Generative AI Guide
Learn Generative AI from scratch: LLMs, prompts, RAG, AI agents, tools, projects, and the roadmap to becoming an AI engineer.
Start Guide ->Learn Generative AI
Choose a practical path through Generative AI fundamentals, RAG, AI agents, prompt engineering, LangChain, evaluation, and production AI systems.
AI Engineer Roadmap
Follow the complete learning path from beginner fundamentals to production AI engineering.
Open Roadmap ->Tutorial Library
RAG Pipeline Explained
A practical explanation of RAG pipelines: documents, chunks, embeddings, vector databases, retrieval, generation, citations, and evaluation.
Read Tutorial ->AI Agents Explained
Learn what AI agents are, how tool calling works, where memory fits, and how to design safer agent workflows.
Read Tutorial ->Prompt Engineering Guide
A practical prompt engineering guide covering instructions, examples, constraints, structured outputs, testing, and common mistakes.
Read Tutorial ->LLM API Tutorial
Learn how LLM APIs work: chat messages, roles, tokens, streaming responses, structured outputs, tool calling, and error handling.
Read Tutorial ->LangChain Roadmap
A practical LangChain roadmap covering messages, chains, retrievers, RAG, agents, toolkits, LangGraph state, and production workflows.
Read Tutorial ->LLM Evaluation Guide
Learn how to evaluate LLM apps with golden datasets, retrieval checks, prompt tests, human review, and production traces.
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