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Starts 8 June 2025 21:43
Ends 8 June 2025
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Building Agentic and Multi-Agent Systems with LangGraph
Master the development of agentic and multi-agent LLM applications using LangChain and LangGraph. Learn to build RAG systems, implement reasoning cycles, and create complex multi-agent workflows for advanced AI applications.
Open Data Science
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Open Data Science
2544 Courses
1 hour 59 minutes
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Overview
Master the development of agentic and multi-agent LLM applications using LangChain and LangGraph. Learn to build RAG systems, implement reasoning cycles, and create complex multi-agent workflows for advanced AI applications.
Syllabus
- Introduction to Agentic Systems
- Introduction to LangChain and LangGraph
- Building RAG Systems
- Implementing Reasoning Cycles
- Creating Multi-Agent Workflows
- Advanced Topics in Multi-Agent Systems
- Hands-On Projects
- Conclusion and Future Directions
Overview of Agentic and Multi-Agent Systems
Key Concepts: RAG systems, reasoning cycles, and workflows
Fundamentals of LangChain
Basics of LangGraph
Integration of LangChain and LangGraph
Understanding Retrieval-Augmented Generation (RAG)
Designing RAG Architectures with LangGraph
Case Studies and Practical Examples
Principles of Reasoning in AI Systems
Developing Reasoning Mechanisms using LangGraph
Debugging and Optimizing Reasoning Cycles
Designing Workflows for Multi-Agent Systems
Coordination and Communication between Agents
Handling Complex Interactions and Dependencies
Scalability and Efficiency in Multi-Agent Systems
Security and Ethical Considerations
Emerging Trends and Technologies in Multi-Agent AI
Project 1: Building a Simple RAG System
Project 2: Developing a Reasoning Cycle
Project 3: Implementing a Complex Multi-Agent Workflow
Summary of Key Concepts
Opportunities for Further Learning and Development
Subjects
Computer Science
