Software engineering is entering a new era, one where humans and AI agents work side by side.
AI is no longer a futuristic concept in software engineering. In this exploratory course, you will dive into how the GitHub Copilot Agent can participate in every phase of the Software Development Life Cycle (SDLC), from initial requirement discussions to deployment strategies. You will explore and do hands-on experiments on how the GitHub Copilot Agent can become your collaborative partner throughout the SDLC.
The process reveals not just what GitHub Copilot can do, but how you can direct it to achieve meaningful outcomes. This course is not about replacing the human elements in SDLC. It’s about transforming how they work. You’ll learn to guide the AI as if it were a capable but inexperienced teammate: great at producing code or generating ideas, yet in need of your judgment and domain knowledge.
Each section includes hands-on exercises designed to simulate collaboration between human expertise and AI capability. Step by step, you will explore each SDLC phase: from gathering requirements to design, implementation, testing, and deployment. In every stage, you will learn how GitHub Copilot’s capabilities can streamline your work and help you think differently about collaboration and productivity.
The course encourages critical thinking: How should teams adapt to this new kind of coworker? What roles remain unique for human? Understanding this evolving collaboration could become an essential professional skill. The course focuses on process understanding: identifying where AI adds value and where it still falls short. You will finish with a practical mindset on how to effectively combine your expertise with AI assistance in your real-world development workflow.
- Early-to-mid level software engineers / developers
- Technical leads, team leads, or engineering managers
- Product owners or solution designers with (or without) coding expertise
- Advanced students or recent graduates in computer science / software engineering
- DevOps / QA engineers interested in AI-assisted workflows
