Gen AI Agentic Track
Completed by Daniel Hernandez on December 31, 2025
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Badge ID: WzGNTC8GTASxjUwvBqwErw
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Learning objectives
- Design and implement agentic AI systems using LangChain and LangGraph, focusing on memory, iteration, and conditional logic.
- Develop AI agents with retrieval-augmented generation (RAG) and LangChain, integrating large language models for accurate responses.
- Build and manage agent memory systems using Letta framework, enhancing reasoning capabilities and persistent memory.
- Create autonomous multi-agent systems using frameworks like LangGraph, CrewAI, BeeAI, and AG2, applying orchestration strategies and workflow patterns.
Skills learned
- Software Design Patterns
- Large Language Modeling
- Record Keeping
- Artificial Intelligence
- Computational Logic
- Application Frameworks
- Business Process Automation
- Agentic systems
- Collaborative Software
- ChatGPT
- OpenAI
- Information Architecture
- Data Science
- Document Management
- Data Governance
- Software Design
- Software Development
- Skills section collapsed. Showing 8 of 17 skills.
Learning content completed
Some of the content and skills presented have been contributed by the content provider.