Gen Ai Crash Course: Understanding The Buzz Words

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