GitHub Copilot: Hands on AI coding with real world examples

Explore GitHub Copilot, an AI-powered coding assistant by GitHub leveraging OpenAI cloud LLMs to suggest code, explain snippets, generate tests, and debug inside IDEs.

Understand large language models and how GitHub Copilot uses them, covering tokenization, prediction, the transformer, and training and fine-tuning, with examples from OpenAI Cloud and GitHub data.

Explore real world debugging with GitHub Copilot as you fix a Spring Boot app by updating a pom.xml dependency; watch Tomcat start on port 8080 after Copilot suggests the fix.

Explore how GitHub Copilot uses project context to understand files like pom.xml and java files, enabling context-aware queries, updates, and automated builds while managing tokens.

Learn how to set up GitHub Copilot in Visual Studio Code, including installing the Copilot extension, Java and spring boot extensions, and exploring inline suggestions and the Copilot chat.

Explore GitHub Copilot's inline chat in Visual Studio Code, learn to generate javadoc and methods, accept or discard suggestions, and easily disable or snooze prompts.

Explore the GitHub Copilot overview, capabilities, and the LLM internals—tokens and vectors—along with simple and inline chat, VS Code setup, and context for advanced concepts.

Explore advanced Copilot features, including custom instructions, prompt files, custom agents, hooks, and agent mode to accelerate real-world coding with GitHub Copilot.

Experience hands-on practice with GitHub Copilot by fixing code, creating files, and reading files using different participants in a Spring Boot project.

Explore copilot customization within the built-in plan, including prompts, agents, skills, MCP servers, and plugins; create a .github directory with custom prompts to tailor features for repo users.

Learn to tailor GitHub Copilot with custom instructions for commit messages, by creating a settings.json in VS Code and appending the project name to each commit.

Apply custom instructions for GitHub Copilot using a .github directory and instructions.md to generate Java docs for all public classes and methods in a Spring Boot project.

Discover how GitHub Copilot reads images, extracts text, and updates a markdown file with content. Learn token considerations for large images and prompts for better results in the next session.

Create custom prompts in GitHub Copilot using workspace prompts and the agent customization window, then set up a review prompt (review.prompt.md) for Java code.

Provide file context and references to guide GitHub Copilot in generating code and JUnit tests. Use precise prompts, consider chat history as context, and avoid overwhelming prompts for improved results.

Create custom agents in GitHub Copilot to research and learn features like JUnit, using fetch and web tools to build an md file knowledge base with code samples.

Learn how GitHub Copilot hooks enable pre and post prompt actions, with json-configured hooks triggered on session start, end, and user prompt submission.

Explore capabilities and internal workings of GitHub Copilot, from Visual Studio Code setup to LLM based tokenization, context handling, vectors, and inline chart, including suggestions, concluding the getting started section.

Review the model context protocol essentials, its client-server architecture, and GitHub MCP features in Visual Studio Code for commit, add, and push, and an MCP time converter.

Generate JUnit tests and Mockito integration with GitHub Copilot. Update pom.xml with JUnit, Mockito, and Jacoco plugin; run mvn clean install and mvn clean test to produce a Jacoco report.

Explore GitHub Copilot billing and licensing, view ai credits and metered usage, and download billing reports. Configure budgets and alerts by ai credits or product level or student plan.

Deepen your understanding of GitHub Copilot hooks, including pre tool, post tool, and session lifecycle hooks, with input and output parameters and permission decisions.

Explore pre-tool hooks in GitHub Copilot workflows by building a pre-tool hook to control tool execution, validate arguments, and apply time conversions across time zones.

Explore implementing a rate limit for an API with GitHub Copilot, crafting a prompt to add rate limiter in the controller and testing a 10 hits per 30 seconds constraint.

Use the Java Copilot SDK to programmatically create a Copilot client, configure the model and prompts, integrate with pom.xml, and run interactive sessions that answer simple queries.