Abstract: Dirty data is everywhere. Have you had a letter addressed to you with your name misspelled? That's dirty data. Do you have trouble finding a product on a website because it's not in the right category? That's dirty data. Do you have trouble finding a person or company name in your system because of a typo? That's dirty data. And it causes problems, lots of problems. Before software implementation, machine learning and AI, you need clean data. It's THE most important thing to fix before doing any of these things, and we're all expected to be able to clean or fix this data, yet no one tells us how to do it! Some of the most common data problems occur in name, address, email and phone number data, and this course will cover this off. While there are many data-cleaning tools out there, almost everyone uses Excel, including non-data professionals, and it's important to have the skills to be familiar with and be able to get to know your data before you use these tools. It's essential to be able to spot and fix errors in Excel first, and understand when the data isn't right so you know if you can trust those fancy tools or not! This course will help you achieve this and you'll learn: What is dirty data? The importance of data quality Tips for cleaning data in Excel How to clean names, addresses, emails and phone numbers in Excel You'll even get your own dirty data set to work on! This course is for you because... You have data quality issues in your organization and would like your team to understand the importance of data quality and how to improve it. You're a data professional spending a significant amount of time cleaning data and would like to work more efficiently. You're not a data professional, but work with data and want to work more efficiently with it. Prerequisites: Some experience of Excel would be beneficial.

Abstract: Software development is increasingly central to a business’s identity. But as the complexity of the practice grows, the demand is high for developers who operate at a senior level. And the rise in generative AI tools means that even expert developers must recalibrate how they work to keep up with the pace of development. Join us to level up your skills and accelerate your journey to senior software engineer. These in-depth sessions cover some of the biggest challenges facing software developers today, teaching you practical methods and best practices to improve coding and software design, better manage data, mentor new engineers, and collaborate with your team.

Abstract: Join host George Anadiotis and guest Eric Xing, for a discussion about the current and expanding field of open-source large language models and how they are impacting the development of generative AI. We’ll cover technical aspects, as well as the business and policy concerns related to open-source LLMs.

Abstract: In an ideal world, usability testing might be considered exclusively the job responsibility of UX designers or researchers. However, for many of us and for various reasons, that just isn’t a reality. No matter what the situation is, running basic usability tests is something everyone is completely capable of—and it comes with the bonus of making us better at our own jobs, as well, by better understanding our users. In this course, we’ll discuss finding participants, thinking through the testing logistics, writing and facilitating a usability test, and reviewing the data. Each learner will get the chance to write a usability testing script for a feature in their own website or application that they’d like to test. Then, they’ll be challenged to practice usability tests with those scripts to get hands-on experience facilitating tests. Learners will leave this course feeling empowered and confident to start a usability testing program at their own workplace!

Abstract: With engineering leaders under increasing pressure to quantify engineering performance, there’s no shortage of opinions or frameworks suggesting which engineering metrics matter most. Join Peter Bell, CTO of Rare Talent, and guests for a discussion about how to select the metrics that matter for your organization’s success. Through this expert panel discussion, you’ll learn why selecting engineering metrics is so challenging, what considerations and trade-offs should be taken into account, the problems with commonly used metrics, and how to have more productive conversations about how metrics relate to executives’ key business goals. CTO Hour is a quarterly live event that brings together a panel of senior engineering leaders to discuss with expert and host Peter Bell how they’ve approached timely technology or business challenges. This dynamic event features ample time for questions. Active and aspiring senior leaders will learn valuable insights from top VPs and CTOs and ultimately be prepared to make better-informed decisions as heads of technology.

Abstract: Advancing in a large organization requires more than just being good at your job. Many of these skills and practices are not obvious and seldom taught. In teaching some of these practices, this course will help you learn how to better manage your time and relationships, find space to innovate, and take advantage of all the perks and benefits of working at a large company, so that you can not only survive but also thrive in your role. What you'll learn and how to apply it By the end of this course, you will have new tools and ways of thinking that will improve your daily outlook, give you more opportunities to advance, and avoid overwork at a large organization. This course is for you because You're new to working at a large company and want some tactics and practices to avoid making mistakes and having an unpleasant worklife. You want to become better at managing relationships and using your time wisely. You want to work on advancing your career and effectiveness at work. Prerequisites You're working in a large company Your job is focused on how the organization runs, either by helping management, being a manager, or aspiring to one of those roles.

Abstract: Join Michael Lopp and Tara Hernandez as they delve into developer productivity--what it is, why it's often misunderstood, and why it's such a hot topic right now. This event is for aspiring and active leaders who want to ensure that their teams are meeting their goals, have the tools they need to do their best work, and are able to communicate the value of their work to non-technical leadership. Viewers will gain insight into recent debates about measuring developer productivity, what qualitative and quantitative data shed the greatest light on productivity, and what steps they can take to foster an organizational culture that looks holistically at developer experience. Tech Leadership Tuesday is a dynamic monthly live event that helps empower people and technology leaders to become more effective and successful in their leadership roles. Each episode delves into a relevant topic for engineering leaders and, through a conversation between a host and guest, you'll learn about common challenges, best practices, and lessons learned from the guest's experience. What you'll learn and how you can apply it What's driving recent debates about developer productivity The role that developer productivity plays in engineering culture The business value of focusing on developer productivity and how you can measure ROI This live course is for you because... You want the chance to hear from Michael Lopp and Tara Hernandez about leadership and developer productivity. You're a leader and you want to learn to think more holistically about how to empower developers and deliver software faster. Recommended follow-up: Read Rethinking Productivity in Software Engineering (book) Read Efficiency vs. Effectiveness vs. Productivity (Chapter 2 from Leading Effective Engineering Teams) 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: 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: Build A Data Strategy to Create Iron-Clad Profit Performance is an online course and toolkit for data professionals who want to get unstuck and up-leveled into their next promotion by delivering fail-proof data strategy plans for their data projects. Learners need to have some degree of mastery with respect to data technologies and skill sets. They don’t need to know how to build every type of data / data science / data engineering solution under the sun, but they should have a firm understanding of at least data analytics, data science, data management or data engineering.

Abstract: Artificial intelligence promises to augment human capabilities, revolutionize scientific research, personalize consumer experiences, transform education, and usher in an era of autonomous transportation. But companies should understand the risks along with the potential. Implementing AI without clear use cases or business goals can lead to wasted resources, and a lack of expertise or attention to ethical considerations can bring powerful consequences. Join our experts to explore how AI is changing technology and business. You'll learn how to harness its transformative potential while avoiding common missteps and discover how to best use AI as a tool for progress rather than a stumbling block. What you'll learn and how you can apply it Apply AI in the right situations and avoid costly mistakes by expecting too much from a developing tech Program macros and scripts with no coding experience using ChatGPT Discover the progress being made with autonomous vehicles and the pitfalls they face This Superstream recording is for you because... You're an ML engineer or developer interested in safely and effectively taking advantage of recent advances in AI while avoiding potential pitfalls. You want to hear about the latest and greatest of AI from experienced industry experts working in the field today. Your organization is quickly advancing into applying AI without a strong map for the potential peaks and valleys ahead. Recommended follow-up: Read Designing Machine Learning Systems (book) Watch Building AI Agents with LLMs (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: Observability is more difficult in the era of large language models, while insight into your code's behavior is increasingly more important. Join Sam Newman and Jessica Kerr for a discussion about the impact of AI on software production. They explore what happens when deterministic work (software development) meets nondeterministic work (GenAI) and examine some of the limitations of communicating with an AI at scale. This event is for anyone who builds or maintains software and is looking to better understand the intersection of GenAI and observability. What's New in Software Development gives you a chance to explore trending topics in software development and to hear from Sam and Jessica Kerr about software development, how to begin implementing AI tooling into your own work, and their own career journeys. They will spend a few minutes covering the trends that are influencing software development 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 How to start thinking about integrating GenAI into your production lifecycle How to use observability to gain insight into how your code behaves in production This live course is for you because... You want to hear from Sam Newman and Jessica Kerr about how software development is changing. Recommended Follow-Up: Read Observability Engineering (book).

