Target Audience
This course is designed for developers and technical professionals who want to accelerate their coding workflow using AI‑assisted development. It suits both beginners and experienced programmers, as the exercises range from simple code generation to full application scaffolding. Participants should have basic familiarity with Python and VS Code, but no prior Copilot experience is required. The session is ideal for anyone looking to improve productivity, code quality, and rapid prototyping skills.
Duration: 2 hours
1. Session Overview
Purpose: Frame Copilot as a practical productivity accelerator for developers.
Includes:
- What Copilot is and how it integrates with VS Code
- Workshop goals
- Brief intro of the consultant
Takeaway: Participants understand the scope of the workshop and what they will achieve in two hours.
Target Audience: Developers, data practitioners, and technical professionals who want to speed up coding tasks, improve code quality, and learn practical Copilot workflows.
2. Improving Developer Productivity with Copilot
- Inline code suggestions accelerate development
- Code generation from descriptive prompts
- Automated generation of functions, tests, comments and documentation
Topics:
- How Copilot interprets context
- When Copilot is most effective
- Real examples of productivity gains
Takeaway: Participants see how Copilot reduces repetitive work and supports rapid prototyping.
3. Practical Copilot Skills in VS Code
Hands-on demonstrations:
- Explaining unfamiliar code
- Refactoring messy code
- Generating new functions from comments
- Auto‑creating docstrings and type hints
- Creating unit tests automatically
Takeaway: Participants learn the core Copilot commands and how to use them effectively inside VS Code.
4. Building an Application with Copilot
- Generating CRUD functions for AdventureWorksLT2022
- Using product ID as a parameter
- Handling insert/update parameters
- Error handling patterns
Takeaway: Participants learn how to use Copilot for structured, multi‑step development tasks.
5. Adding a Windows Interface
- Generating Python GUI code
- Creating forms for select/update/insert/delete
- Improving UI: colours, font sizes, exit buttons
- Error handling in UI workflows
Takeaway: Participants see how Copilot can scaffold full application layers, not just backend logic.
6. Guided Practical Exercises
Exercises
- Generate a Python function from a natural‑language comment
- Refactor messy Python code using Copilot inline suggestions
- Auto‑generate docstrings and type hints
- Optimize a slow Python loop
- Create unit tests automatically
Takeaway: Participants gain confidence using Copilot in real coding scenarios.
7. Review & Q&A
- Recap of productivity gains
- Best practices for prompting
- When to trust Copilot vs. when to verify manually
- Open questions and next steps
Takeaway: Participants leave with a clear understanding of how to apply Copilot in their daily development workflow.