Master Generative Ai – Build Ai Apps – Beginner Friendly

What you'll learn
Helps you harness the power of Generative AI to create innovative applications that boost creativity and streamline processes.
By the end of the course, you will be proficient in building real-world applications using Generative AI technologies
Explore cutting-edge concepts that can be applied to your Generative AI projects
Master the foundations and advanced strategies of Generative AI, equipping you to deliver high-impact, AI-powered applications
Requirements
A little programming / coding knowledge is required
Curiosity to learn AI field
Description
Unlock the Power of Generative AI: Master the Art of Building Revolutionary AI ApplicationsReady to tap into the full potential of Generative AI and reshape the landscape of AI-powered applications? This course is designed to take you from beginner to expert, empowering you with the skills to build innovative AI apps using cutting-edge tools like Hugging Face, LLAMA 2, OpenAI, and Google Gemini Pro.Generative AI Apps and LLM Projects!Engage in hands-on projects that will transform your expertise, including:Project 1: Develop a dynamic question-answering application using the unparalleled capabilities of Generative AI with Hugging Face Spaces, Google Gemini Pro, and OpenAI.Project 2: Build an interactive conversational bot using LangChain and OpenAI, creating personalized and engaging user experiences.Project 3: Create an AI-powered educational app tailored for children, facilitating the discovery of related objects to spark learning and creativity.Project 4: Design a marketing campaign app that leverages AI to craft persuasive sales copy, boosting brand visibility and sales.Project 5: Construct a ChatGPT clone with an advanced summarization feature, offering a versatile and engaging chatbot experience.Course Highlights:Master the power of Generative AI, including cutting-edge technologies like Google Gemini Pro, Hugging Face, and OpenAI.Create scalable AI apps by leveraging LLMs, LangChain, and cognitive data sources.Build modern AI applications with front-ends using Streamlit, all while learning Python and its application in Generative AI.Unlock the limitless potential in your AI projects with real-world applications and hands-on experience that will set you up for success in this rapidly growing field.
Overview
Section 1: Introduction
Lecture 1 Generative AI Introduction
Lecture 2 What is LangChain?
Lecture 3 Let's understand the LangChain benefits
Lecture 4 Guidelines For Source Code
Section 2: HuggingFace Introduction
Lecture 5 HuggingFace Intro & Access Token Generation
Section 3: OpenAI Introduction
Lecture 6 What is OpenAI?
Lecture 7 OpenAI API Key Generation
Section 4: Demo & Working Environment Setup
Lecture 8 Project - Implementation Demo
Lecture 9 Anaconda Installation
Section 5: Langchain - Models Module Concept
Lecture 10 LangChain's Modules Overview
Section 6: Project #1 - Simple Question & Answer App
Lecture 11 LLMs Walkthrough
Lecture 12 LLM Practical Implementation using Python
Lecture 13 Project Environment Setup
Lecture 14 Lets' Build Simple Question Answering Application
Section 7: Project #2 - Simple Conversational App
Lecture 15 Chat Model Walkthrough
Lecture 16 Chat Model Practical Implementation using Python
Lecture 17 Let's Build Simple Conversational Application
Section 8: Project #3 - Find Similar Things App For Kids
Lecture 18 Text Embedding Walkthrough
Lecture 19 Text Embeddings Practical Implementation using Python
Lecture 20 Embeddings Example using Python
Lecture 21 Let's build Similar Words Finder Application
Section 9: Langchain - Prompt Module Concept & Implementation Using Python
Lecture 22 Prompts Module Introduction
Lecture 23 Prompt Template Walkthrough
Lecture 24 Example Selectors Walkthrough
Lecture 25 Adding More Examples To Input Prompt
Lecture 26 Output Parsers Walkthrough
Section 10: Project #4 - Marketing Campaign App
Lecture 27 Convert Jupyter Notebook to Python Script
Lecture 28 Building the App's frontend
Lecture 29 Integration of Frontend & Backend
Lecture 30 Modularization of Code
Lecture 31 Project Source Code
Section 11: Langchain - Memory Module Concept
Lecture 32 Importance of Memory in LLM powered Apps
Lecture 33 Different Types of Memory
Lecture 34 Source Code
Section 12: Project #5 - ChatGPT Clone with Summarization Option
Lecture 35 ChatGPT Clone Demo
Lecture 36 Setting up the Project
Lecture 37 Implementing the Frontend
Lecture 38 Modularizing the Code
Lecture 39 Passing Dynamic Data
Lecture 40 Implementing Chatbot Conversational View
Lecture 41 Conversation Summarization & API key feature
Lecture 42 Source Code
Anyone who is excited to build AI powered LLM apps using Generative AI tools
Homepage

https://www.udemy.com/course/master-generative-ai-build-gen-ai-apps-beginner-friendly/