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: In this course we focus on preparing you for successfully sitting for the challenging CompTIA Data Plus DA0-001 exam. Data is considered the most important asset for enterprise organizations and as a data professional you will be able to provide immediate value to data driven organizations with the Data Plus certification. CompTIA Data+ is a very challenging exam and successful passing will validate that certified professionals have the skills required to facilitate data-driven business decisions and also provide immediate value to the enterprise. Data professionals must know about data mining, data manipulation, and visualizing and reporting data to stakeholders. So, whether applying basic statistical methods or analyzing complex datasets while adhering to governance and quality standards throughout the entire data life cycle, a data professional is an important role to enterprises. This course will prepare you to prove your data science skills by successfully taking for the CompTIA Data Plus exam. What you'll learn and how you can apply it By the end of this course, you will: Understand the importance of the CompTIA Data Plus exam and its objectives. Learn how to collect, analyze, and report on various types of commonly used data. Learn about how to transform raw data into usable information for your stakeholders. Learn about database types, data structures, data schemes and other important aspects of data management. Understand how JSON data, HTML data, and XML data is used with data professionals. Understand how ETL and ELT processes work, how APIs connect us to the cloud and learn about profiling datasets. Learn about data manipulation techniques and important concepts around data transposition and normalization. Learn about descriptive statistics, inferential statistics, and various analytic techniques. Identify common analytics tools used in data analysis. Learn about the importance of Structured Query Language (SQL) and its main components. This course is for you because... You're a current or aspiring Data Engineer, Data Analyst, Data Architect, Database Manager or others IT professional interested in managing data. Prerequisites To get the most of this course it is recommended to have the following experience and/or resources: Basic hands-on SQL Database experience around relational database A computer with any version of Excel installed (if you don't already have it, you can sign up for a free 30-day trial).

Abstract: In DevOps, SRE, and operations, toil is the enemy. Fortunately, the repetitive and time-consuming manual work that drains team resources is steadily being automated. As a result, the automation tooling landscape has expanded to encompass a wide range of tasks. Whether it's testing, infrastructure configuration and management, provisioning, monitoring, or observability, there's now a tool to automate it. Evaluating and choosing among these tools is critical to the success of DevOps and SRE. Join us for in-depth sessions with leading experts to explore what it means to automate, what successful automation looks like, and how to assess the available tools and determine the right ones for your needs. What you'll learn and how you can apply it Understand how to tame your infrastructure as code using architectural patterns for infrastructure as code architecture Learn the basics of working with Terraform in production environments Explore the integration of Crossplane and Kyverno to automate cluster creation, resource configuration, compliance enforcement, add-on deployment, and security checks This live course is for you because... You're a DevOps engineer or SRE for whom understanding and implementing automation is part of the job. You're a platform engineer tasked with evaluating and implementing an automation toolchain that drives developer efficiency by reducing toil. You're a sysadmin or an operations engineer who wants to learn a more efficient, nonmanual way to build, control, and modify your infrastructure. Recommended follow-up: Read Infrastructure as Code, second edition (book) Read Terraform: Up and Running, third edition (book) Read Infrastructure as Code: Patterns and Practices (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: Performance reviews often produce a rollercoaster of emotions, reduced productivity, and increased workload and frustration for employees, managers, and HR business partners. This is because most new managers are not provided with training on how to work with their reports to identify, set, and track S.M.A.R.T. goals. Without realistic, achievable goals, filling out the requested review documents is painstaking and laborious. By the end of this course, the learner will have core goal setting skills that are brand agnostic so they can be utilized across organizations and business units. They will learn how to empower their team to define and write their own S.M.A.R.T. goals, all while ensuring full accountability. What you'll learn and how you can apply it Qualifying coaching questions to understand direct reports motivations and BHAGs Process to empower your team to define and write their S.M.A.R.T. goals Simple planning methodology Goal tracking recommendations 360 accountability (holding yourself and your direct reports accountable to achieve their goals) This course is for you because: You're a newly promoted manager looking for a process that helps facilitate goal setting and structured accountability for your team. You're a new people manager who is entering your first round of performance reviews. While you understand the company mandated deliverables, you are unsure how to structure conversations with your direct reports to complete them. You're a fairly new manager. While you have been through cycles before, your team is preparing for the next performance review cycle and you need to simplify the process. Prerequisites: Beginner knowledge of S.M.A.R.T. goals.

Abstract: Sponsored by Dremio Storing, processing, and moving data efficiently and cost-effectively in the cloud is a must for working with today's enormous datasets. These expert-led sessions deliver insight into how to increase the scalability, speed, and availability of your data and equip you with a set of best practices for utilizing your data warehouse, data lake, or data lakehouse. What you'll learn and how you can apply it Get an overview of the latest technologies for storing and managing your data Learn best practices for standardizing lakehouse data modeling and pipelining Find out how to streamline data lake implementation Explore how to securely develop and implement ML models on a cloud data warehouse Discover the benefits of data contracts in the modern data stack Understand how to enhance lakehouse infrastructure for multimodal AI This Superstream recording is for you because... You're a data or software engineer or solution architect who's interested in learning about the latest trends in storing, processing, and managing data. You want to improve the scalability, speed, and availability of your data. You want to better understand the systems that you already use and learn how to take full advantage of their capabilities. Recommended follow-up: Read Deciphering Data Architectures (early release book) Read Practical Lakehouse Architecture (early release 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: Generative AI has the potential to transform every aspect of healthcare--from personalized patient care and drug discovery to enhanced medical imaging and robot-assisted surgeries. Physicians are taking advantage of state-of-the-art tools like ChatGPT to better connect with their patients and manage medical records. Like any emerging technology, there are benefits and challenges to using AI in medicine. Join us and leading industry experts to learn more about the next-generation AI tools, techniques, and applications driving innovation in healthcare. What you'll learn and how you can apply it Uncover the benchmarks and best practices enabling academic medical centers, pharmaceuticals, and health IT companies to build real-world LLM-based applications Discover how graph databases are reshaping life sciences, catalyzing breakthroughs, and steering healthcare toward impactful, personalized outcomes Explore powerful new generative AI tools designed to enhance the search capabilities of AI models and provide highly accurate LLMs for medical Q&A and summarization Learn how to develop LangChain applications for disease diagnosis and screening Discover generative, predictive, and hybrid AI models that offer comprehensive solutions for complex medical challenges This live course is for you because... You're an AI/ML engineer or data practitioner who wants to broaden your skill set and apply your knowledge to the healthcare industry. You're a medical practitioner looking to explore the latest advancements in AI technology. You're a healthcare leader who wants to implement AI technology in your organization. Recommended follow-up: Read Prompt Engineering for Generative AI (book) Read Developing Apps with GPT-4 and ChatGPT (book) Read Low-Code AI (book) Watch ChatGPT: Possibilities and Pitfalls (video) Read AI-First Healthcare (book) Read Generative Deep Learning, second edition (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: Risk management, the process by which organizations identify, analyze, and mitigate potential threats, is a fundamental skill for any cybersecurity professional. This comprehensive course will teach you the components of risk management, the roles and responsibilities of each player, and how to put it all together to make smart business decisions. You will build the vocabulary and searching skills needed to identify the specific vulnerabilities and threats that are slowing down your mission as well as the ability to communicate about them effectively. What you'll learn and how you can apply it: Be able to apply risk management techniques to your organization Have a firm understanding of cybersecurity risk management Understand the technical risk inventory Be able to consolidate multiple risk analysis reports into a single risk management report This course is for you because: You're a cybersecurity professional. You want a solid foundation and practical skills of risk management. You're looking to move into a new role from a technologist to a cybersecurity professional with an emphasis on core skills important to cybersecurity. Risk Assessment is an adjacent knowledge base that you would like to understand better. Prerequisites: Knowledge of cybersecurity concepts and protocols Knowledge of network security methodologies CompTIA Network+ certification or equivalent knowledge Knowledge of the following: ports, protocols, services, OSI layers, routing, switching, IP addressing, wired and wireless networking infrastructure, network operations, and network troubleshooting tools.

Abstract: An increasing number of organizations are adopting data mesh due to its ability to explain and address the frustrations that many organizations experience as they try to get value from data at scale. Data mesh treats data as a product, considers domains as a primary concern, applies platform thinking to create self-serve data infrastructure, and introduces a federated computational model of data governance. This course will show you how to holistically combine the changes to the technical landscape and the operational model required for data mesh to succeed. You will explore domain ownership, data as a product, how to create a strong developer experience, and federated governance. Once you have completed the course, you will be able to understand the different elements of data mesh in practice and have the confidence to drive data mesh adoption in your company. What you'll learn and how you can apply it: Understand the intent and value behind the foundational elements of data mesh, and have the confidence to participate in a data mesh adoption. This course is for you because: You are or are interested in becoming, involved in a data mesh adoption. You have a stake in successful data use at scale-you're a machine learning practitioner, a data engineer, an engineering manager with responsibility for data or a leader of a technical organization. You are interested in problems at the intersection of business, data and collaboration. Prerequisites Either: Practical experience implementing distributed transactional systems. Practical experience implementing analytical systems. Recommended follow-up: Read Designing Data-Intensive Applications to deepen your technical understanding of data systems at scale. Read Creating a Data-Driven Organisation for a broader look at how to structure an organization to maximize value from data. Read Fundamentals of Data Observability to learn about how to automate data quality checks. Read Enterprise Data Catalog for a deep dive into the discovery part of data management.

