This module introduces the foundational concepts of generative AI, including its mechanics, practical uses in coding, and inherent limitations. Learners will explore how large language models (LLMs) perform text prediction, the role of system prompts, and considerations like context size and model memory. By the end, you'll understand how to effectively leverage generative AI tools such as GitHub Copilot in your development workflow.

This module guides learners through the process of evaluating and selecting the most suitable GitHub Copilot plan for individual or organizational needs. You will compare plan features, understand limitations and billing practices, and learn strategies to avoid common pitfalls when managing Copilot subscriptions.

This module guides learners through the practical use of GitHub Copilot within various IDEs, highlighting features such as inline code suggestions, natural language prompts, and automation tools. Participants will discover best practices for integrating Copilot into their workflow, explore advanced modes like Edit and Agent, and learn how to combine these capabilities for efficient software development.

This module introduces advanced features of GitHub Copilot, including its integration with the terminal, command palette, and debugging tools. Learners will discover how Copilot enhances development workflows through CLI automation, code review, and testing support, using real-world scenarios to maximize productivity and collaboration.

This module introduces the integration of GitHub Copilot into collaborative workflows on GitHub.com, including issue management, pull request reviews, and automation with the Coding Agent. Learners will discover how Copilot streamlines tasks such as drafting issues, suggesting code fixes, and monitoring team activity through dashboards. By the end, you'll understand how to leverage Copilot to enhance productivity and collaboration in software projects.

This module introduces the Model Context Protocol (MCP) as a means to extend GitHub Copilot with secure and flexible access to external tools and data. Learners will discover how to install and configure MCP servers in Visual Studio Code, differentiate between local and remote server setups, and leverage MCP to enhance the capabilities of the GitHub Copilot Coding Agent.

This module guides learners through the essential stages of mastering GitHub Copilot, from understanding prompt construction and LLM context to optimizing team workflows for AI integration. Learners will discover best practices, common pitfalls, and creative strategies for leveraging Copilot's various modes and prompting styles. By the end, participants will be equipped to use Copilot more effectively and collaboratively in real-world coding scenarios.

This module guides learners through effective strategies for fostering a collaborative internal community around GitHub Copilot and generative AI tools. Participants will explore hands-on learning methods, community engagement tactics such as Q&A sessions and hackathons, and approaches for gathering feedback and measuring adoption success.

This module explores how generative AI, such as GitHub Copilot, is transforming software development workflows and expanding its impact beyond coding tasks. Learners will examine ethical considerations, practical applications for both engineers and adjacent roles, and strategies for leveraging AI to enhance productivity and value delivery.