps techniques let you easily launch, manage, and monitor cloud-native distributed machine learning pipelines. Distributed Machine Learning Patterns provides dozens of techniques for designing and deploying distributed machine learning systems. In it, you’ll learn patterns for distributed model training, managing unexpected failures, and dynamic model serving. You’ll appreciate the practical examples that accompany each pattern along with a full-scale project that implements distributed model training and inference with autoscaling on Kubernetes.

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: It's easy to assume that being a software architect is mostly about technical decision-making, but the job involves much more than that. So, what are the skills that make a software architect, and what do you need to know to succeed in the job? Join us to discover how to build the skills you need to step into a software architect role with confidence. You'll explore how to design distributed systems, work with architectural patterns, manage data, collaborate with teams, and more. By the time you're through, you'll understand why the answer to so many questions in software architecture is "It depends" and how to assess the trade-offs that will influence your decision-making. What you'll learn and how you can apply it Use architectural design patterns to make architectural choices Understand why architectural decisions are important and how to make them efficiently Think like a software architect and consider trade-offs effectively This live event is for you because... You're an aspiring software architect who wants to understand which skills you need to progress in your career. You're a software architect who wants to explore key skills in more detail. Recommended follow-up: Read Fundamentals of Software Architecture (book) Please note that slides or supplemental materials are not available for download from this recording. Resources are only provided at the time of the live event.

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: 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: Over the past year, generative AI has dominated headlines. We know that it's being used to write code, but how can you leverage its power in software architecture when every company's architecture is different? How can you convert the knowledge automated by AI into the wisdom required for software architecture? What are the best ways to use this powerful tool to improve your architecture's security and resiliency? Join us to discover how AI may impact software architecture and how you can use it in your architectural processes right now. You'll explore AI for SaaS architecture, how to use AI to create diagrams, and more. If you're looking to stay one step ahead, these sessions are for you. What you'll learn and how you can apply it Understand the possibilities and risks of AI so you can judge when and how to use it Learn how GenAI mechanisms can influence core SaaS architecture strategies and how you can implement this in your SaaS solution Explore the use of prompt engineering for architectural tasks and leverage generative AI to improve their work This live event is for you because... You want to understand how to use generative AI to improve and communicate your software architecture. You're a senior-level developer who wants to make the move to architect. You're a practicing software architect who wants to hone your skills and learn new software architecture techniques and practices. Recommended follow-up: Read Building Multi-Tenant SaaS Architectures (book) Read Communication Patterns (book) Read Software Architecture: The Hard Parts (book) Please note that slides or supplemental materials are not available for download from this recording. Resources are only provided at the time of the live event.

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: Join Neal Ford and Zhamak Dehghani for a discussion about the challenges of creating, sharing, and finding data and making your data work for you. With the rise of generative AI, companies need to manage large quantities of data and are looking at distributed data systems and data mesh to solve this challenge. The problem consists in getting from their existing data storage to a distributed data system that works for all stakeholders. As the originator of the concept of data mesh, and because of her ongoing work with scaling decentralized data, Zhamak is well positioned to provide updates and advice on this more holistic approach to data management. What's New in Software Architecture gives you a chance to explore trending topics in software architecture and to ask Neal and Zhamak Dehghani anything you want about data mesh, how to begin making the move to decentralized data, and their own career journeys. We will spend a few minutes covering the trends that are influencing software architecture and then tell you what you need to know to stay ahead of the curve. What you'll learn and how you can apply it Understand what a data mesh is and how it differs from other methods of storing and sharing data Learn the key data characteristics you need to be a data-led organization Explore the tools that can help you make the move to data mesh This live course is for you because... You want to hear from Neal Ford and Zhamak Dehghani about software architecture and data mesh. Recommended Follow-Up: Read Building an Event-Driven Data Mesh (book) Read Data Mesh (book) Please note that slides or supplemental materials are not available for download from this recording. Resources are only provided at the time of the live event.

Abstract: Acing the System Design Interview is a masterclass in how to confidently nail your next interview. Following these easy-to-remember techniques, you’ll learn to quickly assess a question, identify an advantageous approach, and then communicate your ideas clearly to an interviewer. As you work through this book, you’ll gain not only the skills to successfully interview, but also to do the actual work of great system design.

Abstract: Welcome to our Next.js Mastery course where you'll journey into the world of Next.js and React to become a proficient developer. In this comprehensive course, we'll cover a range of essential topics to equip you with the skills and knowledge needed to create top-tier web applications. Our journey begins with an introduction to Next.js, highlighting its key features and advantages. We'll set clear expectations for what you'll learn in the course and prepare you for the hands-on experience ahead. Dive into practical aspects, including setup and installation, Next.js basics, and mastering React Hooks like useState, useEffect, and useMemo. Routing in Next.js is a vital skill, and we'll cover it extensively. Explore creating dynamic and user-friendly navigation systems, from basic routing to nested routing. Additionally, we'll understand layout design, the differences between common and conditional layouts, and how to effectively implement middleware. Our course places a strong emphasis on API integration, encompassing both client-side and server-side APIs. Gain hands-on experience working with data from external sources and grasp the nuances of client and server components. We'll also delve into optimization, covering image optimization, SEO best practices, and fundamental styling techniques to enhance user experiences. By the course's end, you'll emerge as a Next.js expert, capable of building efficient, optimized, and feature-rich web applications. Whether you're a beginner or an experienced developer, our Next.js Mastery course will empower you to create web applications that excel in the digital landscape.

Abstract: Harness the potential of extracting web data with our detailed course on Web Scraping using Beautiful Soup in Python. Begin your journey with an introduction to the basics of web scraping. Learn why Python and its robust library, Beautiful Soup, are favorites among developers and data enthusiasts. Immerse yourself in the details of HTML structures, learning to identify and navigate through various HTML tags and mastering CSS selectors to precisely extract the data you need. Take advantage of the Requests library for easy and effective management of HTTP requests, simplifying the process of web content retrieval. Advance your skills with hands-on experience in Beautiful Soup, covering everything from fundamental parsing to sophisticated data extraction methods. Practical application is key. Our course offers numerous real-world projects, giving you the chance to apply your skills in different settings, including tracking eBay prices, extracting top hits from Billboard, sourcing movie recommendations from IMDB, and keeping an eye on Bitcoin prices. Complete this course with the ability to effortlessly scrape web data and turn it into valuable insights.

Abstract: This course is meticulously designed to take you on a transformative journey from the rudiments of React.js and JavaScript to crafting a fully functional e-commerce website. E-commerce has reshaped the world of business. As the digital era evolves, the need for skilled developers capable of creating robust online platforms becomes imperative. This course aims to bridge the knowledge gap, blending the world of e-commerce with the technical prowess of React.js, a leading JavaScript library known for its efficiency and flexibility. We commence by demystifying e-commerce's essence, highlighting how React.js can serve as a powerhouse for online retail solutions. For those new to React or needing a refresher, our foundational modules provide a concise dive into essential JavaScript constructs, ensuring a sturdy base. Transitioning to more advanced territory, we delve into React's intricate functionalities—mapping, filtering, and the distinction between JavaScript and JSX. Crucially, React Hooks—a pivotal aspect of modern React development—will be unraveled, focusing on useState and useEffect to instill dynamic capabilities into your applications. The course crescendos into its practical phase, where you'll piece together an e-commerce platform. Each segment, from crafting intricate navigation systems to designing a responsive shopping cart and integrating a secure login mechanism, is taught through hands-on exercises, ensuring theoretical knowledge is always complemented by practical application. Whether you're an aspiring web developer, a business-minded individual eyeing the vast landscape of online commerce, or simply someone seeking to expand their skill repertoire, this course promises a comprehensive learning experience. By its conclusion, you'll not only wield the knowledge of React.js intricacies but also possess a tangible e-commerce platform prototype, a testament to your hard work and ready for further refinement and deployment.