Abstract: Many organizations are moving some or all of their on-premises network resources to the cloud, and for Microsoft shops, that often means Microsoft Azure. IT professionals who are grounded in on-premises networking need to develop their cloud management skills and prove those skills to their employers. This training explains the Microsoft Certified Azure Administrator certification; outlines the key topics of storage, identity, security, and governance; walks through demos of the activities that candidates will be expected to understand; previews what to expect in the exam; and offers tried-and-true study tips honed through years of taking and writing Microsoft courses. What you'll learn and how you can apply it In combination with the course Azure Administrator Associate (AZ-104) - Managing Compute and Networking Resources, you'll learn the fundamentals needed to pass the AZ-104 Microsoft certification course Understand the different types of Azure identities and how to administer Azure resources using the hierarchy of available structures Understand how to create, secure, and monitor storage as well as how to ensure adequate storage fault tolerance and availability Understand the various tools available for monitoring Azure resources, including analytical and logging tools This course is for you because... You are (or hope to be) an IT administrator in an organization moving to Azure. You work with virtual machines and cloud services in a Microsoft shop. You wish to become a certified Azure Administrator Associate (MC:AAA) via the Microsoft AZ-104 exam. You're a developer who wishes to understand the basic administrative context of the environment for your Azure-based apps. Prerequisites: Basic familiarity with Windows and Windows networking Basic familiarity with virtualization Basic familiarity with PowerShell.

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: 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: This is the one stop shop for all What's New in Software Development interviews of 2024 in their audio format. Keep up-to-date with Sam Newman and his colleagues on their software development journeys.

Abstract: This is the one stop shop for all of the 2024 Tech Leadership Tuesday interviews in their audio format. Keep up-to-date with Michael Lopp and his colleagues on their tech leadership journeys.

Abstract: Understanding the core concepts of LLMs is a must-have skill today. This video collection introduces the core concepts you need to know, whether you are a developer or a non-technical person. Learn the components of LLMs, such as the transformer model, context windows, parameters, tokens and more.

Abstract: Open Source Intelligence (OSINT), the gathering of information from publicly available sources, is a critical skill for defensive and offensive cybersecurity. Many professionals that use OSINT as part of their jobs lack a comprehensive and systematic view of the concepts, tools, and techniques for gathering, analyzing, and interpreting data. This course provides a structured path for learning crucial OSINT skills, including search techniques, source evaluation, social media analysis, and ethical considerations. Learners will discover how to leverage OSINT in intelligence gathering, investigations, risk assessment, and decision-making processes.

Abstract: PostgreSQL is the leading open source database for online transaction processing. It serves as the main database for many applications and services, and is a crucial component of any architecture. Knowing how to best utilize PostgreSQL has a big impact on your application. This on-demand course covers the essentials of PostgreSQL, from performing basic administrative tasks to designing a schema to keep data clean and prevent issues down the road. Through a mix of concise demonstrations and interactive assessment, you will learn how to execute queries, identify potential optimizations, and use appropriate indexes to make queries quick and efficient. What you'll learn and how to apply it Module 1: By the end of this module, the learner will be able to understand PostgreSQL core concepts and architecture. Module 2: By the end of this module, the learner will be able to perform common administrative tasks, such as creating users, tables, constraints, and indexes. Module 3: By the end of this module, the learner will be able to perform query optimizations with indexes. This course is for you because You're a developer, DBA or sysadmin You work with databases You want to specialize in PostgreSQL Prerequisites Basic knowledge of SQL.

Abstract: Understanding the core concepts of LLMs is a must-have skill today. This video collection introduces the core concepts you need to know, whether you are a developer or a non-technical person. Learn the components of LLMs, such as the transformer model, context windows, parameters, tokens and more.

Abstract: Understanding the core concepts of LLMs is a must-have skill today. This video collection introduces the core concepts you need to know, whether you are a developer or a non-technical person. Learn the components of LLMs, such as the transformer model, context windows, parameters, tokens and more.

Abstract: Understanding the core concepts of LLMs is a must-have skill today. This video collection introduces the core concepts you need to know, whether you are a developer or a non-technical person. Learn the components of LLMs, such as the transformer model, context windows, parameters, tokens and more.

Abstract: Understanding the core concepts of LLMs is a must-have skill today. This video collection introduces the core concepts you need to know, whether you are a developer or a non-technical person. Learn the components of LLMs, such as the transformer model, context windows, parameters, tokens and more.

Abstract: "This six-module course teaches product managers how to choose a product to design, create a business case, work with engineering, and bring it to market. It will train current and aspiring product managers how to perform market research, understand a product life-cycle process, and successfully define, develop, launch, and promote new products. The modules are intended for anyone with no prior product management experience who wants to work in that capacity in a tech business or startup, as well as aspiring founders who want to learn more about the product management process. What you'll learn and how you can apply it The purpose of this course is to provide a fundamental understanding of new product design and development ideas. It presents essential management concerns in new product design; cutting-edge new product ideation, design, development, and marketing approaches. The goal of the product management module is to walk through the product management life cycle, from inception to growth and launch, while taking customer feedback into consideration and implementing effective tools, processes, and determination to create a scalable product and manage it until its end of life. It covers the product life cycle, market research, competitive analysis, market and pricing strategies, product roadmaps, and the people skills necessary to effectively influence and negotiate. It will give you practical, actionable advice on how to create and capture value as a Product Manager, with a focus on the fundamental concepts that underpin successful product creation and management across industries and individual businesses. Bridging the gap between ""strategy"" and ""implementation"" Learn and implement Product Management tools Prioritize your time and pick your battles (backlog) Collect and analyze customer and market feedback Prioritize and effectively communicate needs to technical teams Manage Technology Roadmaps effectively Guarantee successful product lifecycle management while mitigating product safety risks This course is for you because... You're a product manager with 1-4 years of experience who needs to deliver a product from initiation to decline and expansion. You have basic product management life cycle knowledge, from defining product problem statements, market assessment, technology roadmap, development, and go-to market. You have previous product management experience in charge of a team of at least five developers or cross-functional engineering teams (or if you would like to lead a team of five developers or more). Prerequisites Read: Practical Product Management for Engineers by Nehal Patel, Co-author Philip Hoang (book) Complete: Professional Development by Eric Roulo (Owner Roulo Consulting Inc.) Roulo Consulting Inc - Professional Development Reading/Writing Assignment".

Abstract: Understanding the core concepts of LLMs is a must-have skill today. This video collection introduces the core concepts you need to know, whether you are a developer or a non-technical person. Learn the components of LLMs, such as the transformer model, context windows, parameters, tokens and more.

Abstract: Understanding the core concepts of LLMs is a must-have skill today. This video collection introduces the core concepts you need to know, whether you are a developer or a non-technical person. Learn the components of LLMs, such as the transformer model, context windows, parameters, tokens and more.

Abstract: Understanding the core concepts of LLMs is a must-have skill today. This video collection introduces the core concepts you need to know, whether you are a developer or a non-technical person. Learn the components of LLMs, such as the transformer model, context windows, parameters, tokens and more.

Abstract: These videos are a series of shorts explaining critical data science concepts through visuals and concise explanations. By learning these fundamentals in bite-sized format, you can digest concepts that are core in machine learning and statistical modeling. Problems like bias and spurious correlations can become easier to grasp as well. Topics include Bayes Theorem, probability distributions, mathematical notation, correlation coefficients, linear regression, and logistic regression.

Abstract: These videos are a series of shorts explaining critical data science concepts through visuals and concise explanations. By learning these fundamentals in bite-sized format, you can digest concepts that are core in machine learning and statistical modeling. Problems like bias and spurious correlations can become easier to grasp as well. Topics include Bayes Theorem, probability distributions, mathematical notation, correlation coefficients, linear regression, and logistic regression.

Abstract: These videos are a series of shorts explaining critical data science concepts through visuals and concise explanations. By learning these fundamentals in bite-sized format, you can digest concepts that are core in machine learning and statistical modeling. Problems like bias and spurious correlations can become easier to grasp as well. Topics include Bayes Theorem, probability distributions, mathematical notation, correlation coefficients, linear regression, and logistic regression.

Abstract: Understanding the core concepts of LLMs is a must-have skill today. This video collection introduces the core concepts you need to know, whether you are a developer or a non-technical person. Learn the components of LLMs, such as the transformer model, context windows, parameters, tokens and more.

