AI Engineer Bootcamp 1337 | AI Automation Agent RAG Finetune

Agentic AI Agent LLM GenAI OpenClaw Hermes MCP RAG LangChain LangGraph AutoGen ADK A2A Pi Claude OpenAI NVIDIA AIOps RL

Description

This course contains the use of artificial intelligence.

Not affiliated with Anthropic, LangChain, NousResearch or NVIDIA.

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 streaming

• RAG pipelines that load PDFs, CSVs, web pages, and query them with LLMs

  • Vector RAG (Qdrant; Milvus)

  • Hybrid RAG (BM25; BM42)

  • Graph RAG (neo4j)

  • Agentic RAG

• Multi-agent systems with orchestration patterns: Sequential, Parallel, Loop, Swarm, Supervisor

• Autonomous agents using ReAct, MCTS, BeamSearch, and Tree of Thoughts

• 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

• Cross-framework agent networks via A2A protocol — connecting ADK, LangChain, LangGraph, and AG2

• Production-ready systems with guardrails, evaluation, observability, and HITL

• Fine-tuning with Unsloth fast and VRAM-efficient LLM training with support for RL/RLHF methods (GRPO, PPO, DPO, ORPO, KTO) for reasoning and preference alignment.

Technologies covered:

• Python — syntax, data types, functions, object-oriented programming, file handling, virtual environments.

• LangChain — LCEL chains, RAG, memory, MCP, agents

• LangGraph — stateful graphs, persistence, Time Travel, Send API, Subgraphs

• Pi — skills, extensions, slash commands, session trees, sub-agent patterns, JSONL branching

• Archon — YAML pipelines, harness engineering, deterministic multi-agent orchestration

• Anthropic SDK & Claude Agent SDK — Client SDK, Tool Use, streaming, prompt caching, Claude Agent SDK, subagents, hooks, MCP

• OpenClaw & Hermes Agent — messaging routing, tool & API integration, sub-agent orchestration, multi-step task delegation, personalized assistants, workflow automation

• AG2 (AutoGen) — GroupChat, CaptainAgent, ReasoningAgent, DocAgent

• Google ADK — callbacks, plugins, artifacts, evaluation, UserSimulator

• A2A Protocol — agent interoperability across all frameworks

• Unsloth — fast LoRA/QLoRA fine-tuning, memory-efficient training, model quantization, export to GGUF/vLLM

Every module follows a hands-on structure:
each lesson has working code, real tasks, quizzes, and a final project that ties everything together.

By the end of this course, you won’t just understand AI — you’ll build it.

P.S.

The course is currently in early access mode — 3 modules are already available.

Get in now at the lowest price. As new modules are added, the price will increase. The earlier you enroll, the more you save.

Lock in your spot today before the next price bump.

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