Published 10/2024
MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz
What you’ll learn
Explore Lang graph and Build Agentic Applications
Learn Generative AI using Langchain and Lang Graph
Explore Lang graph and Build Agentic Applications
Provides End to end tutorial for LangChain
Requirements
Basic python programming and NLP
Description
Overview
Section 1: Introduction
Lecture 1 Introduction
Section 2: Generative AI & LLMs: A Comprehensive Guide
Lecture 2 Generative AI
Lecture 3 LLM
Section 3: Introduction to LangChain
Lecture 4 LangChain FrameWork
Lecture 5 LangChain Dataflow
Section 4: Setting Up Environment
Lecture 6 Python Installation
Lecture 7 LangChain and LangGraph Installation
Lecture 8 Setting up OpenAI Account
Lecture 9 Setting up Jupyter notebook
Lecture 10 Setting API Key in Environment File
Section 5: Tools and Agents
Lecture 11 What is Tools
Lecture 12 Types of Tools
Lecture 13 Built-in Tools
Lecture 14 Components of a Tool
Lecture 15 Custom Tools
Lecture 16 Agents
Lecture 17 ReAct Agent
Lecture 18 ReAct Agent in detail
Lecture 19 Building ReAct Agent
Lecture 20 Disadvantages of Agent
Section 6: Introduction to LangGraph
Lecture 21 What is LangGraph
Lecture 22 Key Features of LangGraph
Lecture 23 LangGraph in Action: A Real-World Example
Lecture 24 Salvation by Multi-Agent Approach
Lecture 26 Optimizing Decisions with Cycles and Persistence
Lecture 27 Interactive and Real-Time Systems
Lecture 28 LangGraph’s Inspiration
Section 7: LangGraph Key Terminologies
Lecture 29 Introduction to LangGraph World
Lecture 30 Understanding State in LangGraph
Lecture 31 State Definition in Python
Lecture 32 Node Activation and Execution
Lecture 33 Understanding Edges : Connecting the Dots
Lecture 34 Exploring State Graph: Managing Communication and Workflow
Lecture 35 Enhancing AI Interactions with Message Graph
Section 8: Creating Your First Graph
Lecture 36 First Graph Preview
Lecture 37 Building a basic Chatbot
Lecture 38 Enhancing Chatbot with Tools
Section 9: Introducing RAG World
Lecture 39 Introduction to RAG
Lecture 40 RAG Pipeline
Lecture 41 Components of RAG
Section 10: Real-world applications – RAG
Lecture 42 Simple RAG App Overview
Lecture 43 Building a Retriever
Lecture 44 Agentic RAG : App Overview
Lecture 45 Building Agent Node
Lecture 46 Buildng Generate Node
Lecture 47 Constructing Graph
Lecture 48 Visualize the RAG Graph
Lecture 49 Experiment the RAG
Section 11: Conclusion
Lecture 50 Conclusion
Who is interested to develop GenAI Application using LangGraph