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: The systems of today are exponentially more complex than the systems of 15, or even 10 years ago. There are way more moving parts and interactions to keep track of, sometimes leading to systems behaving in very unpredictable ways. In the past, Software Engineers and Site Reliability Engineers (SREs) could rely on logging and monitoring to make sense of their systems. This is no longer the case. The good news is that Observability can help. In this course, you will learn about how Observability can help SREs and Software Engineers make sense of what's going on in their systems. You will also learn about OpenTelemetry: what it is, how it supports Observability goals, how OpenTelemetry instrumentation works, and how the OpenTelemetry Collector and OpenTelemetry Operator further enhance OpenTelemetry's capabilities. You will put OpenTelemetry theory into practice with hands-on exercises which include instrumenting a Python application with OpenTelemetry, configuring the OpenTelemetry Collector, and deploying and configuring the OpenTelemetry Kubernetes Operator. Finally, you will learn what pitfalls to avoid when setting up an Observability practice, to ensure that you and your teams are positioned for success, and explore some advanced Observability use cases supported by OpenTelemetry. What you'll learn and how you can apply it Understand what Observability is, and why it is an important practice for SREs and software engineers Understand how OpenTelemetry helps to achieve Observability, and understand the basic building blocks required to instrument an application Understand the value of the OpenTelemetry Collector, and how to configure and deploy it Understand the value of the OpenTelemetry Operator, and how to configure and deploy it Quickly see OpenTelemetry in action in a complex ecosystem by running the OpenTelemetry Demo App Use OpenTelemetry to instrument a simple Python application and send traces to an Observability back-end via the OpenTelemetry Collector Understand what pitfalls to avoid in order to run a successful Observability practice Understand additional ways in which OpenTelemetry can help achieve Observability This course is for you because... You're a Site Reliability Engineer looking to improve the reliability of your systems. You're a Software Engineer looking to improve the debuggability of your code. Prerequisites: Familiarity with Linux Working knowledge of Python programming Docker fundamentals Git fundamentals Kubernetes fundamentals, including deploying applications to 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: Join host Michael Lopp, senior vice president at Apple, and his guest Will Larson, chief technology officer at Carta, as they demystify engineering strategy and discuss how these critical documents are much easier to create--and to support--than most people appreciate. You'll explore the common reasons why many organizations do not have a formal engineering strategy and learn about a proven process for creating one. This event is for you if you want to better understand engineering strategy, learn best practices for making one, or help drive and support strategy in your organization. Tech Leadership Tuesday is a dynamic monthly live event that helps empower people and technology leaders to become more effective and successful in their leadership roles. Each episode delves into a relevant topic for engineering leaders and, through a conversation between a host and guest, you'll learn about common challenges, best practices, and lessons learned from the guest's experience. What you'll learn and how you can apply it The importance of having a written engineering strategy How to create an engineering strategy What to avoid when writing an engineering strategy This live course is for you because... You want to hear from Michael Lopp and Will Larson about creating and implementing engineering strategy. You want to learn how to draft an engineering strategy. Recommended follow-up: Read The Engineering Executive's Primer (early release book by Will Larson) Read The Art of Leadership (book by Michael Lopp) Take Executive Leadership Fundamentals in 60 Minutes (on-demand course with Karen Walker).

Abstract: Join Sam Newman and Evan Bottcher for a discussion about the evolution of internal developer platforms and how to design teams that support a cohesive architecture reflected in underlying systems, features, processes, data, and APIs. Team arrangement, or topology, leads to "forces of alignment," which helps in making better technology decisions for both developers and external customers. What you'll learn and how you can apply it Explore how to make tool choices and organize workflows to optimize developer productivity Learn what constitutes an effective platform engineering team Understand the core values and objectives of successful platform engineering This live course is for you because... You want the chance to hear from Sam Newman and Evan Bottcher about how infrastructure & ops is changing. Recommended follow-up: Read Platform Engineering on Kubernetes (book) Watch Infrastructure & Ops Hour: Platform Engineering with Camille Fournier (video).

Abstract: Understanding the core concepts of LLMs is a must-have skill today. This video collection introduces the core concepts you need to know, whether you are a developer or a non-technical person. Learn the components of LLMs, such as the transformer model, context windows, parameters, tokens and more.

Abstract: In this course, you will learn to use Python for data science and gain the essential skills to analyze and visualize data effectively. Whether you are a data analyst, data scientist, business analyst, or data engineer, this course will provide you with the knowledge and tools to excel in your role. Python is a versatile language that offers powerful libraries for data manipulation, visualization, and machine learning, making it the go-to choice for data professionals. The course solves the problem of understanding and leveraging Python's capabilities for data science by providing business use cases. You will learn to use popular Python libraries such as Pandas, Matplotlib, Seaborn, and Scikit-learn to analyze and visualize data, perform statistical analysis, and build predictive models. By the end of the course, you will have a solid foundation in Python for data science and be ready to apply your skills to real-world projects. What you'll learn and how you can apply it Upon completion of this course, learners will be able to: Apply Python programming concepts for data analysis and visualization Manipulate and analyze data using Pandas Create informative and visually appealing data visualizations using Matplotlib and Seaborn Perform statistical analysis to gain insights from the data Build and evaluate machine learning models for predictive analytics This course is for you because... You're a Python beginner who wants to learn how to manage data with Python. You're a traditional data analyst who has experience with tools like Excel and Tableau, but wants to learn how to manage data with Python. You're a finance, healthcare, ecommerce, or manufacturing/logistics professional looking to become adept in Python and data science. Prerequisites No prior knowledge of Python or Data analytics is needed. All course files can be accessed in this GitHub repository.

Abstract: Product management (PM) has emerged as an exciting and highly desirable career path, offering opportunities to people with far-reaching and eclectic skill sets and backgrounds. But this very variability can make product management a particularly challenging field to enter. Do all organizations mean the same thing when they say "product manager"? Do you need to learn technical skills to become a product manager? Become an expert designer? Get an MBA? This video provides strategies for breaking into a PM role from within or outside an organization. What you'll learn and how you can apply it Understand the fast-changing landscape of product management and adjacent roles Discover how to spot the product roles that match your background and experience Learn ways to transition from a nonproduct role to a PM role in your organization Prepare for your first product management job interview This course is for you because... You're a relatively new product manager, product owner, program manager, etc. Prerequisites: Beginner knowledge of product management Recommended follow-up: Watch Product Management Fundamentals (video).

Abstract: These videos are a series of shorts explaining critical data science concepts through visuals and concise explanations. By learning these fundamentals in bite-sized format, you can digest concepts that are core in machine learning and statistical modeling. Problems like bias and spurious correlations can become easier to grasp as well. Topics include Bayes Theorem, probability distributions, mathematical notation, correlation coefficients, linear regression, and logistic regression.

Abstract: These videos are a series of shorts explaining critical data science concepts through visuals and concise explanations. By learning these fundamentals in bite-sized format, you can digest concepts that are core in machine learning and statistical modeling. Problems like bias and spurious correlations can become easier to grasp as well. Topics include Bayes Theorem, probability distributions, mathematical notation, correlation coefficients, linear regression, and logistic regression.

Abstract: These videos are a series of shorts explaining critical data science concepts through visuals and concise explanations. By learning these fundamentals in bite-sized format, you can digest concepts that are core in machine learning and statistical modeling. Problems like bias and spurious correlations can become easier to grasp as well. Topics include Bayes Theorem, probability distributions, mathematical notation, correlation coefficients, linear regression, and logistic regression.

Abstract: Understanding the core concepts of LLMs is a must-have skill today. This video collection introduces the core concepts you need to know, whether you are a developer or a non-technical person. Learn the components of LLMs, such as the transformer model, context windows, parameters, tokens and more.

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: Understanding the core concepts of LLMs is a must-have skill today. This video collection introduces the core concepts you need to know, whether you are a developer or a non-technical person. Learn the components of LLMs, such as the transformer model, context windows, parameters, tokens and more.

Abstract: Understanding the core concepts of LLMs is a must-have skill today. This video collection introduces the core concepts you need to know, whether you are a developer or a non-technical person. Learn the components of LLMs, such as the transformer model, context windows, parameters, tokens and more.

Abstract: Getting out of tech debt can feel like a Sisyphean task. After weeks of work, the success case is to have the app working the way it used to. It's not uncommon for organizations to declare code bankruptcy and rewrite working systems from the ground up. How do we end up in this situation? How do we measure it? And how do we alleviate, or even better, prevent such a situation? Join expert Chelsea Troy to explore technical debt and its impact on an organization. You'll learn how this debt builds up, how to measure it, and how to zero in on areas of greatest need--identifying high-leverage code changes and prioritizing them over renovations. You'll also explore the skills that tech teams use to prevent and reduce tech debt so you can apply them in your own organization. What you'll learn and how you can apply it: By the end of this course, you should be able to marshal you team's morass of frustration around your technical debt into an actual plan with prioritized steps to reduce and control it. This course is for you because: You're an engineer who wants to understand and reduce tech debt. You work with engineers or manage large projects and want the code to work, and keep working, without burning out the team. Prerequisites: Experience leading technical teams or working with a code base that's becoming hard to maintain (useful but not required).

Abstract: These videos are a series of shorts explaining critical data science concepts through visuals and concise explanations. By learning these fundamentals in bite-sized format, you can digest concepts that are core in machine learning and statistical modeling. Problems like bias and spurious correlations can become easier to grasp as well. Topics include Bayes Theorem, probability distributions, mathematical notation, correlation coefficients, linear regression, and logistic regression.

Abstract: These videos are a series of shorts explaining critical data science concepts through visuals and concise explanations. By learning these fundamentals in bite-sized format, you can digest concepts that are core in machine learning and statistical modeling. Problems like bias and spurious correlations can become easier to grasp as well. Topics include Bayes Theorem, probability distributions, mathematical notation, correlation coefficients, linear regression, and logistic regression.

