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Description of  Gen Ai Crash Course Understanding The Buzz Words

Published 3/2024 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz Language: English | Size: 1.47 GB | Duration: 2h 46m Artificial Intelligence and Generative AI for those trying to understand how it all works What you'll learn Understanding the full artificial intelligence landscape AI, machine learning and deep learning basics Generative AI and how it works How your data is being used in GenAI solutions, and how to protect it How to become "AI Ready" Evaluating the copyright infringement argument for AI model trainers Government entity approach to Generative AI How to set your own AI initiatives Latest trends, advancements, and risks Neural Networks, MoE (Mixture of Experts) Vector Databases RAG (Retrieval Augmented Generation) Transformers Prompt Engineering Tricks Requirements For all levels, including non-technical and technical. Description Do you know all those AI buzz words you hear all of the time, but have no idea what they mean? Well, it's time to change that. This course was designed by a leading AI expert in the trans loc field, with two AI awards just in the last 6 months (including TAUS AI Revolutionary of the Year and Slator's Language AI 50 Under 50). Coming from a software product consulting and government background, this course is intended for a learner that is trying to understand how AI and Generative AI really work. This course is for everyone: software background or not. Complex technical problems are broken down into things that everyone can understand. Transformers, neural networks, MoE, vector databases, RAG, you name it. You'll understand all of it by the end.You will even walk through some other lesser known topics in the Generative AI sphere, including questions of copyright, data privacy protection, how Government entities should start to approach AI, and how to set your own AI initiatives to become "AI Ready".You will learn:-Artificial Intelligence 101-AI vs. Machine Learning vs. Deep Learning-Understanding Generative AI-Generative AI Infrastructure-Neural Networks and Mixture of Experts (MoE)-Understanding Vector Databases and RAG-Analysis of Copyright Infringement Claims for Data Training -Data Privacy Protection-Generative AI for Government-Prompt Engineering Tips and Tricks-Becoming AI Ready-Setting Your Own AI InitiativesSign up now, and let's get learning together! Overview Section 1: Let's Skip the GenAI Buzzwords: Welcome to the Course Lecture 1 Introduction Lecture 2 What You'll Learn in the Course Lecture 3 AI Almanac Section 2: Introduction to AI Lecture 4 Artificial Intelligence 101 Lecture 5 Difference Between Artificial Intelligence vs. Machine Learning Lecture 6 What is Generative AI? Lecture 7 The GenAI Hype Cycle and AI Ready Section 3: Machine Learning, Deep Learning, and Neural Networks Lecture 8 Machine Learning Models: Supervised and Un-Supervised Learning Lecture 9 Deep Learning and Neural Networks Lecture 10 The Two Types of Deep Learning Models Section 4: Generative AI Overview Lecture 11 GenAI Learning Method Lecture 12 What Generative AI Can Do (and Its Output) Lecture 13 The Market Landscape of Generative AI Tools Section 5: How Generative AI Works Lecture 14 Introduction to the GenAI Sphere and the Technical Infrastructure Diagram Lecture 15 Foundation Models Lecture 16 Large Language Models Lecture 17 Understanding Parameters, Nodes, and the Learning Process for Generative Models Lecture 18 What are Tokens? Lecture 19 Transformers Lecture 20 How Transformers Work and Affect GenAI Lecture 21 Before Transformers: RNNs Lecture 22 Mixture of Experts (MoE) Neural Network Infrastructure Lecture 23 GenAI Recap and Other GenAI Algorithms Section 6: The Role of Vector Databases and RAG (Retrieval Augmented Generation) Lecture 24 An Introduction to the Unit: The Fine-Tuning Methods Lecture 25 What are Vector Databases Lecture 26 Embeddings Lecture 27 How Vector Embeddings Work Lecture 28 How are Embeddings Used in LLMs and Translation Lecture 29 Retrieval Augmented Generation (RAG) Lecture 30 RAG Visualized and How it Works Section 7: Prompt Design Tips and Tricks Lecture 31 Introduction and Text Prompt Tip #1 Lecture 32 Text Prompt Tip #1 in Action (ChatGPT Live Demo) Lecture 33 Text Prompt Tips #2, #3, #4, #5, #6 Lecture 34 Prompt Tips for Image Generators Lecture 35 Image Generator Prompt Tips in Action (Dall-E Live Demo) Lecture 36 Don't Make These Prompt Mistakes! Section 8: Risks of Generative AI Lecture 37 Hallucinations Lecture 38 Misinformation and Fake Content Lecture 39 Privacy and Security Risks Lecture 40 Legal Challenges Section 9: Data Privacy and Protection in Generative AI Lecture 41 Introduction Lecture 42 Your Data is Your Biggest Asset Lecture 43 How is your data being used in generative models? Lecture 44 How can I protect my data? Section 10: Copyright Questions in Generative AI Model Training Lecture 45 Copyright Infringement Claims in Generative AI Lecture 46 An Overview of Fair Use Laws Lecture 47 Evaluating Fair Use Factor #1: The Character and Purpose of the AI Use Lecture 48 Evaluating Fair Use Factor #2: How Much was Used Lecture 49 Evaluating Fair Use Factor #3: Nature of the Copyrighted Work Lecture 50 Evaluating Fair Use Factor #4: Impact on the Value or Market of the Work Lecture 51 Fair Use Review and Quick Reference Guide Lecture 52 Offering a Different View on Copyright Claims Section 11: A Quick Guide for US Government GenAI Applications Lecture 53 An Introduction to Government GenAI Usage Lecture 54 US State Legislation and the Establishment of Task Forces Lecture 55 AI Regulation and Initiative Guidelines Lecture 56 Federal Government Initiatives (including OpenAI Partnership with Pentagon) Lecture 57 Examples of Successful Govt GenAI Implementations Lecture 58 2 Initiatives You Should be Taking as a Government Entity Section 12: Becoming AI Ready (as a Business or Government Entity) Lecture 59 What Does "AI Ready" Mean? Lecture 60 The Different Components of AI Readiness Lecture 61 Set Up Protected Access to LLMs Lecture 62 AI Data Preparation *THE MOST IMPORTANT THING YOU COULD DO* Lecture 63 Final Thoughts about AI Readiness Section 13: How to Set Your Own AI Initiatives Forward Lecture 64 The Good of the New Horizon Lecture 65 Exercise: What GenAI Is vs. Is Not Lecture 66 A List of Initiatives to Get You Started Section 14: Final Thoughts Lecture 67 Final Recap and Thank You! All Levels