Python Mentor for Algo Trading

Starting from zero coding knowledge, I want to master Python well enough to design, back-test, and deploy my own algorithmic stock-market strategies. The learning path has to begin at absolute basics—installing Python, understanding syntax and data types—and progress methodically toward advanced topics such as object-oriented programming, vectorised analysis with pandas and NumPy, back-testing frameworks like Backtrader or Zipline, broker/API integration (yfinance, Alpaca, Alpha Vantage), and finally live execution.

The format that suits me best is a blend of short live sessions (Zoom, Google Meet, or similar) and hands-on homework. After each module I’ll submit code for review so I can correct mistakes early and build solid habits.

Key milestones I need covered:

• Environment setup on Windows: Python 3.x, VS Code or Anaconda, Git
• Core Python foundations: variables, control flow, functions, classes
• Data handling & visualisation: pandas, NumPy, Matplotlib/Seaborn
• Financial data acquisition & cleaning through web APIs
• Strategy logic, position sizing, risk management principles
• Back-testing, optimisation, performance metrics and reporting
• Deployment first to paper-trading, then to a live broker
• Best practices: virtual environments, version control, unit tests, PEP-8 style

Acceptance criteria
1. I can write clean, documented Python code unaided.
2. I can fetch, analyse, and visualise historical market data.
3. I can back-test at least two strategies and interpret the results.
4. I can run a functioning trading bot in a paper or live environment.

Please outline your teaching approach, estimated timeline, and any relevant algorithmic-trading projects you’ve completed. I’m ready to begin immediately and will dedicate the required study time between sessions.