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Introduction to LangChain
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Classroom Contents
Comprehensive Guide to Generative AI Projects - From Basics to Advanced Applications
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- 1 Prompt Engineering for ChatGPT
- 2 Introduction to Google Gemini 1.5 Pro
- 3 Introduction to Google Gemini
- 4 Agenda of Google Gemini 1.5 Pro
- 5 Versions of Google Gemini
- 6 Introduction to Google AI Studio
- 7 Gemini Models in Google AI Studio
- 8 Tokens in Google AI Studio
- 9 Advance Settings in Google AI Studio
- 10 Temperature in Google AI Studio
- 11 Google AI Studio Left Panel Features
- 12 Vertex AI on Google Cloud
- 13 General Prompt Demo Google AI Studio
- 14 Structured Prompt in Google AI Studio
- 15 Model Tuning in Google AI Studio using System Sample
- 16 Analysing video Google AI Studio using System Sample
- 17 Google Gemini 1.5 Pro Vs Flash
- 18 Python Get and Post Method Demo
- 19 Python and Google Gemini 1.5 Pro Integration
- 20 Get API Key
- 21 What is Chatbot?
- 22 Types of Chatbots
- 23 Applications of Chatbots
- 24 Building Chatbot -Theory
- 25 Demo on Building Chatbot
- 26 Google Gemini 1.5 Pro Vs ChatGPT 4-o versions
- 27 Promot Based Trails
- 28 Prompt Trail on Problem-Solving and Technical Assistance
- 29 Generative AI
- 30 Overview of Python and Introduction to GenAI
- 31 Development Environment Setup
- 32 Generative AI Full course 2024 | All in One Gen AI Tutorial
- 33 Introduction to OpenAPI GPT API
- 34 Flask ChatGPT App
- 35 LangChain Apps
- 36 Introduction to LangChain
- 37 Agenda of LangChain
- 38 How Generative AI will transform our lives in 2023 | Automation with AI tools | ChatGPT | AI Tools
- 39 Why LangChain?
- 40 Development Environment Setup of LangChain
- 41 Demo on Library Installation
- 42 LangChain Core Concepts
- 43 LangChain Components
- 44 LangChain Case Study
- 45 Add LangChain App
- 46 LangChain App Execution
- 47 Introduction to LLMs
- 48 Limitations of LLMs
- 49 Introduction to RAG
- 50 RAG Basics Concepts and Terminology
- 51 Key Components - Retrieval and Generation
- 52 Workflow of RAG
- 53 Steps to implement RAG with LangChain
- 54 Hands-on RAG - Importing Libraries
- 55 Hands-on RAG in detail
- 56 Why are LLMs Important
- 57 Abstract of the Email Generator App
- 58 Generative AI crash course
- 59 Software Requirements for App
- 60 Implementation of the App
- 61 Executing the App
