Roadmap & Module Progression

Estimated time to read: 2 minutes

This page outlines the curriculum and sequential projects designed to build deep, production-grade expertise in AI systems.

🗺️ Learning Path

The roadmap is structured sequentially. Each module serves as a mathematical or architectural foundation for the next.

flowchart TD A[01. LLM Foundations] --> B[02. Prompt Engineering] B --> C[03. Structured Outputs] C --> D[04. RAG Systems] D --> E[05. OCR & Document Intelligence] E --> F[06. AI Agents] F --> G[07. Model Context Protocol] G --> H[08. LLMOps & Observability] H --> I[09. Fine-Tuning] I --> J[10. Multimodal AI] J --> K[11. Financial AI Systems] style A fill:#4CAF50,stroke:#388E3C,color:#fff style B fill:#FF9800,stroke:#F57C00,color:#fff style C fill:#FF9800,stroke:#F57C00,color:#fff style D fill:#FF9800,stroke:#F57C00,color:#fff style E fill:#9C27B0,stroke:#7B1FA2,color:#fff style F fill:#9C27B0,stroke:#7B1FA2,color:#fff style G fill:#9C27B0,stroke:#7B1FA2,color:#fff style H fill:#F44336,stroke:#D32F2F,color:#fff style I fill:#F44336,stroke:#D32F2F,color:#fff style J fill:#2196F3,stroke:#1976D2,color:#fff style K fill:#009688,stroke:#00796B,color:#fff

📊 Module Classification & Complexity

To optimize the learning curve, each topic is classified by difficulty level and estimated duration.

Module	Topic	Difficulty	Est. Timeline	Focus Area
01	Foundations & Math of LLMs	🟢 Easy	2 weeks	BPE/WordPiece, Embedding Space, Attention Blocks
02	Prompt Engineering	🟢 Easy	1 week	Few-shot, COT, XML/JSON schemas
03	Structured Outputs	🟢 Easy	1 week	Pydantic validation, Instructor, Guardrails
04	RAG (Retrieval-Augmented)	🟡 Medium	3 weeks	Hybrid Search, Chunking, Re-ranking, Vector DBs
05	OCR & Parsing	🟡 Medium	2 weeks	Unstructured data extraction, Docling, LayoutLM
06	AI Agents & State Machines	🟠 Hard	4 weeks	LangGraph, Reasoning loops, Memory, Orchestration
07	MCP (Model Context Protocol)	🟠 Hard	2 weeks	API endpoints, Secure tool sandboxing, Tool Registry
08	LLMOps	🔴 Expert	4 weeks	Monitoring (Phoenix, LangSmith), Security, Evals
09	Fine-Tuning	🔴 Expert	3 weeks	LoRA, QLoRA, PEFT, Distillation

🧭 Project Architecture Principles

Every project implemented throughout this roadmap must strictly adhere to the following delivery standards: - Zero Placeholder Code: All APIs, data structures, and tests must be complete and executable. - Strict Linting & Formats: Pre-commit checks via Black, Isort, and Ruff must pass seamlessly. - Robust Verification: Every module must contain reproducible benchmark scripts and at least 90% pytest unit test coverage. - Clean Documentation: Code rationales, mathematical proofs, and trade-off considerations must be logged inside the respective module's README.md.