Python Using AI

Set up a modern Python 3.12 environment with uv, Cursor and GitHub Copilot. Master variables, expressions, lists, dicts, tuples and sets — then use ChatGPT and Claude as a tutor to explain unfamiliar code and generate your first scripts.

Effective coding prompts, the Cursor / Copilot workflow, AI-driven debugging, code-explanation techniques and best practices for AI-assisted development. Learn how to drive an LLM like a senior engineer — context, constraints, output spec.

Conditionals, loops, comprehensions, *args/**kwargs, closures, decorators, pythonic idioms (EAFP vs LBYL, unpacking, walrus). Use AI as a 'pythonic-ness' reviewer that converts ugly code into clean, idiomatic Python.

Classes, inheritance, super(), ABCs. dataclasses, __slots__, descriptors. Modern typing (Protocol, Generics, TypeVar, Annotated), Pydantic for runtime validation, and pythonic design patterns. AI-led code review on OO design.

Automate the boring stuff. File/folder management with pathlib, PDF processing (pypdf, pdfplumber), email automation, browser automation with Playwright, and data extraction. Build a real-world AI-powered file organiser + report generator.

Pandas mastery — vectorisation, groupby, multi-index, merge/join, performance patterns. Pydantic for data quality. AI-generated insights and narrative summaries over real business datasets. Build a sales analysis pipeline end-to-end.

Matplotlib for static charts, Seaborn for statistical visuals, Plotly for interactive web charts, and Streamlit for instant dashboards. Use AI to generate viz code from a natural-language description. Build a business intelligence dashboard.

requests, httpx, BeautifulSoup, selectolax. Ethical scraping, rate limiting, retries. Consuming REST/GraphQL APIs. Build production APIs with FastAPI — routing, dependency injection, auth, request/response models, and OpenAPI docs.

asyncio fundamentals — event loop, coroutines, tasks, gather, semaphores. threading vs multiprocessing vs asyncio: when to use what. concurrent.futures. Profiling with cProfile + line_profiler. Build an async scraper for 1,000+ pages.

pytest deep dive — fixtures, parametrize, mocks, plugins. TDD with AI generating test cases. Debugging (pdb, breakpoint). Static analysis with mypy, ruff, pyright, and bandit. The professional Python engineer's quality toolkit.

OpenAI, Claude and Gemini SDKs. Function calling, structured outputs, streaming. RAG with chromadb. Build a tool-using AI agent in pure Python (planner-executor pattern, memory, tools). LangChain / LangGraph basics.

Modern packaging (uv, poetry, hatch), building wheels, publishing to PyPI. Docker for Python apps, gunicorn + uvicorn. CI/CD with GitHub Actions. Logging, monitoring, security (bandit, pip-audit). Plan → build → ship your capstone.