This video is your introduction to understanding Generative AI. We explain what Generative AI is, how it works, and its benefits, while also touching on ethical aspects. Discover Large Language Models like GPT and learn practical prompting techniques to build your own LLM app for Android. Explore top AI tools like ChatGPT and GitHub Copilot. Learn advanced concepts like Langchain and RAG. With demos and case studies, this video will give you the skills to build advanced AI applications. Watch now and level up your AI journey!

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Topics covered:
00:00:00 Introduction
00:01:39 Introduction to Generative AI
00:10:51 Benefits of generative AI
00:12:12 The future of generative AI
00:13:22 Ethical considerations on generative AI
00:15:09 Introduction and phases of the LLM
00:27:57 Introduction to the OpenAPI GPT API
00:36:22 Claude 3.5 Sonnet
00:52:58 Claude Artifacts
00:53:52 Demo for Claude Artifacts
01:00:12 Use cases by Claude
01:02:25 Demo for Claude Sonnet
01:18:18 GPT 4o Mini and uses
01:20:26 Why GPT 4o Mini
01:21:39 Features of GPT 4o Mini
01:22:45 Difference between GPT 4o and GPT 4o Mini
01:24:26 Demo on the Playground, Dashboard, Docs and API References tabs
01:29:06 Playground and billing settings prompt
01:31:22 Version of Google Gemini
01:38:10 General prompt demo Google AI Studio
01:40:33 Structured prompt in Google AI Studio
01:46:01 Model optimization in Google AI Studio using a system example
01:48:28 Additional data import options in Google AI Studio using System Sample
01:51:30 Email Generator App Summary
01:51:55 Software requirements for app
01:54:15 Implementation of the app
02:03:43 Running the app
02:06:28 Generative AI Popular Tools
02:06:57 ChatGPT
02:07:13 Github Copilot
02:07:26 Claude
02:07:41 Twins
02:08:27 Basics of Prompt Engineering
02:30:02 ChatGPT Basics
02:31:06 Command prompt demonstration on ChatGPT
02:34:37 Python app with ChatGPT 4o
02:41:59 Using ChatGPT 4o for statistical analysis
02:49:08 Command prompt demonstration with ChatGPT 4-o
02:51:12 Executing the portfolio website code
02:25:27 Introduction to Github and Github Copilot
03:08:47 Practical session on Github Copilot
03:41:34 Introduction of Claude
03:53:24 Fast development and installation Claude
04:05:03 Practical experience Claude
04:19:13 Program for Tic-Toe game with Claude
04:21:10 Claude 2 API
04:28:37 Integration of Python and Gemini 1.5 pro
04:35:20 Chatbot with Gemini 1.5 pro
04:53:12 Generative AI applications
05:06:33 Flask ChatGPT App
05:25:30 Flask text-to-image app
05:27:36 Demo – Flask text-to-image app
05:36:24 Introduction to Langchain
05:40:18 Why LangChain?
05:45:30 Setting up the LangChain development environment
05:47:04 Library installation demo
05:49:29 LangChain core concepts
05:54:22 LangChain components
06:00:23 LangChain Case Study
06:09:12 Limitations of LLMs
06:11:04 Introduction to RAG
06:18:08 RAG basics, concepts and terminology
06:29:41 Key components of RAG – recovery and generation
06:38:11 RAG workflows and applications
07:04:17 Hallucinations in RAG
07:12:25 Steps to implement RAG with LangChain
07:25:40 RAG in detail

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