Abstract: While reorganizations can unleash tremendous business value, they're inherently disruptive. And when they're managed poorly, they can do more harm than good. Michael Lopp and Heidi Helfand discuss how to make reorgs as painless as possible for leaders and teams. Join them to understand ways of approaching a reorg strategically to maximize the benefits of the changes, build unity with new teams, and minimize known challenges. You'll learn when and how to effectively communicate the business goals of the reorg, how to advocate for yourself and team members, and what you can do to help others adapt and thrive during this period of growth and change. Tech Leadership Tuesday is a dynamic monthly live event that helps empower people and technology leaders to become more effective and successful in their leadership roles. Each episode delves into a relevant topic for engineering leaders and, through a conversation between a host and guest, you'll learn about common challenges, best practices, and lessons learned from the guest's experience. What you'll learn and how you can apply it How to approach reorgs strategically to minimize disruption How to advocate for you and your team to benefit from the reorg This live event is for you because... You want the chance to hear from Michael Lopp and Heidi Helfand about software development and reorganizations. You want to be better prepared to navigate a reorg. Recommended follow-up: Read (or listen to) Dynamic Reteaming: The Art and Wisdom of Changing Teams, second edition (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: Gallup surveys indicate that up to 67% of the global workforce is disengaged, with disengaged workers costing companies significant money and lost time. Managers and supervisors are in a unique position to change this bleak reality by utilizing best practices to keep their direct reports motivated and engaged. This course provides information and tools for getting direct reports off to a strong start with clear goals as well as the resources and connections they need to accomplish them. It will help managers create a healthy work environment that's conducive to achieving strong performance, delivering helpful feedback, and reengaging a direct report whose motivation is flagging. What you'll learn and how to apply it At the end of this course, you'll be able to: Set goals and track performance Ascertain what motivates (and demotivates) direct reports Use tools to keep direct reports engaged with their supervisor, their colleagues and their work Implement best practices for creating a work environment that's conducive to employees thriving over the long haul Approach giving feedback in a way that gets heard and builds trust with direct reports Use the powerful Stay Interview to re-engage a direct report and help them find the motivation they need to continue with their present employer while contributing at their highest level Tap into available resources if you have followed the best practices for motivating employees and their direct report is still not performing and not demonstrating motivation to improve their performance This course is for you because... You're a recent (1-3 years) manager who wants to become more effective at motivating direct reports You're an aspiring manager who wants to learn what it takes to motivate direct reports You manage informally (i.e. a team lead or project lead) and are looking to incorporate some best practices for motivating your team members into your approach Prerequisites No prerequisites are required for this course.

Abstract: Join us for a special conversation with Sam Newman and software development pro Kevlin Henney, who'll discuss software design things that practitioners keep forgetting about and why good design matters so much. They'll also explore the idea of using the oft-cited "right tool for the job" and explain why that's so difficult to determine when the very process of development is what reveals "the job." This is a chance for you to hear from Sam and Kevlin about software development, how to use the right tools for your work, and their own career journeys. They'll spend a few minutes covering the trends that are influencing software, 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 what really matters for software design See what's coming next for software development This recording of a live event is for you because... You want the chance to ask Sam Newman and Kevlin Henney your questions about software development. Recommended follow-up: Attend Software Development Superstream: Becoming a Senior Software Engineer (live event on February 22).

Abstract: The ability to store, process, and manage data in the cloud efficiently and cost-effectively is a must for working with today's enormous datasets. Data lakes answered the problem of silos found in many data warehouses. And the data lakehouse emerged as a solution that combined the strengths of both models. But with the number of versatile data storage and management options available, it can be hard to figure out which solution is right for you. These expert-led sessions will give data engineers, software engineers, and solution architects insight into how to increase the scalability, speed, and availability of your data, along with best practices for best utilizing your data warehouse, data lake, or data lakehouse. About the Data Superstream Series: This Superstream series is designed to help your organization maximize the business impact of your data, and packed with insights from key innovators and the latest tools and technologies to help you stay ahead of it all. What you'll learn and how you can apply it Get an overview of the latest technologies for storing and managing your data Discover the benefits of implementing a data lakehouse for improved analytics and data science Understand how to perform robust analytics on a cloud data warehouse Find out how to test data quality at scale with Apache Iceberg Learn best practices for using a data mesh approach Explore how to democratize and leverage machine learning on a data lakehouse This recording of a live event is for you because... You're a data or software engineer or solution architect interested in learning about the latest trends in storing, processing, and managing data. You want to improve the scalability, speed, and availability of your data. You want to better understand the systems that you already use and learn how to take full advantage of their capabilities. Recommended follow-up: Read The Cloud Data Lake (book) Read Data Management at Scale, second edition (book) Take Google BigQuery First Steps (live online training course with Joy Payton) Take Data Lakehouse Fundamentals (live online training course with Janani Ravi) 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: 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 George Anadiotis and Dan Jeffries, former CIO at Stability AI, for a discussion on the current developments in the field of generative AI, open source AI research, and state-of-the-art AI models such as Stable Diffusion that are making waves in the field--and beyond. Hear about the applications that are being built with generative AI, the challenges and limitations of these powerful models, the impact they'll have in industries such as media, biotech, and software development, and more. What's New in AI gives you a chance to hear from leading minds in the field on topics such as generative AI, large language models, responsible AI, current regulations, and other developments as they appear. Host George Anadiotis, founder of Linked Data Orchestration, and members of O'Reilly's community of experts help you make sense of the bigger picture in AI and leverage emerging AI technologies to solve your organization's most challenging problems. What you'll learn and how you can apply it Understand the origins of and vision behind the generative AI renaissance and discover what's coming next Explore the Diffusion architecture and learn how to use it to create and customize generative AI models This recording of a live event is for you because... You want to understand the potential of generative AI as a tool for building innovative solutions and products for your organization. You're a data scientist, machine learning engineer, machine learning architect, leader, or practitioner who designs, develops, and deploys machine learning systems. You want to keep up-to-date on the latest developments and breakthroughs in the field of AI. Recommended follow-up: Read Hands-On Generative AI with Transformers and Diffusion Models ( early release book) Read "Autoencoders, GANs, and Diffusion Models" (chapter 17 in Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow) Read "Image and Text Generation" (chapter 12 in Practical Machine Learning for Computer Vision) Read "Text Generation" (chapter 5 in Natural Language Processing with Transformers) Read Generative Deep Learning, second edition (early release 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: What you'll learn and how you can apply it Explore contemporary tools and techniques in data visualization for better business decision-making Learn best practices for data visualization and storytelling that you can apply to your work today Build data visualizations that provide actionable insights from complex sets of data Develop an interactive, functional dashboard for end users to use while incorporating the best visualization and graphic design principles This recording of a live event is for you because... You're a data advocate within your organization who wants to tell data's story through the creation of compelling data visualizations. You're an analyst or decision-maker who wants to hone your skills and learn new data visualization techniques and best practices. You're a business intelligence specialist for your company, and you want to practice your craft with a real-world challenge. Recommended follow-up: Read ColorWise (book) Read Fundamentals of Data Visualization (book) Read Tableau Strategies (book) Read Mastering Salesforce Reports and Dashboards (book) Read Practical Tableau (book) Read Hands-On Data Visualization (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: Join us for a special conversation with Sam Newman and tech leader Pat Kua, where they'll discuss why excellence in software engineering matters more today than ever--and why it's important to continually hone your craft. They'll also explore how engineering practices have evolved and what that implies for the future. This is a chance for you to hear from Sam and Pat about software development, how to use the right tools for your work, and their own career journeys. They'll spend a few minutes covering the trends that are influencing software, 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 what really matters for software design Find out what's coming next for software development This recording of a live event is for you because... You want the chance to hear from Sam Newman and Pat Kua about software development. You want to keep up with the latest developments in engineering practice. Recommended follow-up: Read Building Evolutionary Architectures, second edition (book) Listen to The Manager's Path (audiobook) Read The Staff Engineer's Path (book).

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: 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: Python programming knowledge is at the core of financial applications. Knowing Python and modeling will help you to tackle the challenging problems in finance. Besides, learning or improving the modeling skill in finance with Python can enhance your understanding and contribute tremendously to your skill set. Python is a powerful tool in modeling due to its simplicity and robust modeling capabilities. Python includes libraries for mathematical operations, optimization, visualization, manipulation, and so on. Combining these wide range of applications with a user-friendly Python environment, there has been a consensus to say that Python is quite handy in financial modeling. In this video course, modern financial issues will be tackled with step-by-step explanations via Python. To do that, the course is divided into three modules. In the first module, after a brief introduction to Python with functions, iterations, and conditions, the main financial concepts will be discussed. What you'll learn and how you can apply it How to write script for the main functions of Python. What the main financial tools in financial modeling are (as well as Regression, APIs, and required Python libraries). How to tackle main Financial problems with Python. How to interpret the empirical results of the financial model and how to make sense of them. This course is for you because... You're a financial analyst or decision maker in your current role. You want to improve your finance knowledge. You're familiar with Python and specifically want to learn how to adapt Python to Finance while increasing your Python skills. Knowing financial modeling takes you to a whole new level in your career. Prerequisites: Beginner level Python Beginner level of finance knowledge.

