AI Python Lab

This 6-week cohort-based course equips you with the skills to harness Python for modern AI applications. You’ll learn how to build intelligent, asynchronous systems and leverage tools like OpenAI, Pydantic, MCP, and AI agents.

Week 1: Prompting Basics, Copilot, and AI in Jupyter
Kickstart your journey by mastering the foundations of AI interaction. Learn to craft effective prompts to get precise results from AI systems. Harness the power of GitHub Copilot in VSCode for smarter coding and integrate AI seamlessly into Jupyter Notebooks for an enhanced data workflow.

• Key Takeaways:

  • Write effective prompts for optimal AI responses.

  • Use Copilot to supercharge your productivity.

  • Blend AI with your Python workflow in Jupyter.

Week 2: Pydantic and Structured Output
Move beyond raw outputs by leveraging Pydantic to define, validate, and structure AI-generated data. Ensure your applications are not just intelligent but also reliable and production-ready.

Key Takeaways:

• Validate AI responses with precision.

• Design structured data pipelines for real-world applications.

• Bridge AI and business logic seamlessly.

Week 3: Using Agents
Learn best practices for coding agents. Explore how they can be used for non-coding tasks. Use the popular Aider agent with any LLM (OpenRouter).

Key Takeaways:

• Learn the RECR process

• Work with any LLM

• Create guidelines for agents

Week 4: MCP
Learn how to call existing MCP servers, then design your own MCP server.

Key Takeaways:

• Connect to and consume MCP content

• Build custom MCP servers to serve your own data and tools

Week 5: Async Clients and Servers
Discover how asynchronous programming transforms AI applications. Build efficient, scalable clients and servers to handle real-time communication, ensuring your applications are fast and responsive.

Key Takeaways:

• Master async/await for non-blocking operations.

• Develop robust, scalable AI-driven services.

• Build real-time AI systems with asynchronous programming.

Week 6: Packaging and Final Project
Bring everything together by packaging your AI-powered Python application. Learn best practices for creating reusable, distributable tools and complete a capstone project to showcase your skills.

Key Takeaways:

• Package Python projects for scalability and reuse.

• Deliver polished, production-ready AI applications.

• Create a capstone project to demonstrate your expertise.

Every week builds on the last, combining foundational skills with advanced techniques to ensure you finish the course equipped to build powerful, production-ready AI systems.

• On-Demand: Flexible, self-paced access to all course materials.

• Live Cohort + Coursework: Join live sessions with hands-on projects and peer collaboration.

• Private Coaching: Includes live cohort benefits plus 1:1 sessions for personalized feedback and project support.