Abstract: Welcome to this immersive course designed to take you from a basic understanding to a proficient level in using Git and GitHub, two of the most essential tools in modern software development. This course begins by laying a solid foundation with an introduction to the core concepts of version control, the significance of Git and GitHub in the development world, and the differences between them. We dive into why these tools are indispensable for developers, ensuring even absolute beginners grasp the basics. We then progress to practical aspects, guiding you through installations and account setups. You'll learn how to install Git, set up a GitHub account, and configure necessary tools like Visual Studio Code. This practical approach ensures you're not just learning concepts but also applying them in real-world scenarios. The heart of the course lies in mastering the basics of GitHub. You'll explore how to create and manage repositories, understand branching, make pull requests, address issues, and more. We also delve into the Git Command Line Interface (CLI), teaching you essential commands and how to use Git for effective version control. Advanced topics are not left out. We'll introduce you to GitHub Desktop, Git Bash, GitHub Extensions, and the innovative GitHub Copilot. By the end of this course, you'll have a comprehensive understanding of Git and GitHub, equipped to handle code in a collaborative environment with ease and confidence. Whether you're a beginner programmer, a project manager, or just passionate about coding, this course will provide the knowledge and skills necessary to excel in your coding journey.

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: Bootstrapping Microservices, Second Edition is your microservices mentor. It teaches you to use industry-standard tools to create a working video streaming application from the ground up. You'll learn the pillars of cloud-native development, including Terraform for configuration, Docker for packaging, and a basic Kubernetes deployment. Plus, this second edition includes coverage of GitHub Actions, continuous delivery, and Infrastructure as Code.

Abstract: In today's digital world, mobile apps have become an integral part of our daily lives, driving the need for proficient mobile app developers. This comprehensive course is tailored to both beginners and experienced developers, providing a deep dive into the world of React Native. Begin your journey by unraveling the nuances of app development, distinguishing between app and web landscapes, and understanding the pivotal role of React Native in the current tech arena. Dive deeper to uncover the heart of React Native, including its core concepts, file structures, and vital components. JavaScript is the backbone of React Native, and we'll ensure you gain a robust understanding. Whether it's basic constructs like variables and operators or advanced functionalities like map and filter, this course has got you covered. But what's an app without aesthetics and user experience? Learn the art and science of styling in React Native. Delve into various styling methodologies, layout techniques, and the critical aspect of app navigation. By the end of this course, not only will you be equipped with the knowledge to build dynamic apps, but you'll also have a keen sense of design and navigation, ensuring your apps are both functional and user-friendly. Whether you're aiming for a career transition, enhancing your current skills, or nurturing a hobby, this course is your gateway to mobile app mastery.

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: Dive into the dynamic world of web development with our comprehensive course catering to both beginner and intermediate learners. It's a deep dive into the fundamental principles of PHP, one of the most popular server-side scripting languages. The journey begins with an introduction to PHP, paving the way for essential tools such as the installation of XAMPP SERVER and an exploration of PHP syntax. Our step-by-step approach ensures a solid foundation, paving the way for more advanced concepts. Dive into the heart of PHP by tackling crucial topics such as data types, variables, and operators. Understand the importance of constant variables, arithmetic, assignment, and logical operators in PHP programming. This section is essential for mastering the syntax and logic of the language. The course then transitions into the 'Basics of PHP', where learners engage with conditional statements (If, Else If), loops (While, Do While, For), and the construction of functions. These elements are vital in building dynamic and responsive web applications. Additionally, the module on 'Types of Strings' offers insights into efficient data handling and manipulation. A significant portion of the course is dedicated to 'Array Methods'. Here, you'll learn about array manipulation techniques including count, sizeoff, searching, replacing, slicing, splicing, and more. These skills are indispensable for data management in PHP. 'POST and GET' methods form the backbone of data submission and retrieval in web forms. Our focused sessions on form validation using GET, POST methods, and handling input types like radio buttons, equip you with the skills to manage user inputs securely and effectively. MySQL integration is another cornerstone of this course. You'll gain expertise in MySQL database management, table structure, configuration, and executing basic to advanced database operations. The course culminates in a project-based module, 'Queries and Project', where you'll apply your skills in real-world scenarios. This includes database updates, form UI design, database connections, and user data management. This course empowers you with the knowledge and skills to excel in PHP and MySQL, opening doors to numerous opportunities in web development.

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: Join Neal Ford and his guest Pramod Sadalage, director at Thoughtworks, to get an expert perspective on what the future holds for data-driven architecture. Big data is getting bigger all the time, so you know you’ll have to support a data-driven strategy at some point, but what will that entail? How will you develop partnerships between database professionals, software developers, and software architects? Learn the best practices and principles for designing and future-proofing your data architecture without complicating it.

Abstract: One month. One hour a day. That's all it takes to start writing Rust code! Learn Rust in a Month of Lunches teaches you to write super fast and super safe Rust code through lessons you can fit in your lunch break. Crystal-clear explanations and focused, relevant examples make it accessible to anyone--even if you're learning Rust as your first programming language. By the time you're done reading Learn Rust in a Month of Lunches you'll be able to: Build real software in Rust Understand messages from the compiler and Clippy, Rust's coding coach Make informed decisions on the right types to use in any context Make sense of the Rust standard library and its commonly used items Use external Rust "crates" (libraries) for common tasks Comment and build documentation for your Rust code Work with crates that use async Rust Write simple declarative macros Explore test driven development in Rust Learn Rust in a Month of Lunches is full of 24 easy-to-digest lessons that ease you into real Rust programming. You'll learn essential Rust skills you can use for everything from system programming, to web applications, and games. By the time you're done learning, you'll know exactly what makes Rust unique--and be one of the thousands of developers who say it's their best loved language! About the Technology Learn how to create fast powerful programs in Rust in just 24 short lessons! Rust gives you modern features like a top-notch compiler, a rich ecosystem of pre-built libraries, and the same low-level performance you get with a language like C, but without the awkward syntax, complex memory management, and code safety concerns. This book guides you step by step from your first line of code. About the Book Learn Rust in a Month of Lunches breaks down the Rust language into concise hands-on lessons designed to be completed in an hour or less. The examples are fun and easy to follow, so you'll quickly progress from zero Rust knowledge to handling async and writing your own macros. You won't even need to install Rust--the book's code samples run in the browser-based Rust Playground. There's no easier way to get started! What's Inside Build working Rust software Understand messages from the compiler and Clippy Use external Rust "crates" (libraries) for common tasks Explore test driven development in Rust About the Reader No previous experience with Rust required. About the Author Dave MacLeod was an educator, Korean-English translator, project controller, and copywriter before becoming a full-time Rust developer. The technical editor on this book was Jerry Kuch. Quotes Breaks the journey down into manageable parts, teaching in small increments and making consistent progress. If you've put off learning Rust, this is the book for you! - Luca Palmieri, Mainmatter Covers all you need to start programming in Rust. - Jonathan Reeves, Wolfjaw Studios Simple language and a great pace. Easy-to-understand examples cover key language concepts. It's everything you need to know to get going. - Steve Fenton, Octopus Deploy Unlock your potential as a Rust programmer with this exceptional guide. - Srikar Vedantam, Volvo Group.

Abstract: Welcome to this comprehensive beginner's course designed to unlock your creative potential in the realm of 3D design. Throughout this course, you will be introduced to the fundamentals of 3D design, the layout and functionality of SketchUp, and the techniques necessary to transform your ideas into digital reality. You will engage in hands-on projects, encouraging you to apply learned concepts while cultivating a robust understanding of SketchUp's tools and applications. By the end of this course, you will not only grasp the essentials of SketchUp but also gain the confidence to explore more complex design challenges. You will develop a strong foundation that will serve as a stepping stone towards more advanced 3D modeling techniques. So, whether you are an aspiring architect, an interior designer, a game developer, or someone who loves to create, this course offers a fun, flexible, and comprehensive approach to 3D modeling. Let's start modeling!