Abstract: Sponsored by F5 Join us for a conversation on API architectures with James Gough, distinguished engineer at Morgan Stanley and author of Mastering API Architecture, and Byron McNaught, senior solutions marketing manager at F5. They'll discuss strategies for building and testing APIs that use API gateways to combine offerings at the microservice level and cover some of the challenges around deploying, operating, and configuring key components of an API platform, using API gateways and service meshes appropriately, and core security and common vulnerabilities in API architecture. What you'll learn and how you can apply it Learn API fundamentals and architectural patterns for building an API platform Use practical examples to understand how to design, build, and test API-based systems This live course is for you because... You want to go beyond the words on the page and hear from the expert author. You want to learn principles and best practices for mastering API architecture. Recommended follow-up: Read Mastering API Architecture (book) Read Principles of Web API Design: Delivering Value with APIs and Microservices (book) Watch API Day (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: Join us for this edition of O'Reilly Book Club with Yevgeniy Brikman, author of Terraform: Up and Running, to learn more about Terraform's simple, declarative programming language for deploying and managing infrastructure with a few commands. Ask questions, learn tricks of the trade, listen to stories, and connect with other readers. The O'Reilly Book Club series is an opportunity to delve into your favorite O'Reilly books and deepen your understanding of the topics they cover. You'll hear directly from O'Reilly authors about why they wrote these books, what issues they're trying to solve, and which challenges they still struggle with. What you'll learn and how you can apply it Progress from Terraform basics to running a full stack that can support a massive amount of traffic Get up to speed on Terraform 0.13 to 1.0 and beyond This recording of a live event is for you because... You want to go beyond the words on the page and hear from the experts. You're a sysdamin, DevOps engineer, or novice developer who wants to move from Terraform basics to advanced techniques. Recommended follow-up: Read Terraform: Up and Running, third edition (book) Read Terraform Cookbook (early release book).

Abstract: Because communication is at the root of all successful professional endeavors--from landing a job to negotiating a deal to managing conflict--professionals have always needed to be strong communicators. But in a world where both consumers and employees are saturated with information and technology, professionals now more than ever need to harness specific communication strategies for creating messages at work that cut through the clutter, resonate with audiences, and draw attention to key points. In this business communication course, Curtis Newbold covers the critical strategies for improving interpersonal and written communication. More specifically, Curtis walks learners through processes to become more emotionally intelligent and communication-aware professionals. This course will help viewers become better relationship-builders and stronger writers and speakers. After taking this course, professionals can expect to feel more confident in their abilities to share high-impact information through one-on-one interactions, direct email, and written interactions. Moreover, participants will be able to use communication strategies to better persuade stakeholders and employees to get on board and to take action. What you'll learn and how you can apply it: Recognize the role of communication in workplace efficiency, relationship-building, persuasion, negotiation, and leadership. Apply emotional intelligence to create self-awareness and positively influence others. Write with efficiency and clarity in emails, letters, and reports to establish credibility and motivate people to take action. Lead teams through effective conflict management, constructive feedback, and the integration of inclusive language and active listening. This video course is for you because... You're in or seek to advance toward team leader, management, or executive roles. You write, design, and distribute content meant to inform, persuade, and encourage action. You're seeking communication tactics that can be applied in day-to-day work.

Abstract: Problems. We are plagued with them. Some we see coming, but others sneak up on us. Do youfeel like you need to put out fires on a daily basis and sometimes are left with little time to get toyour core responsibilities? The ability to meet problems head on in the most efficient and sustainable fashion is a core skill for any professional wanting to make their mark. Having thetools to be able to solve problems effectively increases your productivity, streamlines workflow,and prepares you to take on new roles and responsibilities. Join Zina O'Leary as she walks you through how to tackle issues before they become problems, how to identify problems so that they can be addressed, and how to analyze problems so thatyou can successfully deal with them. After this course you will be able to resolve problems in asustainable fashion that satisfies a range of stakeholders. What you'll learn and how you can apply it Control issues before they become problems Identify problems as they arise Analyze problems from a variety of perspectives Efficiently and effectively engage in problem resolution This course is for you because... You're an individual contributor in your organization and you want to learn how to tackleissues before they become complex and potentially expensive problems. You manage a team and you need to be able to analyze and solve problems in the mostefficient and effective manner possible. You're a leader within your organization and you want to embed solid problem solvingskills in your workforce. You want to become a better problem solver.

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: You've got your Kubernetes cluster up and running. . .so what's next? You can do much more with Kubernetes than just manage containers. These expert-led sessions will show you how. Join us to keep up with Kubernetes. You'll learn practical strategies and techniques (like how to build K8s into your own developer platform and how to use it on a public cloud), get insight into doing serverless on Kubernetes, and get a glimpse of what the future holds for this widely popular tool. What you'll learn and how you can apply it Understand the benefits and pitfalls of working with Kubernetes Learn how tooling can help with multicluster management This live event is for you because... You're a developer who wants to learn more about developer platforms built on top of Kubernetes so that you can have the tools you need when you need them. You want to use Kubernetes to benefit or improve reliability, velocity, security, and more. You want to learn more about MLOps and the Kubernetes tools ecosystem. Recommended follow-up: Read Kubernetes Up and Running, third edition (book) Explore Certified Kubernetes Application Developer (CKAD), second edition (video course) Watch GitOps and Kubernetes (video edition) Read Introducing MLOps (book) Watch Infrastructure and Ops Hour: Platform Engineering with Camille Fournier (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: 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: Join us for this edition of O'Reilly Book Club with Chip Huyen, author of Designing Machine Learning Systems. You'll learn more about the complex and quickly evolving components of current machine learning systems and how best to ensure your systems are scalable, reliable, and taking advantage of the developing technologies in the field. Ask questions, learn tricks of the trade, listen to stories, and connect with other readers. What you'll learn and how you can apply it Discuss the challenges you're facing and discover opportunities for building machine learning systems for industry Learn tips for developing reliable, scalable, and adaptive machine learning systems for changing environments and business requirements This live course is for you because... You want to go beyond the words on the page and hear directly from the subject matter expert. You're a data scientist, data/machine learning engineer, machine learning architect, or software engineer who is building systems on top of AI models. Recommended follow-up: Read Designing Machine Learning Systems (book) Read Machine Learning Interviews (early release book) Read Machine Learning Design Patterns (book) Watch Designing Machine Learning Systems (Superstream video) Follow AI Superstream: Designing Machine Learning Systems (expert playlist) 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: 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: 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: Sponsored by AWS It's no longer a question of whether your organization is moving to the cloud, but rather how fast you can move while ensuring security, visibility, control, and safety. If you're migrating to the cloud or already operating in the cloud, you want a secure and efficient way to manage and monitor your infrastructure and applications in the cloud, on premises, or in hybrid or multicloud environments. Join us for the third of three half-day online events in the AWS Observe and Operate series designed to showcase solutions for your observability and operations needs. The pressures to keep systems up and running with minimal disruption are increasing while applications, infrastructure, and services are being deployed at ever-increasing rates. The dynamic nature of modern applications and architectures is producing an explosion of siloed data and telemetry from multiple sources. Observability and operations professionals are being challenged to maintain SLOs and SLAs to achieve availability, reliability, and performance. In this third event in the AWS Observe and Operate series, we dive deep into key use cases for operations and observability and demo solutions as you set up alarms, detect anomalies, identify and analyze issues, build in proactive and reactive operational processes, and automate responses to issues in order to lower Mean Time To Resolution (MTTR), maintain availability and performance, prevent and mitigate operational issues, and optimize resources and infrastructure. We will show you how customers have used AWS services to apply Amazon best practices for observability and operations. Join this interactive event as we demo and answer your burning questions live! This course is for you because: You're a cloud engineer or architect responsible for managing and maintaining infrastructure and applications in your AWS, hybrid, or multicloud environment. You are responsible for monitoring systems and applications to ensure they run smoothly, and for identifying and resolving incidents quickly to minimize downtime and prevent disruptions. You want to improve MTTR, maintain high availability, and improve performance across your applications. What you'll learn and how you can apply it: Understand how you can use AWS to achieve your business and operational goals Learn how you can leverage AWS to improve system performance, enhance customer experience, and optimize cost Get best practices on setting up your operations and observability Prerequisites: Foundational knowledge of cloud and/or on-premises infrastructure and applications Recommended follow-up Watch AWS Observe and Operate: Manage Your Cloud Infrastructure and Modern Applications (video) Watch AWS Observe and Operate: Monitor Your Cloud Infrastructure and Modern Applications (video) Read AWS Observability Best Practices (AWS resource).

