Udemy - LangGraph for Developers - From Zero to Hero

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Udemy - LangGraph for Developers - From Zero to Hero (Size: 3.5 GB)
  Bonus Resources.txt 102.4 B
  CODE_OF_CONDUCT.md 5.1 KB
  CONTRIBUTING.md 3.3 KB
  DeepAgent
  __init__.py 0 B
  backend_memory_research_agent.py 3 KB
  filesystem_research_agent.py 1.7 KB
  get_started.py 204.8 B
  hello_world_deep_agent.py 614.4 B
  human_in_the_loop.py 1.8 KB
  notes.md 3.1 KB
  preference.txt 0 B
  research_deep_agent.py 1.4 KB
  sandbox.py 716.8 B
  skills
  langgraph-docs
  LICENSE 1 KB
  LangChain
  __init__.py 0 B
  src
  __init__.py 0 B
  agent.py 7.7 KB
  knowledge_base.py 1.4 KB
  mcp_agent.py 2.5 KB
  mcp_servers
  LangGraph
  __init__.py 0 B
  src
  __init__.py 0 B
  agents
  __init__.py 0 B
  agent_node.py 2.5 KB
  capabilities
  __init__.py 0 B
  functional
  __init__.py 0 B
  essay_review.py 716.8 B
  hello_graph.py 512 B
  workflows
  Langfuse
  PPT
  00 (A) Introduction.pptx 8.3 MB
  00 (B) About Instructor.pptx 2.8 MB
  01 Evolution of AI.pptx 20.1 MB
  02 What is Agentic AI.pptx 25.1 MB
  03 Benefits of Agentic AI.pptx 1.4 MB
  04 Agentic Design Patterns.pptx 12.9 MB
  05 Agentic Patterns for Highly Autonomous Agents.pptx 1.4 MB
  06 LangGraph.pptx 534.4 KB
  07 LangChain Vs LangGraph Vs DeepAgents.pptx 7.7 MB
  08 MCP Vs A2A.pptx 16.1 MB
  09 Langfuse.pptx 146.5 KB
  10 FastAPI.pptx 97.4 KB
  11 Conclusion.pptx 291.9 KB
  README.md 6.3 KB
  SECURITY.md 614.4 B
  env.example 409.6 B
  github
  ISSUE_TEMPLATE
  bug_report.md 819.2 B
  custom.md 102.4 B
  feature_request.md 614.4 B
  __init__.py 0 B
  get_started_with_langfuse.py 921.6 B
  __init__.py 0 B
  conditional_routing.py 921.6 B
  graph.png 10 KB
  loop_demo.py 921.6 B
  message_state_demo.py 1 KB
  reducers_demo.py 819.2 B
  subgraphs_demo.py 819.2 B
  two_step_workflow.py 716.8 B
  persistence_demo.py 4 KB
  tools_setup.py 614.4 B
  tools_setup.py 614.4 B
  __init__.py 0 B
  math.py 409.6 B
  multi_agent.py 1.6 KB
  response.json 614.4 B
  tool.py 921.6 B
  skills.md 1 KB
  sub_research_writer_agent.py 2.3 KB
  skills.py 1 KB
  Get Bonus Downloads Here.url 204.8 B
  pull_request_template.md 1.5 KB
  workflows
  7 - Let's review our learnings
  1. Final Certification Quiz LangGraph for Developers.html 52.3 KB
  8 - Conclusion
  33. Thank You!.mp4 19.6 MB
  gitignore 0 B
  python-app.yml 819.2 B
  requirements.txt 307.2 B
  ~Get Your Files Here !
  1 - Welcome
  1. Why Learn AI Agents.mp4 12.1 MB
  2 - Introduction to Agentic System
  10. MCP vs A2A.mp4 91.6 MB
  3 - LLM Provider
  11. OpenAI LLM Provider.mp4 38.7 MB
  4 - LangGraph Basics
  12. What is LangGraph.mp4 17.5 MB
  13. Your First Graph.mp4 83.9 MB
  14. Core Concepts State, Nodes, Edges & Reducers.mp4 129.9 MB
  15. Control Flow & Conditional Edges.mp4 251.2 MB
  16. Build a Tool-Calling Agent & Streaming.mp4 292.9 MB
  17. Persistence, Interrupts, Time Travel.mp4 326.8 MB
  18. Memory & Sub-Graph.mp4 130.6 MB
  19. Functional API.mp4 67 MB
  LangGraph
  __init__.py 0 B
  src
  __init__.py 0 B
  agents
  __init__.py 0 B
  __pycache__
  agent_node.py 2.6 KB
  capabilities
  __init__.py 0 B
  __pycache__
  functional
  __init__.py 0 B
  essay_review.py 819.2 B
  hello_graph.py 614.4 B
  workflows
  5 - Langfuse Basics
  20. What is Langfuse.mp4 5.7 MB
  21. Installation & Setup.mp4 50.6 MB
  22. Observability & Tracing.mp4 120.5 MB
  23. Prompt Management.mp4 35.9 MB
  24. Evaluations.mp4 51.5 MB
  6 - Capstone Project
  25. What is FastAPI.mp4 17.5 MB
  26. Project Setup and Healthcheck.mp4 331.6 MB
  27. Database Connection & Schemas.mp4 144 MB
  28. AI Agent API.mp4 133.4 MB
  29. Setting Up MCP Server.mp4 114.1 MB
  30. MCP Tool Discovery.mp4 339.1 MB
  31. Exposing MCP Tool Endpoint.mp4 139.3 MB
  32. Connecting the MCP Server with the AI Agent Client.mp4 166.2 MB
  AI_Agent_Engineering_Build_Production_Ready_Agentic_Systems-dev
  AI_Agent_Client
  __init__.py 0 B
  database
  __init__.py 0 B
  database_connection.py 716.8 B
  main.py 2.7 KB
  models
  __init__.py 0 B
  chat_history.py 409.6 B
  routers
  __init__.py 0 B
  agent_router.py 1 KB
  general_router.py 409.6 B
  schemas
  AgentQueryRequest.py 102.4 B
  __init__.py 0 B
  utils
  AI_Agent_MCP_Server
  __init__.py 0 B
  main.py 2 KB
  routers
  __init__.py 0 B
  general_router.py 1.8 KB
  tookit
  __init__.py 0 B
  tools
  __init__.py 409.6 B
  _discover.py 1.7 KB
  research_paper_analyser
  __init__.py 102.4 B
  promt.py 204.8 B
  schema.py 204.8 B
  tool.py 1.8 KB
  utils
  Architecture_Diagram
  Agentic AI-A2A.png 98.8 KB
  Agentic AI-DeepAgents.png 410.6 KB
  Agentic AI-LangChain, LangGraph, and DeepAgents Relate.png 172.3 KB
  Agentic AI-LangChain.png 246.7 KB
  Agentic AI-LangGraph.png 180.6 KB
  Agentic AI-MCP & A2A.png 147.4 KB
  Agentic AI-MCP.png 124.8 KB
  Agentic AI-Reflection with external feedback.png 139.7 KB
  Agentic AI.drawio 124 KB
  Agentic AI.png 184.6 KB
  ai-agents.png 311.3 KB
  __init__.py 0 B
  settings.py 716.8 B
  __init__.py 0 B
  prompt.py 102.4 B
  settings.py 716.8 B
  __init__.py 0 B
  conditional_routing.py 921.6 B
  graph.png 10 KB
  loop_demo.py 921.6 B
  message_state_demo.py 1 KB
  reducers_demo.py 921.6 B
  subgraphs_demo.py 819.2 B
  two_step_workflow.py 716.8 B
  persistence_demo.py 4.2 KB
  tools_setup.cpython-312.pyc 1.3 KB
  tools_setup.py 614.4 B
  tools_setup.cpython-312.pyc 1.3 KB
  tools_setup.py 614.4 B
  4. Evolution of AI.mp4 96.2 MB
  5. What is Agentic AI.mp4 77.8 MB
  6. Benefits of Agentic AI.mp4 21.9 MB
  7. Agentic Design Patterns.mp4 63.8 MB
  8. Highly Autonomous Agentic Design Patterns.mp4 72.8 MB
  9. LangChain vs LangGraph vs DeepAgent.mp4 47.2 MB
  2. About Instructor.mp4 21.8 MB
  3. Coding Resources.html 7.6 KB