Abstract: Dive deep into the core principles of Single Page Applications (SPAs) and understand why Angular stands out from other frameworks, gaining insights that will help you make informed decisions in your projects. We cover everything from setting up your development environment in Visual Studio Code to the intricacies of TypeScript, ensuring that you have a solid foundation to build upon. Our hands-on approach means you'll be writing code from day one. Explore JavaScript, ES6, and TypeScript basics, learning how these technologies come together to create robust web applications. You'll grasp essential programming concepts, understand data types, functions, events, and master the use of the "this" keyword. Angular 16 brings a plethora of features and improvements, and you'll learn how to leverage them to create highly interactive and responsive web applications. From creating components to understanding directives, routing, and component interaction, you'll acquire the skills to handle complex development challenges. RxJS and reactive programming are at the heart of Angular. This course offers an in-depth exploration of RxJS, teaching you how to manage asynchronous operations and data flow like a pro. You'll work with Observables, Operators, and Subjects, unlocking patterns and techniques that are key to building high-performance applications. We'll integrate third-party libraries like Bootstrap, enhancing the visual appeal and responsiveness of your applications. Through real-world projects, you'll apply your learning, reinforcing concepts, and building confidence in your abilities. By the end of this course, you'll have a comprehensive understanding of Angular 16, RxJS, and the best practices in modern web development, poised to tackle complex projects and create seamless, efficient web applications.

Abstract: Whether you're a beginner eager to delve into the realm of 3D design, or an experienced professional aiming to enhance your skills, this course offers a wealth of knowledge and practical insights to elevate your proficiency. Kick-start your learning experience with an insightful introduction to AutoCAD 3D, where you will unravel the differences between 2D and 3D design, and grasp the fundamental concepts that underpin 3D modeling. As you progress to setting up your workspace, you will learn to customize the user interface, optimize display settings, and understand the coordinate system, ensuring a smooth and efficient design process. Dive deep into creating basic and advanced 3D objects, exploring a myriad of tools and techniques that bring your designs to life. From box and sphere to intricate gears and bolts, you'll master the art of 3D object creation and modification. The course also shines a spotlight on 3D house modeling, providing step-by-step guidance on designing architectural elements, applying materials and textures, and incorporating lighting for a touch of realism. Furthermore, you'll unlock the secrets to impeccable documentation and presentation, generating 2D drawings from your 3D models, annotating, dimensioning, and creating stunning renderings and walkthrough animations. This comprehensive course ensures you're well-equipped with the skills and knowledge to excel in the field of 3D design and modeling, paving the way for endless possibilities and career advancement.

Abstract: Revolutionize your architectural designs with Revit 2023! In this course, you will embark on an exciting journey to unlock the full potential of Revit, the industry-standard software that has transformed the world of architecture, engineering, and construction. The course is designed to empower you with the latest features, functionalities, and best practices of Revit. Prepare to dive deep into the world of Revit 2023, as you explore advanced modeling techniques to craft accurate and compelling building designs. You will master the key concepts of Building Information Modeling (BIM), become proficient with the Revit interface and navigation, and tackle essential topics such as site design, massing, floor plans, sections, elevations, and 3D views. Furthermore, you will learn how to work with families, manage and coordinate your projects, and create visually stunning visualizations. By the end of this course, you will not only have a solid understanding of the capabilities of Revit 2023, but you will also be equipped with the skills needed to create professional building designs and documentation that will leave a lasting impression. Equipped with this knowledge and skillset, you will be well-positioned to contribute meaningfully to any architectural project, enhancing your professional portfolio and establishing yourself as a proficient Revit practitioner.

Abstract: This intensive program is designed for both beginners eager to dive into the world of data science and seasoned professionals looking to deepen their understanding of machine learning, deep learning, and TensorFlow's capabilities. Starting with Python—a cornerstone of modern AI development—we'll guide you through its essential features and libraries that make data manipulation and analysis a breeze. As we delve into machine learning, you'll learn the foundational algorithms and techniques, moving seamlessly from supervised to unsupervised learning, paving the way for the magic of deep learning. With TensorFlow, one of the most dynamic and widely-used deep learning frameworks, we'll uncover how to craft sophisticated neural network architectures, optimize models, and deploy AI-powered solutions. We don't just want you to learn—we aim for you to master. By the course's end, you'll not only grasp the theories but also gain hands-on experience, ensuring that you're industry ready. Whether you aspire to innovate in AI research or implement solutions in business settings, this comprehensive course promises a profound understanding, equipping you with the tools and knowledge to harness the power of Python, Machine Learning, and TensorFlow.

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: 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.

Abstract: Join us for this edition of O'Reilly Book Club with Mark Richards and Neal Ford, author of Fundamentals of Software Architecture and Software Architecture: The Hard Parts. Ask questions, learn tricks of the trade, listen to stories, and connect with other readers. What you'll learn and how you can apply itUnderstand what software architecture is and why it's so hard to define precisely Learn the fundamentals of software architecture (structure of the system combined with architecture characteristics, architecture decisions, and design principles) Explore the importance of thinking like a software architect This recording of a live event is for you because... You want to go beyond the words on the page and hear from the authors. You want to learn from other software architects. Recommended follow-up: Read Fundamentals of Software Architecture (book) Read Software Architecture: The Hard Parts (book) Attend Software Architecture by Example (live event with Mark Richards and Neal Ford) Attend our 2023 Software Architecture Superstream events Attend our Software Architecture Hour events.

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: 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: Frontend developers and architects combine interface design skills and programming excellence to ensure that users can easily interact with their organizations' web pages. As the demand for online goods continues to grow, developers, architects, and designers will need to consider the efficiency, scalability, performance, and security of their websites to best support their customers. The rise of new language frameworks and micro-frontends means that it's now possible to create truly decoupled user interfaces leading to faster deploying and more scalability. Join leading experts and practitioners from the field for a deep dive into the discipline of frontend architecture. You'll gain insight into the latest tools, standards, and best practices that have elevated frontend web development to an entirely new level. What you'll learn and how you can apply it Understand how cloud native and the Web Platform APIs are pushing the boundaries of what was once known as the Jamstack and micro-frontends into a full stack composable architecture Learn what the future holds for frontend developers This recording of a live event is for you because... You're a software architect or developer working on or thinking about working on frontend architectures and want to learn best practices. You want to effectively develop your frontend architecture into a system where user data is "at the beck and call of the users themselves" for a more user-centric experience. Recommended follow-up: Listen to Blazor in Action (audiobook) Read Building Micro-Frontends (book) Read Micro Frontends in Action (book).

Abstract: Join us for a special conversation with Neal Ford and Anna Shipman, technical director at the Financial Times (FT). They'll discuss how the company brought seven disparate technical groups into a single cohesive engineering group with one tech strategy, focusing on how the FT changes its strategy to meet changing business needs. They'll also delve into ways of aligning engineering work with business strategy, how to refresh the vision and communicate the strategy, and how to execute it and keep it on track. This is a chance for you to hear from Neal and Anna about software, architecture, and their own career journeys. They'll spend a few minutes covering the trends that are influencing architecture, then tell you what you need to know to stay ahead of the curve. What you'll learn and how you can apply it Learn how to craft technical strategy and make sure it's aligned to business needs See what's coming next with software architecture This recording of a live event is for you because... You want the chance to hear from Neal Ford and Anna Shipman about the alignment between strategy and software architecture and what the future might look like. You're looking for ways to grow your own skills and to act as an innovator in your organization. Recommended follow-up: Read Building Microservices, second edition (book) Read Enabling Microservice Success (book) Listen to Building Microservices, second edition (audiobook) Listen to Microservices Patterns (audiobook) Watch Software Architecture Superstream: Microservices (video).

