Building AI Agents for Production
LangChain, CrewAI, MCP, RAG — design and deploy autonomous AI agents in production. The most advanced program in our catalogue.
What you'll be able to do
Design AI agent architecture for a business use case
Build an agent with LangChain and/or CrewAI with tools and multi-step reasoning
Implement a complete RAG system (indexing, vector search, generation)
Integrate external tools via MCP (Model Context Protocol)
Deploy an agent to production with monitoring and security
Program
AI agent fundamentals and LangChain
- › Agent architecture: ReAct, Plan-and-Execute, Tool Use
- › LangChain: Models, Chains, Agents, Tools, Memory
- › Tools, Function Calling and conversational memory
- › First complete ReAct agent
RAG, MCP and multi-agents
- › RAG: full pipeline, chunking, embeddings, vector databases
- › Advanced RAG: hybrid search, re-ranking, evaluation
- › MCP: develop a server, connect to Claude
- › CrewAI: multi-agent systems with roles and processes
Production, evaluation and project
- › Deployment: FastAPI, error handling, security, guardrails
- › Monitoring: LangSmith/LangFuse, metrics, alerting
- › AI Act compliance and AI agents
- › Integration project: complete deployed agent
Tools covered
Practical info
3 to 5 days (21-35h)
Senior developers, AI/ML engineers, tech leads, software architects
Proficiency in Python, REST API basics, LLM fundamentals, Git required
4 to 8 people
15% theory / 85% practice
Ulysse Trin
Pricing
Post-training support
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Request the full program
Bespoke program, tailored to your industry. First call is free.