Complete AI Training
Sign inGet started

Certification

Certification in Developing AI Agents & Workflows with LangGraph and Python

Get certified in LangGraph for Python to demonstrate your ability to build AI agents, design chatbots, implement intelligent workflows, manage state, integrate tools, and deliver retrieval-based Q&A solutions efficiently.

Exam of 10 to 20 questionsCertificate for LinkedInBeginner · Intermediate
IT and developmentProduct developmentEducation
Take the exam Share

The exam

Take the certification exam

Multiple-choice questions about the course. Pass with 70% or more and your certificate is issued at once, with a public page and an "Add to LinkedIn" button.

Become a memberAlready a member? Sign in

What the exam covers

2 questions from each of the 15 chapters of the course

20 multiple-choice questions, drawn fresh for every attempt. Pass with 70% or more.

  1. 01Introduction and type annotations8:35
  2. 02Elements of LangGraph12:33
  3. 03Agent 1: hello world graph11:14
  4. 04Agent 2: multiple inputs11:05
  5. 05Agent 3: sequential graph13:10
  6. 06Agent 4: conditional graph16:32
  7. 07Agent 5: looping graph16:10
  8. 08AI agent 1: simple bot14:39
  9. 09AI agent 2: chatbot with memory19:22
  10. 10AI agent 3: ReAct intro9:08
  11. 11AI agent 3: ReAct code16:18
  12. 12AI agent 4: drafter intro2:13
  13. 13AI agent 4: drafter code21:10
  14. 14RAG agent14:06
  15. 15Testing and outro3:36
About the course

The "LangGraph for Beginners: Build AI Agents & Workflows with Python (Video Course)" certification provides a practical foundation for creating advanced AI agents using Python and LangGraph. By mastering these skills, you'll gain increased productivity, a competitive edge, and the adaptability required for a future-proof career in AI development. Enroll now to unlock higher income potential and confidently build intelligent chatbots and automated workflows.

This certification covers the following topics:

  • Foundational Python Concepts for LangGraph
  • The Core LangGraph Elements: State, Nodes, Runnables, and Messages
  • Building Basic Graph Structures in LangGraph
  • Handling Multiple Inputs and Data Types in the State
  • Sequential Graphs and Edges: Orchestrating Flow
  • Conditional Graphs and Routing Logic: Making Decisions in the Workflow
  • Looping in LangGraph: Repeating Steps Until a Condition is Met
  • Integrating LLMs into Graphs: Building AI Agents
  • Managing Conversation History and Memory with Sequence and Reducers
  • Building ReAct Agents: Reasoning and Acting in LangGraph
  • Retrieval Augmented Generation (RAG) Agents: Answering with External Knowledge
  • Robustness and Best Practices When Building LangGraph Agents