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: Join us for a special conversation with Neal Ford and Michael Feathers, founder and director of R7K Research & Conveyance, where they'll discuss the best way to handle making improvements to a large, unfamiliar code base--a task that starts with understanding code base technologies you've never seen before. Understanding the system, something that is rarely taught, is a vital part of software development. You'll hear about the patterns you can use to make this task successful. This is a chance for you to hear from Neal and Michael about software, architecture, and their own career journeys. They'll spend a few minutes covering the trends that are influencing architecture, then tell you what you need to know to stay ahead of the curve. What you'll learn and how you can apply it Get insights to support your work with legacy systems See what's coming next with software architecture This live course is for you because... You want the chance to hear directly from Neal Ford and Michael Feathers about the alignment between strategy and software architecture and what the future might look like. You are currently looking for ways to grow your own skills and to act as an innovator in your organization. Recommended follow-up: Read Working Effectively with Legacy Code (book) Read Refactoring: Improving the Design of Existing Code (book) Listen to Building Microservices, second edition (audiobook).

Abstract: Scripting with Python and SQL for Data Engineering Learn Python data structures, web scraping, SQL, and MySQL from the ground up. Master essential skills for collecting, storing, and working with data. In this hands-on course for beginners, you'll learn how to: Store and manipulate data using Python lists, dictionaries, JSON Write reusable scripts to process data Connect Python to databases like SQLite and MySQL Query, import, and export data with SQL Scrape and parse websites using Beautiful Soup and Scrapy Persist scraped data to databases and files You'll use the following example repositories to practice: Mapping data in Python Python Scripting Scrapping Basics Key topics include: Mapping, iterating, and persisting data structures Creating modules, scripts, and workflows in Python SQL essentials - queries, statements, aggregations Setting up connections from Python to SQLite and MySQL Scraping data locally and at scale with spiders Storing scraped data to optimize pipelines You'll build your data wrangling skills through practical examples and hands-on coding exercises in every lesson. By the end of the course, you'll have experience building end-to-end data engineering scripts. Whether you're a beginner looking to learn Python and SQL, or want to develop robust data engineering skills, this course will get you started. Enroll now and start collecting, storing, and working with data using Python and SQL You'll gain hands-on experience building Python scripts and SQL queries for common data engineering tasks. This course is divided in 4 weeks: Week 1 Working with Data in Python By the end of Week 1 you'll be able to: Apply Python data structures like lists, dicts Extract data from sources like CSV, JSON Load and persist data using JSON Lesson 1: Data Structures in Python Lesson Outline Lists, tuples, dictionaries Working with pandas DataFrames Loading data files like CSV into data structures Lesson 2: Reading and Writing Data Lesson Outline Reading and writing CSV files Serializing Python objects with JSON Parsing and dumping JSON data Lesson 3: Persisting and Loading Data in Python Lesson Outline Loading data from files Saving data from Python to disk Loading and saving data to JSON Week 2 Python Scripting and SQL By the end of Week 2 you'll be able to: Write reusable Python scripts Use SQLite to persist data Query SQLite databases with Python Lesson 1: Python Scripting Techniques Lesson Outline Writing modular, reusable Python scripts Exception handling and logging Python virtual environments Lesson 2: Python with SQLite Lesson Outline Creating SQLite databases from Python Writing tables with SQLAlchemy Querying SQLite from Python with SQLAlchemy Week 3 Learning Objectives By the end of Week 3 you'll be able to: Scrape and collect data from websites Build scalable scraping scripts Persist scraped data to files/databases Lesson 1: Web Scraping with Python Lesson Outline HTML parsing and structure Using Beautiful Soup for scraping Storing scraped data in Python Lesson 2: Scalable Web Scraping Lesson Outline Scraping best practices Scaling scraping with multiprocessing Storing scraped data in databases Week 4 Learning Objectives By the end of Week 4 you'll be able to: Connect to MySQL from Python Execute SQL statements and queries Import and export data from MySQL Lesson 1: Python and MySQL Lesson Outline Installing MySQL and configuration Connecting Python to MySQL Executing queries and statements Lesson 2: Running SQL queries from VSCode Use Visual Studio Code to build SQL queries Execute and review SQL queries from Visual Studio Code Lesson 3: Importing and Exporting Data Lesson Outline Loading and exporting CSV data Best practices for moving data into MySQL Automating data imports with Python 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 DevOps and MLOps will give you everything you need to get started applying these powerful concepts. Resources Python and Rust CLI Tools Linux For Beginners Hands on Python for MLOps.

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: 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: Join us for a special conversation with Neal Ford and Carola Lilienthal, where they will discuss how to make large improvements to your software architecture by measuring the amount of accidental complexity with the modularity maturity index (MMI). They'll dive into how the modularity maturity index (MMI) gives management and teams a guideline for deciding which software systems need to be refactored, which ones should be replaced, and which ones don't need to worry about so that you can find out which technical debt should be resolved so that the architecture becomes sustainable and maintenance becomes easier and less expensive. This is a chance for you to hear from Neal and Carola about software, architecture, and their own career journeys. We will spend a few minutes covering the trends that are influencing architecture and then tell you what you need to know to stay ahead of the curve. What you'll learn and how you can apply it What's coming next with Software Architecture This recording of a live event is for you because... You want the chance to hear from Neal Ford and Carola Lilienthal about methodologies to improve your software architecture. You are currently looking for ways to grow your own skills and to act as an innovator in your organization. Recommended follow-up: Read Software Architecture Metrics (book) Listen to Building Microservices, second edition (audiobook).

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: Sponsored by Cockroach Labs With an eye to the future, many organizations have made the move to microservices as a means of decomposing monolithic legacy systems. But what does a distributed system mean for delivering data? Join us to discover how understanding the intersection of software architecture and data can help you achieve new levels of velocity, agility, reliability, and efficiency. From the application of patterns to your machine learning systems to the rise of the data mesh architecture; there are now proven methods to simplify getting your company's data directly into the end users hands to accelerate business growth. If you're looking for ways to manage data as a software architect or developer, these sessions will help you learn what's involved so you can chart a course toward a successful solution. What you'll learn and how you can apply it Understand how to architect decentralized data systems Learn how to apply domain-driven design to your data Discover which software architecture issues you should consider when adopting and designing systems based on the NoSQL and distributed SQL databases This live event recording is for you because... You're a senior-level developer who wants to make the move to architect. You're a practicing software architect who wants to hone your skills and learn new software architecture techniques and practices. You want to better understand how to solve the unique problems of integrating data into your architecture. Recommended follow-up: Listen to Software Architecture: The Hard Parts (audiobook) Read Building an Event-Driven Data Mesh (book) Read Data Mesh (book).

Abstract: Microsoft Azure AI Fundamentals (AI-900) Certification Pass the AI Fundamentals certification This early release (ongoing) course will give you everything you need to pass the Azure AI Fundamentals (AI-900) certification. This is the foundational certification for doing Machine Learning and Data Science using Azure and its specialized services. The course will go into every content that is relevant to pass the certification including how to create a study guide and strategy to pass the exam. This course includes and covers all of the author's study notes so that you can use them in addition to your own notes . Course overview This course contains a complete walkthrough over all of the content relevant for the AI-900 certification with a summary and specialized notes after each sections, following the same content that is available as Learning Paths. Aside from the video content, create your own study notes and strategy using the example reference guide Course Content Get Started with AI Get Started with AI Study notes Get Started with Artificial Intelligence on Azure 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 studying and passing the AI-900 is seen throughout this course, where you will get a first-hand experience with study notes, example repositories, and a solid study strategy. Resources Pytest Master Class Practical MLOps book.