Abstract: This course will provide the foundational knowledge necessary to engage the vulnerability management team, support risk management, and collect data for risk assessments. Join expert Dean Bushmiller to learn the basis for scientifically defining and differentiating today's threats and vulnerabilities. Explore the best ways to identify and manage vulnerabilities using the CVE scoring system, the CAPEC system, the CWE system, and the MITRE ATT&CK matrix. What you'll learn and how you can apply it The components of vulnerabilities and threats and how to compare and contrast them The CVE vulnerability scoring system to prioritize actions The organization of the CAPEC system The root causes of hardware and software vulnerabilities Which vulnerability management system works with your environment How to interpret threat vulnerability reports and inform stakeholders This course is for you because: You're a professional looking to enter or advance in cybersecurity roles. You're a professional with cybersecurity as a component of your job description. You're a security analyst, vulnerability analyst, penetration tester, blue team technician, red team technician, network defense auditor, or risk assessor. Prerequisites: Equivalent knowledge of CompTIA Network+ certification Knowledge of the following: ports, protocols, services, OSI layers, routing, switching, IP addressing, wired and wireless networking infrastructure, network operations, and network troubleshooting tools. Recommended follow-up: Take Risk Management for Cybersecurity and IT Managers (video course with Jason Dion) Take System and Privacy Data Protection (video course with Aamir Lakhani).

Abstract: Join host George Anadiotis and guest Evan Sparks, chief product officer of AI at Hewlett Packard Enterprise, who'll discuss the AI chips and new AI hardware that will enable the latest AI-powered systems to run more efficiently and effectively. AI chips provide an advantage over general-purpose processors for AI systems that require exponentially larger volumes of data and computational power. Generative AI and new models like ChatGPT, GPT-4, and others have migrated beyond the AI field into the general public. At the same time, the creators of AI chips, which enable practitioners to train and deploy these models, are equally engaged in a somewhat lesser-known effort: the race to produce the best hardware to support these powerful AI systems. Join George and Evan to discuss how AI chips are becoming the backbone of new AI systems, and hear their thoughts on the state of AI chips today and the developments to look for in the near future. What's New in AI gives you a chance to hear from leading minds in the field on topics such as generative AI, large language models, responsible AI, AI hardware, and other developments as they appear. Host George Anadiotis, founder of Linked Data Orchestration, and members of O'Reilly's community of experts help you make sense of the bigger picture in AI and leverage emerging AI technologies to solve your organization's most challenging problems. What you'll learn and how you can apply it Understand the advantages of these new hardware technologies and the types of applications and systems they can power Learn about different AI chip architectures and what each brings to the tableExplore how to evaluate the options Discuss the role of software stacks in abstracting different AI chips or integrating them tightly in your applications Learn about the changing terrain of AI hardware vendors and service providers This recording of a live event is for you because... You're a data scientist, machine learning engineer, machine learning architect, leader, or practitioner who designs, develops, and deploys machine learning systems. You want to keep up-to-date on the latest developments and breakthroughs in the field of AI. Prerequisites A basic understanding of machine learning systems Recommended follow-up: Read "Infrastructure and Tooling for MLOps" (chapter 10 in Designing Machine Learning Systems) Watch "Energy-Efficient AI and High-Performance Computing Data Centers" (event segment video) Watch Fast and Lean Data Science with TPUs (video).

Abstract: This course covers the basics of the Agile and Scrum Methodologies, and its application to layers of various technologies. Leading Blockchain projects requires a scaling agile approach as well as blending together various Agile solutions to accommodate the Blockchain solutions combined with accompanying technologies. In this course learner will attain the skills needed to lead Blockchain based projects. What you'll learn and how you can apply it By the end of this course, you'll understand: The foundations of the Agile and Scrum methodologies How to apply Scrum and Agile principles to Blockchain projects How to scale Agile to a team-of-teams approach How to use different Agile methodologies to lead and deliver complex solutions And you'll be able to: Understand how to implement an Agile and Scrum solution for complex projects. Scale Agile and Scrum solutions to support layers of technologies. Involve the team and stakeholders in continuously delivering working Blockchain based projects. This course is for you because... You're interested in the distributed ledger emerging technology. You work in IT, and you want to understand the solutions Blockchain delivers. You want to add to your current skill set and become a leader in Blockchain and emerging technology. Prerequisites: Basic knowledge of web applications and the Internet.

Abstract: Packet analysis using Wireshark is one of the most critical hands-on skills to have as a security practitioner. It is also a versatile skill, spanning many facets of cybersecurity. If you read a technical report on network security, threat intelligence, or even application security, Wireshark is commonly used and referenced. Packet analysis and Wireshark are used in system administration, troubleshooting networks, incident response, and forensics. In this course, learners will learn the basics of packet analysis, looking at and understanding network traffic, and using real network traffic in exercises. Basics including network packet, the Open Systems Interconnection model (OSI) model, and a packet capture (PCAP) file will be introduced. Demonstrations include using Wireshark to reconstruct a conversation between two computers, extract pictures from a PCAP file, extract credentials that were sent insecurely on a network, and analyze maltraffic. What you'll learn and how you can apply it What a network packet is and how it encapsulates the OSI model The dangers of sending sensitive data unencrypted, "in-the-clear," over an open or untrusted network The difference between encoding and encryption And you'll be able to: Reconstruct files (e.g., images, video, audio, apps) from network traffic. Catch sensitive information (including usernames and passwords) from network traffic. Verify sensitive information without illegally logging into a system without permission. Filter network traffic by IP address(es), protocol, and even by strings. Analyze network traffic containing malware. This course is for you because... You're a software engineer or web developer who wants to know more on how things work on the network level. You're a security practitioner and want to understand how things (i.e., the network, network communications under the hood) really work -beyond just using security tools (e.g., Ettercap, Kismet, Xplico, NetworkMiner). You want to become a network engineer or specialist. You have aspirations to work in network security or threat intelligence. Prerequisites: Basic working knowledge of computers, including installing software, uploading and downloading content, hardware, and software Rudimentary knowledge of computer security concepts such as plaintext, encryption/decryption, malware.

Abstract: Sponsored by deepset Join us for this edition of O'Reilly Book Club with Lewis Tunstall and Leandro von Werra, authors of Natural Language Processing with Transformers, to learn how transformers, which are the backbone of the state-of-the-art LLM models in the field today, work and how to integrate them in your applications. Bringing insights from their experience working at Hugging Face, Lewis and Leandro will discuss the benefits and challenges of training your own model, scaling, and deploying it for your system. Learn tricks of the trade, listen to stories, and gain new insights. What you'll learn and how you can apply it Learn about a variety of NLP tasks transformers can help you solve Understand how transformers can be used for transfer learning Learn about building, debugging, and optimizing transformer models This live event is for you because... You want to go beyond the words on the page and ask your own questions. You're a data scientist, machine learning engineer, or developer who is working with AI and machine learning and want to learn about the latest developments in the field. Recommended follow-up: Read Natural Language Processing with Transformers, Revised Edition (book) Read Hands-On Large Language Models (early release book) Read Hands-On Generative AI with Transformers and Diffusion Models (early release book) Read Introduction to Transformers for NLP: With the Hugging Face Library and Models to Solve Problems (book) Watch Natural Language Processing Using Transformer Architectures (video).

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: The Hedera Hashgraph Enterprise Strategist program allows non-technical students and working professionals to demonstrate the knowledge required to orchestrate client applications and smart contracts leveraging Hedera Hashgraph. Your introduction to Distributed Ledger Technology (DLT) technology allows you to see how this technology could impact business, operation models, and solution integration. What you'll learn and how you can apply it By the end of this course, you'll understand: The foundations of the Agile and Scrum methodologies. How to apply Scrum and Agile principles to Blockchain projects. How to scale Agile to a team-of-teams approach. How to use different Agile methodologies to lead and deliver complex solutions. And you'll be able to: Understand how to implement an Agile and Scrum solution for complex projects. Scale Agile and Scrum solutions to support layers of technologies. Involve the team and stakeholders in continuously delivering working Blockchain based projects. This course is for you because... You're interested in the distributed ledger emerging technology. You work in IT and want to understand the solutions Blockchain delivers. You want to add to your current skill set and become a leader in Blockchain and emerging technology. Prerequisites: Basic knowledge of web applications and the Internet.

