From LLM fundamentals to production agentic systems — structured learning paths covering every layer of modern AI engineering with architecture diagrams, code examples, and real-world deployment patterns.
Each path is a deep-dive with diagrams, code examples, and production guidance.
Master transformer architecture, tokenization, prompt engineering, and large language model APIs from first principles.
Build production RAG pipelines: embeddings, vector stores, hybrid search, advanced chunking, and GraphRAG.
Design and build autonomous agents with tool use, memory, ReAct loops, LangChain, AutoGen, and OpenAI Assistants.
Multi-agent architectures, CrewAI, LangGraph, Azure AI Agent Service, and production Kubernetes deployments.
Production workflow orchestration with n8n, LangChain/LangGraph, Temporal.io durable execution, and event-driven AI pipelines.
Structured phase-by-phase journey from ML foundations to senior AI engineer — skills matrix, tools ecosystem, and project ideas.
Every layer you need to master — from raw data to production autonomous systems