Abstract: Join us for a special conversation with Neal Ford and Mary and Tom Poppendieck, authors of four books including the groundbreaking 2003 title Lean Software Development: An Agile Toolkit. You'll learn what they think the future of software will look like and discover why what's most meaningful to software development isn't the newest technologies but knowing what value is and what's most important to work on. You'll also hear their insights on how to get from where you are now to where you need to be in a safe, reliable, and scalable way. This is a chance for you to hear from Neal, Mary, and Tom about software, architecture, and their own career journeys. They'll spend a few minutes covering the trends that are influencing architecture, then tell you what you need to know to stay ahead of the curve. What you'll learn and how you can apply it Find out what the future of software may look like Discover why it's essential to consider the value of your software See what's coming next with software architecture This recording of a live event is for you because... You want the chance to hear from Neal Ford and Mary and Tom Poppendieck about software engineering and architecture and what the future may hold for the field. You're looking to enhance your skills and innovate in your organization. Recommended follow-up: Read Software Architecture: The Hard Parts (book) Read Lean Software Development: An Agile Toolkit (book) Read Implementing Lean Software Development: From Concept to Cash (book) Read Leading Lean Software Development: Results Are Not the Point (book) Take Software Architecture by Example (live online course with Neal Ford and Mark Richards) Watch Software Architecture Superstream: Software Architecture Trade-Offs (live event on January 18).

Abstract: One of the most difficult tasks an architect will face is untangling the various forces and trade-offs at play in their architectures—and that’s particularly true for distributed systems. If an architect thinks they’ve discovered something that isn’t a trade-off, more likely they just haven’t identified what the trade-off is yet. After all, as the first law of software architecture states: Everything in software architecture is a trade-off. While the scope of software architecture is almost impossibly broad, unifying elements do exist. But to truly understand and evaluate the significance of trade-offs in architecture, developers need a working knowledge of basic concepts and terminology concerning components, modularity, coupling, and connascence. These expert-led sessions will level up your skills and help you work through the complexity and trade-offs in your own system.

Abstract: Linux for Beginners A hands on and practical introduction of Linux This early release (ongoing) course will give you a foundational knowledge to quickly get started with Linux. You will learn practical examples packaged in easy-to-follow videos that give you just enough knowledge to use Linux. There is a strong focus on using the terminal exclusively for this course, which is the best way to ensure a wide variety of Linux environments can be used with almost no difference in concepts. The course will not cover deep Linux internals or advanced usage. It will also not go through specialized scenarios that are meant to pass a Linux certification. Learn objectives Use a terminal to navigate the file system Understand different Linux versions and use readily available versions without installing Linux Use a shell with common features Create and edit files using a terminal text editor Manage system processes and services Install and remove packages 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: Microservices--an approach to distributed systems that promotes the use of finely grained services that can be changed, deployed, and released independently--have reached a level of maturity within the software development ecosystem. (And tools and engineering practices have evolved in tandem to make distributed development easier.) Microservices work incredibly well for organizations that are moving toward more loosely coupled systems, with autonomous teams delivering user-facing functionality. Beyond this, microservices provide a huge number of options for building out systems, giving you the flexibility to ensure your system can change to meet the needs of your users. But while microservices simplify business logic, they bring increased complexity (even for experienced developers), in areas like networking, security, communication styles, team structure, and more. Join us for expert-led sessions that will demystify this complexity, covering the tools, patterns, techniques, engineering practices, and other pieces that will allow microservices development teams to rocket to the next level. What you'll learn and how you can apply it Understand how observability can help keep your microservices running smoothly Explore contract-driven development and learn how it can help you identify compatibility issues earlier in the development lifecycle Discover how Twitch moved from a monolith to microservices This recording of a live event is for you because... You're a software architect or developer working on or thinking about working on a microservices-style architecture and want to learn best practices for deploying microservices. You want to effectively leverage the benefits microservices bring. Recommended follow-up: Listen to Microservices Patterns (audiobook) or read the book Read Building Microservices, second edition (book) Watch The Principles of Microservices (video) Please note that slides or supplemental materials are not available for download from this recording. Resources are only provided at the time of the live event.

Abstract: Introduction to MLflow for MLOps Learn how to use MLflow for managing the machine learning lifecycle. Track experiments, package models, and deploy to production. In this course you'll learn how to use MLflow - an open source platform for managing the machine learning lifecycle. You'll learn how to: Install MLflow and explore its components like the UI, tracking, and model packaging Log metrics, parameters, and artifacts to track ML experiments Create reproducible ML projects with MLflow for repeatable model training Package models and dependencies for deployment and serving Use model registries to version, stage, and deploy models Deploy models to tools like Azure ML and SageMaker This course includes hands-on exercises, projects, and real-world examples so you can apply your new MLflow skills immediately. Use the reference repository for MLFlow examples and projects: Example MLFlow Projects Learning objectives Install and configure MLflow Use the tracking UI and APIs Log metrics, parameters, tags, and artifacts Create reproducible ML projects Version, stage, and deploy models with registries Deploy models to Azure ML, SageMaker, etc Lesson 1: Introduction to MLflow Lesson Outline Overview of MLflow components Installation and configuration Tracking experiments with UI, Python, R APIs Logging metrics, params, tags, artifacts Lesson 2: MLflow Projects Lesson Outline Motivation for reproducible ML projects Creating project directories Running projects locally or on Git Customizing execution environments Lesson 3: MLflow Models Lesson Outline Packaging models and dependencies Model versioning with registries Staging and promoting model stages Deploying models to services 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 work with MLFlow and apply it to MLOps tasks. Resources Pytest Master Class Practical MLOps book.

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: 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: 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: 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: About Architectural Katas: What could be better than practicing software architecture with your handpicked dream team of architects? Participants in Architectural Katas, moderated by Neal Ford, work together in small groups of their choosing to solve a challenge an actual organization is facing. Everyone gets the chance to practice their craft with a real software architecture problem in a safe and social environment, and the finalists and winners earn well-deserved bragging rights (not to mention an intriguing line on their résumé). Plus a selected organization will have some of its gnarliest software architecture problems solved. How it works: You put together a first-rate team of three to five people, ready to tackle an architecture challenge. We'll share the architecture problem with you at the kickoff. Then your team will have to solve it, working in whatever way is best for you (video calls, group chat, shared docs, etc.). Teams will submit their solutions and reconvene at the semifinals to find out which will move on to the finals. At the finals, the teams will submit video presentations and the audience will vote on the winner. Series schedule: Event 1: Kickoff - October 19, 2023 Meet the judges, hear all the details on how Architectural Katas works, learn more about the software architecture problem you'll be solving, and get the chance to ask Neal any questions you may have. Event 2: Semifinals and Architectural Presentation - November 14, 2023 Get a master class on presentation skills and learn how to successfully showcase software architecture plans to developers and stakeholders (and judges). You'll also find out the top teams that will submit their video presentations for the final event. Event 3: Finals - December 4, 2023 The top teams' videos are shown, judges provide feedback, attendees vote for their favorite, and judges announce the winner. What you'll learn: Identify and design architectural components Explore techniques to analyze and select the right architecture patterns Learn how to diagram and document an architectural solution Develop better communication skills to champion architecture decisions to developers and stakeholders This event is for you if... You're a senior-level developer who wants to make the move to architect. You're a practicing software architect who wants to hone your skills and learn new software architecture techniques and practices. You're responsible for creating a software architecture for your company, and you want to practice with a real-world challenge. Recommended follow-up: Read Fundamentals of Software Architecture (book) Read Building Microservices, second edition (book) Read Building Evolutionary Architectures (book) Read Building Event-Driven Microservices (book).

Abstract: Join us for a special conversation with Neal Ford and Chris Richardson, an experienced software architect, creator of the original CloudFoundry.com, and the author of POJOs in Action and Microservices Patterns. They'll discuss the concerns that you must consider when deciding between monolithic and microservice architectural styles, then they'll dive into how well each architectural style resolves these forces and how to evaluate the relative importance to your application of each of these forces. What you'll learn and how you can apply it Understand how to decide between monolithic and microservice architectural styles See what's coming next with software architecture This recording of a live event is for you because... You want the chance to hear from Neal Ford and Chris Richardson about microservices and software architecture and what the future might look like. You're looking for ways to grow your own skills and to act as an innovator in your organization. Recommended follow-up: Read Microservices Patterns (book) Listen to Microservices Patterns (audiobook) Read Monolith to Microservices (book) Read Building Microservices, second edition (book) Attend Microservices in 3 Weeks (live event) Watch Software Architecture Superstream: Microservices (live Superstream event recording).

