Learning Github Copilot Multiplying Your Coding Productivity Using Ai
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Learning GitHub Copilot
Harness the power of generative AI in your coding with GitHub Copilot. In this practical guide, author Brent Laster explains what Copilot is, how it works, and what it can do for you. You'll learn how to leverage AI to automate and simplify development, testing, documentation, and more. Software professionals in all roles will find the information needed to supercharge your productivity. Learning GitHub Copilot shows DevOps engineers, software developers, and database administrators how to make the most of the tool's code completion and generation capabilities. You'll understand how to take advantage of the tool's chat interface to get rich, detailed responses. Suitable for all skill levels--no matter what coding language or framework you use--Learning GitHub Copilot provides the knowledge you need to fully utilize Copilot. Learn how GitHub Copilot leverages GenAI and what it can do Understand when and how to use Copilot's separate inline and chat interfaces Explore ways to use Copilot for creating, testing, documenting, explaining, and fixing code Learn how to use Copilot for testing frameworks, SQL generation, and Kubernetes manifests Understand how Copilot integrates with IDEs and GitHub Discover the key strategies, tips, and tricks to make the most of Copilot's capabilities
Learning GitHub Copilot
Author: Brent Laster
language: en
Publisher: "O'Reilly Media, Inc."
Release Date: 2025-07-10
Supercharge your coding productivity with generative AI using GitHub Copilot. In this practical guide, author Brent Laster guides you through using generative AI for writing better code faster, generating tests with ease, creating polished documentation at any stage of development, and more. You'll also explore advanced uses—like leveraging Copilot's Agent functionality to add features autonomously and reviewing pull requests automatically. Learning GitHub Copilot is for developers, testers, DevOps engineers, and software professionals at all levels. Alongside the fundamentals, you’ll dive into Copilot Edits, Agent mode, and Copilot Vision. You’ll also learn how to create your own Copilot extensions to expand its capabilities. Whether you’re working in Python, JavaScript, or any other language, this book helps you confidently integrate AI into your development workflow. Harness real-time AI insights to explore and understand unfamiliar code and algorithms Master inline completions and the chat interface to automate common tasks Turn natural language prompts into complete functions, tests, and docs quickly and easily Optimize AI results with context and prompts to get targeted solutions Streamline feature development and refactors with AI assistance in your IDE
Structure and Interpretation of Computer Programs, second edition
Structure and Interpretation of Computer Programs has had a dramatic impact on computer science curricula over the past decade. This long-awaited revision contains changes throughout the text. There are new implementations of most of the major programming systems in the book, including the interpreters and compilers, and the authors have incorporated many small changes that reflect their experience teaching the course at MIT since the first edition was published. A new theme has been introduced that emphasizes the central role played by different approaches to dealing with time in computational models: objects with state, concurrent programming, functional programming and lazy evaluation, and nondeterministic programming. There are new example sections on higher-order procedures in graphics and on applications of stream processing in numerical programming, and many new exercises. In addition, all the programs have been reworked to run in any Scheme implementation that adheres to the IEEE standard.