Abstract: Agile development is not really about being fast, but about getting into a rhythm with sustainable speed so we can deliver continuously. Among other things, agile development requires creating high quality code and lightweight design. Often, a lack of or inadequate automated testing makes it hard to respond to change. Automated testing provides two significant benefits: regression and better design. However, writing tests mechanically will not automatically give us design benefits. This course focuses on how to use automated tests to drive the design of applications. We start with learning about strategic design and then dive into tactical design issues influenced by automated tests. We learn about both test and design quality, how to maintain a good code coverage, and the essential principles for creating lightweight design. Along the way we will discuss how to bring in design patterns and also measure the quality of design. What you'll learn and how you can apply it Learn how to build software from start to finish. Learn how to use automated tests to design applications Learn about strategic design and how to use design patterns Learn how to dive into tactical design issues influenced by automated tests Learn how to maintain a good code coverage Learn the essential principles for creating lightweight design Learn how to measure the quality of design. This course is for you because... You're a programmer, group leader, hands-on architect, or a technical manager. You work with code that requires high quality design and needs to be extensible. You want to become a better developer or leader of a team that develops industrial strength software. Prerequisites: Strong programming knowledge and experience, in any language, though Java will be used in the examples. Some experience with design principles and patterns is helpful but not required.

Abstract: With an increased demand for SEO effectiveness, Python, and the advances in data science, this course teaches web professionals, data analysts, and scientists how to understand and apply data-driven approaches to improve website search visibility. It's crucial for those in digital marketing and data analysis to stay ahead in a rapidly evolving field where data science is key to success. This course uniquely integrates the power of Python and data science with the strategic needs of Search Engine Optimization. This course offers in-depth knowledge and practical skills for leveraging data science in enhancing SEO strategies across high demand SEO topic areas. Learners will understand how to navigate the challenges of integrating data science techniques into SEO strategies. The course addresses the gap in knowledge between SEO practices and data science, providing professionals with the tools to make informed, data-backed decisions, crucial for enhancing online website visibility in search engines. Learners will acquire skills in querying the Google Search Console API, keyword clustering based on search intent, data-driven content optimization, forecasting search trends, and conducting valid SEO split tests. The course empowers participants to use Python for practical, impactful SEO and data analysis, setting a new standard for excellence in SEO. What you'll learn and how you can apply it By the end of this course, the learner should understand the relationship between data and SEO performance and be able to apply data science techniques in Python. This course is for you because... You're a SEO professional interested in learning to save time producing high impact SEO recommendations. You're a data scientist or data analyst looking to level up your SEO skills to help your organization win and retain more clients and increase visibility. You want to see how Python and Data Science can be applied to SEO. Prerequisites Open a Jupyter notebook Run Python commands in Jupyter Install Python packages either via the command line or Jupyter using the Python Install Packages (pip).

Abstract: Trust is the bedrock of every relationship and for managers, it is vital to ensuring that team members feel supported and perform successfully. Without trust, teams fracture: individuals do not share information, conflicts increase, and cooperation breaks down. In this on-demand course, managers will learn the importance of trust and several models for fostering it. You will learn common behaviors that break trust and ways to build it back and forge strong team relationships. What you'll learn and how you can apply it Understand the importance of trust at work Learn the three dimensions of trust Understand the trust equation Learn the pillars of trust Learn the ways to build trust Develop strong team relationships Understand the traits of trustworthy managers Understand the ABCD Model of Trust Distinguish between trust building actions and trust breaking actions Understand trust inducing behaviors This course is for you because... You're a team leader or manager who needs to build more trust with the team. You're a manager who feels that a lack of trust is impeding your team's success. You're a new manager who needs to build a cohesive and high-performing team and you want to start off on the right foot. Prerequisites: Experience as a manager.

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

Abstract: Sponsored by F5 and Orca Security Many organizations today find themselves in a hybrid or multicloud environment, whether they planned it or just stumbled into it. But juggling workloads across these complex architectures is an incredibly tricky business. From isolated silos to costly resource sprawl, the challenges are immense. The supercloud has arrived on the scene to help, providing a layer of abstraction on top and offering a consistent way to manage it all. However, there's a lot of mystery still swirling around about what the supercloud is exactly and how it works. Join our expert speakers as they shed light on the different approaches to managing combined or multiple private, public, and edge clouds. They'll demystify common terms and concepts, help you gain a better understanding of what these various cloud models look like in practice, and show you how to successfully plan for, deploy, monitor, and secure these complex cloud architectures of the future. What you'll learn and how you can apply itUnderstand the various cloud deployment models and the opportunities and challenges of combining different types of cloud services and infrastructure Learn how to prepare for the complexities of hybrid or multicloud systems and identify the best solutions for your business or professional needs This recording of a live event is for you because... You're a developer, architect, engineer, or decision maker working with complex cloud environments. You want to be able to manage or leverage multiple cloud services and stay up-to-date on the latest developments in cloud technologies. Recommended follow-up: Read Cloud Without Compromise (book) Read Hybrid and Multicloud Management (report) Watch Infrastructure & Ops Hour: Multicloud with Gregor Hohpe (video) Take Multicloud Strategy Choices and Trade-Offs (live online training with Rashmi Tambe and Sunit Parekh) 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: Sponsored by Rapid The API economy has precipitated a need for expert developers and architects who understand the intricacies of building, integrating, and monitoring APIs to connect distributed systems and deliver data for enhanced performance. API Day will give you a head start. Join host and API author Mike Amundsen and some of the top experts in software development to better understand the full picture of the API economy. You'll explore API options, service-oriented architectures, and security concerns; learn how to evolve existing legacy applications toward API-based systems and use API infrastructure for evolving or replatforming a system for effective cloud deployment; and so much more. Whether you're a business leader, security analyst, developer, or software architect, these practical sessions will help you build resilient applications as part of the API economy. What you'll learn and how you can apply it Learn how the API economy is driving and transforming distributed systems Understand how to design, build, integrate, and secure APIs Determine your API strategy for new software or legacy applications This live event is for you because... You're a software architect looking to evolve legacy systems using APIs and effectively integrate them without security risks. You're a software developer who needs strategies for successfully choosing and integrating APIs, as well as skills and tools for building robust and scalable APIs. You're part of an ops team dealing with the integration, governance, management, and automation of APIs and the applications using them. You're a security analyst who wants to better understand how to better combat the threat presented by recent increases in API attacks. You're a business leader looking to lead and accelerate your digital transformation efforts. Recommended follow-up: Read Mastering API Architecture (book) Read RESTful Web API Patterns and Practices Cookbook (book) Read Continuous API Management (book) Read Designing Web APIs: Building the APIs That Developers Love (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: As software development grows more complicated and becomes increasingly central to a business's identity, the demand is high for developers who operate at a senior level. Join us to level up your skills and accelerate your journey to senior software engineer. These in-depth sessions cover some of the biggest challenges facing software developers today, teaching you practical methods and best practices to improve coding and software design, better manage data, mentor new engineers, and collaborate with your team. About the Software Development Superstream Series: This series will help you elevate your technical skills, become a better project manager, and build the other professional skills that will allow you to move into senior engineering roles. What you'll learn and how you can apply it Learn how to contribute at a high level, drive big projects, and determine tech strategy Understand what's really important for career development Determine what you should be working on, set your goals, and define your backlog of work This recording of a live event is for you because... You're a developer who wants to find your skills gaps and upskill accordingly to move to the senior or staff level. You want to better understand what work matters the most at every stage of your career and learn how to build the skills you need to support your journey. Recommended follow-up: Read The Staff Engineer's Path (book) Read Software Engineering at Google (book) Listen to The Manager's Path (audiobook) Read Mentoring (book) Take From Developer to Software Architect (live online training course with Nathaniel Schutta) Take Fundamentals of Software Engineering in 3 Weeks (live online training course with Nathaniel Schutta) Take Hands-On Software Design (live online training course with Venkat Subramaniam) Take Introduction to Critical Thinking (live online training course with Connie Missimer) 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: Sponsored by deepset Reaching a million users in less than a week, ChatGPT has ignited discussions about the potential of artificial intelligence to disrupt industries from law to academia, art to medicine. OpenAI and Google, Meta, and others are releasing large language models that are fueling innovations in the development of search engines, recommendation systems, and tools we use to generate content from text, images, and music to code and software. While the possibilities for new products and services built on these state-of-the-art AI systems are endless, business leaders and machine learning practitioners alike are searching for answers on how to get the most of these technologies for their work. Important questions are also emerging around the limitations and potential obstacles to integrating new large AI models such as ChatGPT into existing systems. Join our expert speakers to discuss these issues and learn how you can leverage ChatGPT and other large AI models to build new products, increase productivity, and more. What you'll learn and how you can apply it You're a current or future machine learning product owner or machine learning practitioner, or you're simply interested in the state of the art of artificial intelligence. You want to learn more about ChatGPT and other large AI models and how they will impact other technologies as well as nontechnological fields. This recording of a live event is for you because... Discover possibilities for ChatGPT and large language models Uncover pitfalls and avoid missteps as you integrate this new frontier in AI into organizations of all types Learn actionable suggestions on dealing with large datasets and data augmentation, various model architectures, domain adaptation, and inference challenges Recommended follow-up: Read Natural Language Processing with Transformers, revised edition (book) Follow ChatGPT (expert playlist) 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.