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Udemy - From Knowledge Graph Assistant to Agentic AI with LangGraph

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Added 1 day ago by freecoursewb in Other
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Udemy - From Knowledge Graph Assistant to Agentic AI with LangGraph (Size: 3.2 GB)
  Bonus Resources.txt 102.4 B
  Get Bonus Downloads Here.url 204.8 B
  ~Get Your Files Here !
  1 - Introduction
  1 - Enterprise_Multi_Agent_AI_Course_Introduction_Guide.pdf 6.9 KB
  1 - Enterprise_Multi_Agent_Healthcare_AI_Introduction_20_Slides (1).pptx 46.3 KB
  1 - Glossary- Part3.pdf 138.9 KB
  1 - Introduction.mp4 60.3 MB
  2 - M2 Building the Enterprise Agentic AI Architecture
  2 - Handbook_ Knowledge Graph based Agentic AI System.pdf 684 KB
  2 - M2 Building the Enterprise Agentic AI Architecture.mp4 152.5 MB
  2 - Module-2.pdf 112.2 KB
  2 - Module_2_Instructor_Slide_Deck_40_Slides.pptx 62.5 KB
  3 - Theory Langgraph Tutorial
  10 - Memory.mp4 35.4 MB
  3 - Langgraph-200 QnA.pdf 11.3 MB
  3 - Why Langgraph.mp4 200.6 MB
  4 - Langgraph State.mp4 41.8 MB
  4 - System Architecture
  11 - System Design.mp4 257.1 MB
  12 - Four Important Concepts.mp4 36.2 MB
  13 - AgentState.mp4 253.3 MB
  14 - Planner Agent.mp4 184.1 MB
  15 - Ontology Agent.mp4 189.3 MB
  16 - Query & Validation Agents with Retry.mp4 232.6 MB
  17 - ResponseAgent.mp4 129.2 MB
  18 - Memory and Graph building.mp4 210.4 MB
  19 - Guardrails.mp4 76.6 MB
  20 - RBAC & Multitenancy.mp4 177.5 MB
  21 - Cost tracking, Observability & Monitoring.mp4 147.1 MB
  22 - Offline Evaluation.mp4 128.5 MB
  23 - Asynchronous Processing & Final Demo.mp4 223.3 MB
  5 - Capstone Project
  24 - Capstone Project.mp4 127.1 MB
  24 - Capstone_Project_Guide_Compact.pdf 3.1 KB
  5 - Nodes and Edges.mp4 104.7 MB
  6 - Conditional Routing.mp4 32.2 MB
  7 - Parallel Execution.mp4 77.2 MB
  8 - Checkpointing & Persistence.mp4 93.1 MB
  9 - Interrupt & Human in the Loop.mp4 87 MB

Description


From Knowledge Graph Assistant to Agentic AI with LangGraph
https://WebToolTip.com
Published 8/2026

MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch

Language: English | Duration: 4h 51m | Size: 3.19 GB
Build enterprise-grade multi-agent AI systems using LangGraph, Knowledge Graphs, RAG, Neo4j, Human-in-the-Loop, Memory,
What you'll learn

Build a multi-agent AI Assistant using LangGraph with Planner, Ontology, Retrieval, Insight, and Response agents.

Integrate Knowledge Graphs, GraphRAG, and LLMs to deliver accurate, explainable, and context-aware AI responses.

Implement agent orchestration, memory, tool calling, and human-in-the-loop workflows for enterprise AI assistants.

Monitor, trace, and evaluate AI agents using LangSmith to debug, optimize, and improve production-ready AI systems.
Requirements

Prior knowledge of Semantic Web or Knowledge Graphs is required.

A willingness to learn Ontology Engineering and Semantic Web technologies based Agentic AI system

A computer with at least 8 GB RAM (16 GB recommended)

Advanced programming language in Python.

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