Gen Ai Crash Course – Understanding The Buzz Words

Free Download 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!
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