What you'll Learn
-
Master the fundamentals of multi-agent communication for efficient task-solving through agent collaboration.
-
Gain hands-on experience using LangGraph to build and manage collaborative multi-agent systems.
-
Develop skills in building research & data visualization using multi-agent systems
About the Instructor
Dipanjan Sarkar - Head of Community and Principal AI Scientist, Analytics Vidhya

Who Should Enroll?
-
AI practitioners, software developers, and system architects aiming to deepen their understanding of multi-agent systems.
-
Learners enthusiastic about entering the world of collaborative AI systems and mastering LangGraph to lead innovative projects in technology.
FAQ
-
What is LangGraph?
LangGraph is a framework designed to simplify the creation of collaborative multi-agent systems by leveraging graph-based structures for efficient communication and coordination.
-
What are the key components of LangGraph?
LangGraph is built around nodes (agents), edges (communication), and tasks. Nodes represent agents with specific roles, edges define interactions, and tasks output.
-
What is LangGraph, and how is it different from LangChain?
LangGraph is an advanced framework built on LangChain, focusing on structured workflows, graph-based chaining, and improved modularity for building complex LLM-driven systems.
-
Will I get a certificate of completion?
Yes, a certificate will be awarded upon successful completion of the course and assessments.
-
Does the course include hands-on projects?
Yes, the course includes practical, hands-on projects where you’ll build a a collaborative muti-agent system with LangGraph.