Abstract: DevOps command-line tools in Python and Rust Use both Python and Rust to automate systems engineering tasks In this introductory course, you will learn how to build powerful command-line tools using Python and Rust. You will discover how to set up a development environment, incorporate user input, expand functionality using modules and libraries, and optimize performance for common DevOps and Systems Engineering tasks. Whether you're new to programming or an experienced developer, this course will teach you the fundamentals of building command-line tools using Python and Rust. By the end of the course, you'll have the skills to automate tasks and improve the efficiency of your DevOps and Systems Engineering workflows. This course includes GitHub repositories that you can use as a reference for all the learning content: Python CLI Examples Rust CLI Examples Learn objectives Set up a development environment for building command-line tools. Build basic command-line tools. Expand the functionality of command-line tools using modules and libraries. Create a simple command-line tool using Rust and understand the basic structure of a Rust-based CLI tool. Incorporate user input, such as arguments and options. Learn how to organize code into modules and packages, and work with dependencies and libraries in both Python and 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. 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: Join us for a special conversation with Neal Ford and Thoughtworks tech principal Andrew Harmel-Law about how the definition of an "effective" software architect is changing in response to the rise of modern decoupled systems. Architects, and traditional architectural approaches, must evolve to meet the challenges of increasingly autonomous, independent, and self-managing development teams. You can avoid creating the bottleneck for architecture decisions when you're working with all those teams. Andrew will outline the architecture advice process, which enables anyone working in a system to make an architecture decision--but only after talking to the people who have expertise as well as the people who'll be impacted by the decision. This is a chance for you to hear from Neal and Andrew about software, architecture, and their own career journeys. They'll spend a few minutes covering the trends that are influencing architecture, then tell you what you need to know to stay ahead of the curve. What you'll learn and how you can apply it How to craft technical strategy and make sure it's aligned to business needs See what's coming next with software architecture This recording of a live event is for you because... You want the chance to hear from Neal Ford and Andrew Harmel-Law about software design, extreme programming, and what the future might look like. You are currently looking for ways to grow your own skills and to act as an innovator in your organization. Recommended follow-up: Read Software Architecture: The Hard Parts (book) Listen to The Software Architect Elevator (audiobook) Read Building Evolutionary Architectures, second edition (book) Read Software Architecture Metrics (book).

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: 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: Sponsored by Cockroach Labs Domain-driven design and event-driven architecture are inherently flexible and scalable, allowing organizations to build systems based on actual usage and needs. Well-built event-driven architectures maximize your system's responsiveness, performance, scalability, and elasticity, while domain-driven design helps you collaborate with domain experts, tapping into their existing mental models and consequently building deep insight into the problems you're trying to solve. Unfortunately, with all this power comes a fair amount of complexity--building an event-driven architecture and fully grokking domain-driven design are both really hard. But this event can help. Whether you're examining the viability of these concepts or trying to make the most of an ongoing implementation, these sessions offer expert guidance on maximizing their value to your organization. What you'll learn and how you can apply it Understand how to design, build, and evolve adaptive systems and team structures for a fast flow of change Learn what the future holds for event-driven architecture This live course is for you because... You're a software architect or developer working on or thinking about working on event-driven architectures and want to learn best practices. You want to learn more about domain-driven design (DDD) and the collaboration between developers and domain experts to ensure the right thing is built. Recommended follow-up: Read Learning Domain-Driven Design (book) Read Building Event-Driven Microservices (book) Watch Domain-Driven Design Distilled (video course).

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: 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: Join us for a special conversation on software engineering with Neal Ford and Grady Booch, IBM’s chief scientist for software engineering and coauthor of the Unified Modeling Language. They’ll discuss what the future holds and how that future relies on software that has yet to be written. You’ll discover why the story of computing is the story of our own humanity and explore what it means to be human in the face of a technology that can amplify us, diminish us, and most certainly will coevolve with us. Neal and Grady also talk about software, architecture, and their own career journeys. They’ll spend a few minutes covering the trends that are influencing architecture, then tell you what you need to know to stay ahead of the curve.

Abstract: This introductory lesson will walk you through everything you need to know to quickly get started with Azure ML Studio using AutoML. After creating the necessary resources, you'll walk through the steps needed to create a regression job using a dataset. Next you'll create a compute cluster and review the different options available and finally, you'll analyze the results after the best model is selected.

Abstract: This video series covers live coding with TensorFlow and the Rust language.

Abstract: Join us for a special conversation with Neal Ford and Kent Beck, programmer, creator of Extreme Programming, pioneer of software patterns, coauthor of JUnit, rediscoverer of test-driven development, and signer of the Agile Manifesto. They'll discuss how software design is an exercise in human relations, then get into the work Kent is doing to empower geeks everywhere to improve software design, starting with making small changes to code (tidyings) before moving into changes that improve the larger design. Along the way, they'll dive into the theory behind software design (coupling, cohesion, discounted cash flows, and optionality). This is a chance for you to hear from Neal and Kent about software, architecture, and their own career journeys. They'll spend a few minutes covering the trends that are influencing architecture, then tell you what you need to know to stay ahead of the curve. What you'll learn and how you can apply it Learn how to craft technical strategy and make sure it's aligned to business needs See what's coming next with software architecture This recording of a live event is for you because... You want the chance to hear from Neal Ford and Kent Beck about software design, Extreme Programming, and what the future might look like. You're looking for ways to grow your own skills and to act as an innovator in your organization. Recommended follow-up: Read Extreme Programming Explained, second edition (book) Read Test-Driven Development by Example (book) Read Implementation Patterns (book).

Abstract: Professional Data Engineer Certification Course Section 1: Designing Data Processing Systems 1.1 Storage technology selection 1.2 Data pipeline design 1.3 Data processing solution design 1.4 Data warehousing & processing migration Section 2: Building & Operationalizing Data Processing Systems 2.1 Storage system implementation 2.2 Pipeline building & operationalization 2.3 Processing infrastructure implementation Section 3: Operationalizing ML Models 3.1 Pre-built ML models as a service 3.2 ML pipeline deployment 3.3 Training & serving infrastructure selection 3.4 ML model measurement, monitoring & troubleshooting Section 4: Ensuring Solution Quality 4.1 Security & compliance design 4.2 Scalability & efficiency assurance 4.3 Reliability & fidelity assurance 4.4 Flexibility & portability assurance Learning Objectives Learn to design, build, and operationalize data processing systems that meet business requirements, system requirements, and industry best practices. Learning to build scalable, efficient, and secure solutions with Google Cloud technologies to manage and analyze data at scale. Learning the key syntax and features of the SQL language for handling, querying, and performing operations on structured data in Google Cloud. 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: 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: Join us for a special conversation with Neal Ford and Gayathri Thiyagarajan, where they will discuss practical application of Data Mesh to improve data quality and some of the challenges that come from implementing it at scale as well as the opportunities it provides. They'll dive into a practical discussion of Data Mesh based on implementing Data Quality at scale and what steps are needed to ensure end users are receiving reliable data. This is a chance for you to hear from Neal and Gayathri about software, architecture, and their own career journeys. They will spend a few minutes covering the trends that are influencing architecture and then tell you what you need to know to stay ahead of the curve. What you'll learn and how you can apply it Understand data mesh and how it might fit into your organization. See what's coming next with software architecture. This live course is for you because... You want the chance to hear from Neal Ford and Gayathri Thiyagarajan about methodologies for improving your software architecture. You're looking for ways to grow your own skills and act as an innovator in your organization. Recommended follow-up: Read Data Mesh (book) Read Software Architecture: The Hard Parts (book).