Description


LangGraph for Developers: From Zero to Hero

https://WebToolTip.com

Published 2/2026
Created by Arnab Das
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Level: Intermediate | Genre: eLearning | Language: English | Duration: 33 Lectures ( 6h 16m ) | Size: 3.52 GB

Build Production-Ready Agentic AI Systems using LangGraph, LLMs, MCP & FastAPI

What you'll learn
✓ Understand agentic systems and clearly differentiate them from traditional LLM applications.
✓ Design AI agent architectures using modern agentic patterns, memory, and tool based reasoning.
✓ Build production AI agents with LangGraph, MCP pipelines, and multi-agent collaboration.
✓ Secure, evaluate, and monitor AI agents using guardrails, Langfuse, observability, authentication, and performance metrics.
✓ Deploy scalable agentic systems to the cloud using Docker, FastAPI, and real world production workflows.
✓ Architect end-to-end AI Agent APIs, from LLM integration and tool orchestration to backend connectivity and real-world system deployment.

Requirements
● Basic Python programming knowledge (functions, classes, virtual environments)
● Familiarity with REST APIs and JSON
● Fundamental understanding of LLMs or prior experience using ChatGPT or similar tools
● A laptop or desktop with internet access
● Willingness to install Python, VS Code, Pycharm and required libraries

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