A 95-lesson, code-first path from Python and LLM fundamentals to production-grade, auditable AI agents for finance, healthcare and legal. This repository holds the working code for the first lessons. The full lessons, with architecture diagrams and walkthroughs, are published in the newsletter.
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| Lesson | Code | |
|---|---|---|
| Lesson 1 | Python Setup for AI | lesson1/ |
| Lesson 2 | Advanced Python & Libraries | lesson2/ |
| Lesson 3 | Transformer Architecture Deep Dive | lesson3/ |
| Lesson 4 | Understanding LLM Parameters | lesson4/ |
| Lesson 5 | The Model Landscape & Selection | lesson5/ |
- Foundations: Python for AI, transformers, LLM APIs, agent theory, memory, prompting, context engineering
- Building Blocks: tool use, RAG, vector databases, retrieval optimization, evaluation
- Agentic Reasoning: ReAct, self-correction, planner, retriever, validator and synthesizer agents
- Multi-Agent Systems: AutoGen, CrewAI, coordination strategies, enterprise orchestration
- Enterprise MLOps: CI/CD, serving, monitoring, guardrails, cost, canary deployments
- Vertical Case Studies and Capstone: finance, healthcare and legal agents, governance, red teaming, the VAIA capstone
Paid subscribers get all 95 lessons in full, the complete code for every lesson in a private repository, and the other courses in the newsletter: Hands-On AI Agent Mastery and Production AI Engineering.
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