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: 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: What is the if __name__ condition in Python for? If you've seen __main__ at the end of a Python script and wondered why that is there it is to avoid side effects when importing and allowing you to run the file as a script on the terminal. If you want more details, watch this short video where we work with a Python script to find out those side effects and how the Python script can change once the if condition with __name__ is done at the end. Next Steps Now that you know about the conditional at the end, you might want to explore writing Python scripts that use this trick. There are several examples you can follow in these GitHub repositories with argparse, the Click framework and using sys.argv: argparse GitHub repo examples sys.argv GitHub repo examples Build Python applications from scratch.

Abstract: Learn to use K-Means clustering from theory to implementation 00:00 Intro 00:47 Theory of Machine Learning 05:00 Colab Notebook exploration of K-Means Algorithm 06:00 Distance Metrics 08:00 Creating K-Means Pipeline 12:00 Elbow Plots 14:00 Silhouette Plots 17:00 Running K-Means Serial Simulation 18:34 Running K-Means Parallel Simulation 20:00 Spinning up Huge Cloud9 128 GB Ram 32 vCPU Instance 23:00 Running massively parallel K-Means.

Abstract: Join us for a special conversation with Neal Ford and Java pro Brian Goetz, where they'll discuss Java's vibrancy and the future of the platform. They'll cover some of the latest updates to the Java language and platform and dig into some fascinating research on embedding abstractions and its impact on software architecture. They'll also spend a few minutes covering the trends in Java that are influencing architecture, then tell you what you need to know to stay ahead of the curve. What you'll learn and how you can apply it Explore some of the latest updates to Java See what's coming next with software architecture This recording of a live event is for you because... You want to learn about how to work better with Java. You're looking for ways to improve your architecture. Recommended follow-up: Read Java Concurrency in Practice (book) Read Building Microservices, second edition (book) Read Fundamentals of Software Architecture (book) or listen to the audiobook Read Software Architecture: The Hard Parts (book) Read 97 Things Every Java Programmer Should Know (book) Watch Brian Goetz, Stuart Marks, and Nicolai Parlog: Ask the Java Architects--Java 17 and Beyond (video).

Abstract: Learn to build cloud pipelines with AWS Step Functions 00:00 Intro 01:00 Create AWS Lambda function in Python 04:00 Create return statement that returns JSON depending on type of event 05:49 Test the AWS Lambda function 08:00 Build a second AWS Lambda function that can parse first function 13:00 Create AWS Step Function that consumes both AWS Lambda functions for Pipeline.

Abstract: Java Fundamentals is a comprehensive video course introducing the core elements of Java programming. In over 14 hours of professionally produced video, along with ample opportunities to try out what you’re learning, you’ll master the essentials in a friendly, easy-to-understand way. You’ll not only dig into the syntax and structure of the Java language, but also build up good habits and practices as you work with the many hands-on examples. As you progress from section to section, you’ll incrementally build a fully functioning application by adding and refining features.

Abstract: Learn how to use Python dictionaries to store and retrieve data. Although dictionaries look complex with different ways to represent, retrieve, and store data, they can be straightforward to use. In this course I'll show you how to create, store, retrieve, and loop over dictionaries. Once you go through these different actions, you should be able to choose the right approach to work effectively with dictionaries. If you are already familiar with Python lists and you are ready to take the next step with dictionaries, then this course is for you.

Abstract: Learn to provision EC2 instances from both the AWS Console and AWS CloudShell. Also learn the key components of EC2 instance provisioning. 00:00 Intro 00:45 EC2 Instance Provisioning Key Component Diagram Walkthrough 03:18 Launching an EC2 Instance from AWS Console 04:06 Creating SSH key pair 04:46 Configuring Security Group rules 05:21 Walkthrough of Advanced Setting including User Data 06:33 Observing EC2 Instance State in Console 07:07 Using AWS CloudShell to launch and controll EC2 Instances 07:44 Finding AMI IDs to launch EC2 Instances from AMI Catalog 08:00 Launching EC2 Instances from AMI Catalog with AWS CloudShell 08:52 Connecting to EC2 Instances from AWS Console and logging into Linux shell 09:40 Walkthrough of EC2 Instance Connection options for Windows with RDP 10:56 Terminating Instances with AWS CloudShell and Bash AWS CLI 11:50 Recap of EC2 Instance Provisioning.

Abstract: GitHub Codespaces and custom dotfiles Add your dotfiles to any Codespace automatically Customize any GitHub Codespace you create or use by automatically getting your dotfiles in there with no effort! You only need a GitHub repository that contains your dotfiles to get this feature enabled in any Codespace you work on You also have the ability to have a setup.sh script that you can use to further customize how GitHub will add your dotfiles to your Codespace at creation time. Learning Objectives In this lesson you will learn: Configure a GitHub Codespace with dotfiles Create a repository with your own dotfiles Additional features you can try with dotfiles in Codespaces Useful Resources Dotfiles and Codespaces documentation Free Azure Certification for Students Introduction to GitHub Actions Run Python In GitHub Actions.

Abstract: Automated deletion of Azure Resources Prevent surprise bills with automation Prevent your Azure bill from running wild! In this video I show how you can automate the removal of Azure resources on demand or by schedule. With GitHub Actions and an Azure account you can prevent services from running wild and causing unnecessary billing overcharges! With automation in place, there is no need to remember what VM you left running! First, you'll start by creating a GitHub Action that authenticates to Azure, then you will query locally your resource groups to identify which ones you can delete. Next, you will port the query over to the Action workflow. Finally, you will delete resources that match, making sure those are fully removed, preventing a large bill. You will need a GitHub and Azure account, an Azure Service Principal and the Azure CLI installed locally. Learning Objectives In this lesson you will learn: Create a GitHub Action workflow to query Resource Groups Query Resource Groups that match locally Use scripting to extract Resource Group names Remove Resource Groups with the Azure CLI in GitHub Actions Useful Resources Sample GitHub repository Create an Azure Service Principal for GitHub Actions Azure Service Principal documentation Install Azure CLI Free Azure Certification for Students Introduction to GitHub Actions Run Python In GitHub Actions.

Abstract: Learn to use Hugo a popular Go-based content management system to deploy global-scale websites on AWS. 00:00 Intro 00:53 The need to spread information that helps humans at scale 02:26 Hugo Continuous Delivery with AWS CodeBuild workflow diagram 06:04 AWS CodeBuild 06:38 AWS Cloud9 07:56 Download Hugo and run it locally 09:40 Follow Hugo's Quickstart guide 11:36 Edit inbound rules for Cloud9 to preview running Hugo website 13:10 Looking at the buildspec.yml file for continuous delivery of Hugo website with AWS S3 and Cloudfront and Route 53 14:52 Walkthrough of AWS S3 static hosting 15:45 Walkthrough of AWS CodeBuild continuous delivery for Hugo console settings.

Abstract: Learn to master the Databricks platform for doing MLOps.

Abstract: VSCode development environments Learn different options for programming with VSCode Find out different ways you can use VSCode for development: on the web, with Codespaces or locally with configurable Docker containers This video will cover what makes each one different and when you might want to use one vs. the other. From quick edits on GitHub to a more powerful machine backed by a remote compute using Codespaces, it is all about flexibility! Topics Covered Include: Use quick edits with GitHub.dev that show on your repository Open any repository with VSCode.dev Use Codespaces with a powerful remote compute Configure a local codespace with Devcontainers using Docker Additional 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.

Abstract: Intro to Pandas Over 1 hour of course material with practice code Quickly learn to use Pandas with examples Learn how to work with data using Pandas and NumPy. From loading and reading datasets from different sources to plotting graphs and exploring common problems in data. Pandas will allow you to perform transformations and export your data into different formats, and NumPy will boost your ability to work with numerical data. This course is meant for beginners that want to understand Pandas from the start and find more about NumPy. All lessons and videos have accompanying GitHub Repositories with example code. Reference GitHub Repository Learning Objectives In this course you will learn to: Load and export data from different sources Manipulate data in datasets Apply functions and transform columns Query for specific data Perform common operations on NumPy arrays Resources Python for beginners course Python Functions and Classes course Python Dictionaries course Introduction to Testing in Python course Pytest Master Class Python Bootcamp for Data Practical MLOps book.

