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1
Introduction
2
Introduction to Generative AI
3
Advantages of Generative AI
4
The Future of Generative AI
5
Ethical Considerations in Generative AI
6
Introduction and Phases to LLMs
7
Introduction to OpenAPI GPT API
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Claude 3.5 Sonnet
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Claude Artifacts
10
Demo on Claude Artifacts
11
Use cases of Claude
12
Demo on Claude Sonnet
13
GPT 4o Mini and uses
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Why GPT 4o Mini
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Features of GPT 4o Mini
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Difference between GPT 4o and GPT 4o Mini
17
Demo on Playground tab, Dashboard tab, Docs tab and API References tab
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Prompting on Playground and Billing Settings
19
Version of Google Gemini
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General Prompt Demo Google AI Studio
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Structured Prompt in Google AI Studio
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Model Tuning in Google AI Studio using System Sample
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Other data import options in Google AI Studio using System Sample
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Abstract of the Email Generator App
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Software Requirements for App
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Implementation of the App
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Executing the App
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Generative AI Popular Tools
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ChatGPT
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Github Copilot
31
Claude
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Gemini
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Basics of Prompt Engineering
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Basics of ChatGPT
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Demonstration of Prompt on ChatGPT
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Python App using ChatGPT 4o
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Using ChatGPT 4o for Statistical Analysis
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Demonstration of Prompt using ChatGPT 4-o
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Portfolio website code execution
40
Introduction to Github and Github Copilot
41
Hands-on session on Github Copilot
42
Introduction of Claude
43
Prompt Engineering and Install Claude
44
Hands-on Claude
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Program for tic-toe game using Claude
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Claude 2 API
47
Integration of Python and Gemini 1.5 pro
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Chatbot using Gemini 1.5 pro
49
Generative AI Applications
50
Flask ChatGPT App
51
Flask Text-to-Image App
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Demo - Flask Text-to-Image App
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Introduction to Langchain
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Why LangChain?
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Development Environment Setup of LangChain
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Demo on Library Installation
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LangChain Core Concepts
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LangChain Components
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LangChain Case Study
60
Limitations of LLMs
61
Introduction to RAG
62
RAG Basics Concepts and Terminology
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Key Components of RAG - Retrieval and Generation
64
Workflow and Applications of RAG
65
Hallucinations in RAG
66
Steps to implement RAG with LangChain
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Hands-on RAG in detail
Description:
Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only! Grab it Embark on a comprehensive journey through Generative AI with this extensive 7-hour 40-minute tutorial. Gain a thorough understanding of Generative AI fundamentals, including its workings, advantages, and ethical considerations. Explore Large Language Models like GPT and master prompting techniques to create your own LLM app for Android. Discover popular AI tools such as ChatGPT, GitHub Copilot, Claude, and Gemini. Delve into advanced concepts like Langchain and Retrieval-Augmented Generation (RAG). Through hands-on demonstrations and case studies, develop the skills to build sophisticated AI applications. Cover a wide range of topics, from basic prompt engineering to creating Flask-based ChatGPT and text-to-image apps. Learn about the limitations of LLMs and how to overcome them using RAG. By the end of this tutorial, you'll be equipped with the knowledge and practical experience to shape the future of AI-driven communication and build advanced generative AI applications.

Generative AI Full Course 2024 - From Basics to Advanced Applications

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#Computer Science #Artificial Intelligence #Generative AI #Natural Language Processing (NLP) #LLM (Large Language Model) #ChatGPT #Prompt Engineering #LangChain #Programming #Software Development #GitHub Copilot #Claude #Machine Learning #Retrieval Augmented Generation
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Introduction