AI Engineer Bootcamp 1337 | AI Automation Agent RAG Finetune

administrator June 17, 2026 Artificial Intelligence (AI), IT & SoftwareUdemy

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AI Engineer Bootcamp 1337 | AI Automation Agent RAG Finetune, AI, LLM, GenAI, OpenClaw, Hermes Agent, MCP, RAG, LangChain, LangGraph, AutoGen (AG2), ADK, A2A, Pi, Claude Code, OpenAI.

Description

This course contains the use of artificial intelligence.

Not affiliated with Anthropic, LangChain, or NousResearch.

Welcome to the most complete AI Engineering Bootcamp 🙂

This is not a theory course. From day one, you write real code, build real agents, 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
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 — 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

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

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.

Who this course is for:

Aspiring AI Engineers who want to build real-world agent systems with LangChain, LangGraph, ADK, and AG2 from scratch.
Software Developers looking to level up by adding AI automation, agents, and LLM integration to their skill set.
Prompt Engineers who want to go beyond prompting and build full agentic pipelines with memory, tools, and RAG.
Data Scientists who want to expand from analysis into building intelligent, production-ready AI systems.
MLOps / DevOps Engineers interested in deploying, evaluating, and monitoring multi-agent AI systems in production.
Generative AI Enthusiasts who want to understand how LLMs really work inside apps — chains, embeddings, RAG, fine-tuning.
AI Content Creators & No-Code Users ready to step into code and build AI tools that automate their creative workflows.
Product Managers & AI Product Builders who want hands-on understanding of what AI agents can and can’t do.
Freelancers & Entrepreneurs who want to build and sell AI automation solutions, chatbots, and agent products.
Students & Career Switchers with zero AI background who want a complete, practical path into the AI job market.
NLP Engineers who work with text data and want to integrate LLMs, embeddings, and vector search into their stack.
Researchers & Academics exploring applied AI — RAG, multi-agent systems, evaluation frameworks, and A2A protocols.
For engineers ready to move beyond one-off AI scripts and build deterministic, repeatable multi-agent workflows they can ship to production.
For developers who want a minimal, transparent coding agent they fully understand and control — without bloated prompts or framework lock-in.
AI enthusiasts and indie hackers who want to ship their own SaaS or automation tools powered by Claude — with billing, routing, Docker isolation, and OTel monitoring out of the box.
Python developers who want to build real AI agents using Anthropic’s official SDKs — from simple API calls to multi-agent systems with tools, subagents, and production deployment.
Backend engineers looking to integrate AI agents into existing infrastructure using OpenClaw & Hermes Agent as a unified communication layer between services and sub-agents.
AI enthusiasts and indie hackers who want to ship autonomous workflow automation tools powered by intelligent routing, multi-step task handling, and scalable agent orchestration.
Python developers who want to build production-ready AI messaging and routing systems — from a single agent to a multi-agent pipeline with tools, APIs, and real-time task delegation.
Developers who want to build personalized AI assistants powered by OpenClaw & Hermes Agent — with custom routing, memory, and tool integration tailored to individual user needs.
Automation engineers and indie hackers who want to automate complex workflows with OpenClaw & Hermes Agent — connecting APIs, triggering sub-agents, and orchestrating multi-step tasks without manual intervention.