Abstract: 52 Weeks of Rust Learning Rust by Live Coding This video series live codes Rust and iteratively learns the language. Lessons Covered Include: 1.0 52 weeks rust ep 1 getting started setup env 2.0 52 weeks rust ep 2 starting scripts 3.0 52 weeks rust ep 3 functions 4.0 52 weeks rust ep 4 loops 5.0 52 weeks rust ep 5 ownership more looping Learning Objectives Learn Rust by Live Coding 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: Iteratively Build NLP Tools and FastAPI Microservice on AWS From Zero From Zero to NLP Hero This video will show you how to use CUDA GPUs with Python. Lessons Covered Include: 1.0 Introduction to Course 1.1 Introduction to Python Statements with Colab, IPython and GitHub CodeSpaces 2.0 Introduction to Python functions from simple to complex with Closure, and Decorators 3.0 Build a simple NLP Tool with TextBlob, Wikipedia and Python Fire command-line tool 4.0 Build an end-to-end NLP Microservice with FastAPI, ECR and AWS App Runner. Learning Objectives Learn key software engineering principles and best practices for building software. Learn to build NLP tools using TextBlob and Wikipedia. Learn to build a FastAPI containerized Microservice deployed via Amazon ECR and AWS App Runner. 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: Doing Hugging Face Building Solutions with Hugging Face This video course will show you how to build solutions with Hugging Face. Topics Covered Include: 1.0 Introduction to Course 1.1 Learn to use MLOPs methodology to deploy a Hugging Face Spaces application using Github Actions. Learning Objectives Build applications with Hugging Face Apply MLOPs methodology to deploy a Hugging Face Spaces application using Github Actions. 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 WT.mc_id=academic-0000-alfredodeza) Practical MLOps book Python for DevOps-Playlist.

Abstract: How is long-term planning possible when everything changes all the time--and how do you address the unfortunate fact that architectures often gradually degrade? Evolutionary architectures support the building of systems that allow architects and developers to make sweeping changes to the most important parts with confidence. Join us for a special conversation on evolutionary architectures with Neal Ford and Thoughtworks CTO Rebecca Parsons. They'll discuss how their ideas around evolutionary architectures have evolved since the publication of their 2017 book Building Evolutionary Architectures (cowritten with Patrick Kua). Learn practices that allow developers to build continual architectures, which evolve cleanly without the need for a crystal ball. This is a chance for you to learn about architecture and Neal and Rebecca's own career journeys. They'll spend a few minutes covering the trends that are influencing architecture, then tell you what you need to know to stay ahead of the curve. What you'll learn and how you can apply it Understand what evolutionary architectures are and how to implement them See what's coming next with software architecture This live event is for you because... You want to learn more about building and maintaining evolutionary architectures. You're looking for ways to improve your architecture. Recommended follow-up: Read Building Evolutionary Architectures (book) Read Software Architecture Metrics (book) Read Fundamentals of Software Architecture (book) Read Software Architecture: The Hard Parts (book) Explore Evolutionary Architectures Fundamentals (course) Attend Software Architecture Superstream: Architecture Meets Data (live online event on November 30, 2022).

Abstract: Introduction to Azure Functions Create a function with Python and Flask Learn how to create an Azure Function in the fastest way using instant deployment with Visual Studio Code, and then find out how to take it to the next level by using the Flask framework to take advantage of common Python patterns you might already be used to. Finally, we'll go through automation steps using GitHub Actions so that you can re-deploy your Azure Function after merging changes. This will give you confidence for deployment, make it less error-prone, and give you a foundational workflow to implement serverless technology using the Azure cloud. Learning Objectives Create an Azure Function using the Azure Portal Quickly build a function using Visual Studio Code Deploy in one click with the Azure Functions extension Modify your code and routes to use Flask Use GitHub Actions for automating the deployment process 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 creating courses with Codespaces is seen throughout this course, where you will get a first-hand experience with practical examples as well as applicable configuration for any development environment. Resources GitHub Codespaces course Microsoft Azure Fundamentals (AZ-900) Certification Pytest Master Class Practical MLOps book.

Abstract: Assimilate AWS with Python Master AWS by Coding with Python in this ongoing series This video series covers mastering AWS in Python from the absolute beginning with incremental weekly lessons. Follow along for a deep dive into programmatically mastering AWS with Python. 1.0 Assimilate AWS by using Github Copilot and Github Codespaces to build solutions for S3, Apigateway and Click. 2.0 refactor boto3 code build translation click tool Assimilate AWS By Coding 3.0 Assimilate AWS By Coding EP3 Bash CloudEnvs Containers: Use Bash to build CloudEnvs and Containers Topics Covered Include: Python Basics Github Repo for Assimilate AWS 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: Assimilate F Learning Fsharp During Live Coding This video series covers live coding the Fsharp Language iteratively thus learning the language. Lessons Covered Include: 1.0 Setup Fsharp in Visual Studio Code and GitHub Codespaces and build interactive Fsharp scripts and projects Learning Objectives Learn Fsharp Learning to build solutions with Fsharp Learning the key syntax and features of the FsharpLanguage 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: Sponsored by HASURA With an eye to the future, many organizations have made the move to microservices as a means of decomposing monolithic legacy systems. But what does a distributed system mean for delivering data? Join us to discover how understanding the intersection of software architecture and data can help you achieve new levels of velocity, agility, reliability, and efficiency. If you're looking for ways to manage data as a software architect or developer, these sessions will help you learn what's involved so you can chart a course toward a successful solution. About the sponsor: Hasura is a GraphQL API engine that gives you instant GraphQL APIs on all your databases, speeding up development time and making your engineering teams super productive. What you'll learn and how you can apply it Understand how to use current technologies to implement systems in a more customer-centric way Learn how to apply best practices for software to your data Discover which software architecture issues you should consider when adopting and designing systems based on the NoSQL and distributed SQL databases This recording of a live event is for you because... You're a senior-level developer who wants to make the move to architect. You're a practicing software architect who wants to hone your skills and learn new software architecture techniques and practices. You want to better understand how to solve the unique problems of integrating data into your architecture. Recommended follow-up: Listen to Fundamentals of Software Architecture (audiobook) or read the book Read Software Architecture: The Hard Parts (book) Read Data Mesh (book) Read Foundations of Scalable Systems (book) Take Event-Driven Architecture and Data (live online training course with Adam Bellemare) Please note that slides or supplemental materials are not available for download from this recording. Resources are only provided at the time of the live event.

Abstract: Azure PostgreSQL Setup and deploy an Azure PostgreSQL database Learn how to setup a PostgreSQL database using the Azure cloud. From the different options you have to create a PostgreSQL database (flexible or single server) to connection strings and firewall settings. This video will walk you through all you need to know to setup the resources, understand the constraints, and then correctly connect from a remote workstation using psql . Learning Objectives In this video you will learn to: Use the Azure Portal to create a PostgreSQL database Select between single and flexible server options Understand the constraints to create a database Setup firewall settings for external access Use psql to connect from a remote workstation to PostgreSQL Use the default database to connect Resources Azure Fundamentals Certification Azure Fundamentals quick reference guide Azure remote compute for VSCode Automated Azure resource cleanup Learn Azure ML (AutoML) in One hour.

Abstract: Assimilate PyTorch Learning PyTorch During Live Coding This video series covers live coding the PyTorch Language iteratively while learning the language. Lessons Covered Include: 1.0 Getting started with PyTorch in GitHub Codespaces with GPU (Live Coding) Learning Objectives Learn PyTorch Learning to build solutions with PyTorch Learning the key syntax and features of the PyTorch Framework 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.