Comprehensive Guide to Generative AI Projects - From Basics to Advanced Applications

Overview

Explore top generative AI projects in this comprehensive 5-hour video tutorial. Dive into Google Gemini Pro 1.5, comparing its features with other models. Learn to build AI applications using Python, from environment setup to app development. Understand LangChain and its role in creating AI-driven solutions. Explore Retrieval Augmented Generation (RAG) and its impact on improving language models. Conclude with steps to build a functional LLM app for Android mobile devices. Cover fundamental AI concepts including machine learning, neural networks, and deep learning. Gain hands-on experience with prompt engineering, chatbot development, and integration of various AI tools and platforms. Explore practical applications of generative AI in business and problem-solving scenarios.

Syllabus

Prompt Engineering for ChatGPT
Introduction to Google Gemini 1.5 Pro
Introduction to Google Gemini
Agenda of Google Gemini 1.5 Pro
Versions of Google Gemini
Introduction to Google AI Studio
Gemini Models in Google AI Studio
Tokens in Google AI Studio
Advance Settings in Google AI Studio
Temperature in Google AI Studio
Google AI Studio Left Panel Features
Vertex AI on Google Cloud
General Prompt Demo Google AI Studio
Structured Prompt in Google AI Studio
Model Tuning in Google AI Studio using System Sample
Analysing video Google AI Studio using System Sample
Google Gemini 1.5 Pro Vs Flash
Python Get and Post Method Demo
Python and Google Gemini 1.5 Pro Integration
Get API Key
What is Chatbot?
Types of Chatbots
Applications of Chatbots
Building Chatbot -Theory
Demo on Building Chatbot
Google Gemini 1.5 Pro Vs ChatGPT 4-o versions
Promot Based Trails
Prompt Trail on Problem-Solving and Technical Assistance
Generative AI
Overview of Python and Introduction to GenAI
Development Environment Setup
Generative AI Full course 2024 | All in One Gen AI Tutorial
Introduction to OpenAPI GPT API
Flask ChatGPT App
LangChain Apps
Introduction to LangChain
Agenda of LangChain
How Generative AI will transform our lives in 2023 | Automation with AI tools | ChatGPT | AI Tools
Why LangChain?
Development Environment Setup of LangChain
Demo on Library Installation
LangChain Core Concepts
LangChain Components
LangChain Case Study
Add LangChain App
LangChain App Execution
Introduction to LLMs
Limitations of LLMs
Introduction to RAG
RAG Basics Concepts and Terminology
Key Components - Retrieval and Generation
Workflow of RAG
Steps to implement RAG with LangChain
Hands-on RAG - Importing Libraries
Hands-on RAG in detail
Why are LLMs Important
Abstract of the Email Generator App
Generative AI crash course
Software Requirements for App
Implementation of the App
Executing the App