Gen AI Agentic Track
Completed by Mirko Romay on October 13, 2025
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Learning objectives
- Design and implement agentic AI systems using LangChain, LangGraph, and other frameworks to build intelligent, self-improving agents capable of reasoning and collaboration.
- Develop AI agents with retrieval-augmented generation (RAG) and LangChain technologies, applying prompt engineering and in-context learning to generate accurate responses and solve complex problems.
- Build and manage agent memory systems using LLMs, leveraging frameworks like Letta to extend memory beyond context windows and enable advanced reasoning capabilities.
- Orchestrate multi-agent systems using frameworks such as CrewAI and BeeAI, implementing design patterns and workflow strategies to create scalable and efficient AI applications.
Learning content completed
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