Move beyond basic code completions and learn to use GitHub Copilot as a conversational development partner. This course teaches you how to structure multi-turn interactions that build context incrementally, producing more accurate and relevant code than single-shot prompts. You will master iterative refinement techniques that transform rough initial outputs into production-quality code through structured follow-up prompts and scope narrowing.

GitHub: Advanced Prompt Engineering for Code

Recommended experience
What you'll learn
Structure multi-turn GitHub Copilot conversations that build context incrementally and produce more accurate code than single-shot prompts
Apply iterative refinement techniques like scope narrowing, error correction, and follow-up prompting to transform code into production-ready output
Leverage cross-file context, open editor tabs, and specification-driven generation to work effectively across large and unfamiliar codebases
Details to know

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2 assignments
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There are 3 modules in this course
What's included
10 videos4 readings1 assignment
What's included
5 videos2 readings
What's included
1 video1 reading1 assignment
Instructor

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Felipe M.

Jennifer J.

Larry W.

Chaitanya A.

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Frequently asked questions
No prior Copilot experience is required. The course starts with foundational conversational prompting concepts before progressing to advanced multi-file context techniques. Basic familiarity with any code editor is sufficient.
Yes. Most developers use Copilot for single-shot completions and miss the conversational capabilities. This course teaches multi-turn interaction patterns, iterative refinement, and context management strategies that significantly improve the quality and relevance of generated code.
Demonstrations use Python with frameworks like FastAPI, but the prompting techniques apply to any language supported by GitHub Copilot. The focus is on interaction patterns and context strategies rather than language-specific syntax.
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Financial aid available,

