Self-Paced Interactive Learning

Trading AI Learning Paths

Path 01 · Intermediate · Python

Agentic AI for Trading

Build a five-agent research pipeline — Hypothesis Designer, Data Scout, Backtester, Performance Analyst, Notebook Assembler — that takes a trading idea from hypothesis to a backtested Python notebook.

17 modules · 98 lessons · ~23h

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Path 02 · Beginner · No-Code

Claude AI for Trading

Run a complete systematic-trading workflow in plain English inside Claude — source an idea, write testable rules, backtest with live market data over MCP, and paper trade it on Alpaca.

15 modules · 75 lessons · ~20h

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Direct files: AgenticAIForTrading.htm · claudefortrading.htm