AI Engineer Bootcamp 1337 | AI Automation Agent RAG Finetune

About this course

This course contains the use of artificial intelligence.

Not affiliated with Anthropic, LangChain, NousResearch, TypeSafe, NVIDIA, Google, Microsoft or 杭州深度求索人工智能基础技术研究有限公司.Welcome to the most complete AI Engineering Bootcamp :)This is not a theory course. From day one, you write real code, build real AI Agents, Agentic AI and ship real systems. Whether you're a developer, data scientist, or complete beginner — by the end you'll be able to design, build, and deploy production-grade AI systems confidently.

What you'll build:

• MCP — connect agents to GitHub, databases, filesystems, and any external tool

Conversational AI assistants with memory, tools, and streamingRAG pipelines that load PDFs, CSVs, web pages, and query them with LLMsVector RAG (Qdrant; Milvus) Hybrid RAG (BM25; BM42)Graph RAG (neo4j)Agentic RAGMulti-agent systems with orchestration patterns: Sequential, Parallel, Loop, Swarm, Supervisor

Autonomous agents using ReAct, MCTS, BeamSearch, and Tree of ThoughtsJev — a System One decision model (not a reasoning model): typed Choice, Score, and Noul answers in a single pass, for routing and guardrails instead of step by step thinking

Personalized AI assistants powered by OpenClaw & Hermes Agent (Nvidia NemoClaw OpenShell) — with custom routing, tool & API integration, sub-agent orchestration, and multi-step task delegation

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