# Generative AI Learning Roadmap Docs

This folder turns the main roadmap into a modular learning guide. Use the root
`README.md` for the broad resource catalog, then use these docs for deeper
topic-by-topic study.

## Start Here

- [How to Use This Roadmap](00-introduction/how-to-use-this-roadmap.md)
- [Career Paths & Portfolio Guide](00-introduction/career-and-portfolio.md)
- [README Deep Analysis](roadmap-analysis.md)
- [Link and Content Quality Audit](link-audit.md)
- [Roadmap v2 Overview](../ROADMAP_V2.md)

## Core Foundations

- [Mathematics for AI](01-scientific-foundations/mathematics.md)
- [Statistics for AI](01-scientific-foundations/statistics.md)
- [Machine Learning Foundations](02-machine-learning-foundations/machine-learning.md)
- [Transformers](03-deep-learning-transformers/transformers.md)

## Generative AI Engineering

- [Embeddings](04-llm-engineering/embeddings.md)
- [Tokenization](04-llm-engineering/tokenization.md)
- [Fine-Tuning](04-llm-engineering/fine-tuning.md)
- [Prompt Engineering](04-llm-engineering/prompt-engineering.md)
- [LLM Evaluation](04-llm-engineering/evaluation.md)
- [Efficient Inference](04-llm-engineering/efficient-inference.md)
- [Retrieval-Augmented Generation](05-rag-systems/rag-overview.md)
- [Advanced RAG Patterns](05-rag-systems/advanced-rag.md)
- [AI Agents](06-ai-agents/agents.md)
- [AI Agent Patterns](06-ai-agents/agent-patterns.md)
- [LLMOps and AI Infrastructure](07-ai-infrastructure/llmops.md)
- [Observability](07-ai-infrastructure/observability.md)

## Applied AI Tracks

- [Open Source AI Ecosystem](08-open-source-ai/open-source-ai.md)
- [Enterprise AI Governance](09-enterprise-ai/governance.md)
- [Multimodal AI](10-multimodal-ai/multimodal.md)
- [AI Product Engineering](11-ai-product-engineering/copilots.md)
- [AI for DevOps and SRE](12-real-world-use-cases/devops-sre.md)
- [AI for Recommender Systems](12-real-world-use-cases/recommender-systems.md)
- [AI Tools and Frameworks](13-tools-and-frameworks/tools-and-frameworks.md)

## How to Extend These Docs

When adding a new topic file, keep the structure consistent:

1. Start with why the topic matters.
2. List core concepts in learning order.
3. Add a small set of high-quality resources.
4. Include practical projects or real-world relevance.
5. Link related roadmap topics.