Generative Ai: All-In-One Fast Track - All Levels
Published 11/2024
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 835.29 MB | Duration: 3h 23m
Learn what is Generative AI | The fundamental concepts underneath | How does it generates images and text | fast track
What you'll learn
Understand Generative AI Fast: Learn how Generative AI differs from traditional AI in a concise, accessible way.
Explore Real-World Applications: Discover how AI generates text, images, audio, and video with real-life examples and short demos.
Master Foundational Concepts: Gain clarity on terms like datasets, training datasets, test datasets, and key stages in training.
Dive into Neural Networks: Learn the basics of Neural Networks and Convolutional Neural Networks for image and data processing
Unpack Advanced Architectures that power text and image generation : Explore GANs, VAEs, and Transformers at a conceptual level without the complex math.
Ethics and Limitations: Learn about ethical considerations and challenges in Generative AI to use these tools responsibly.
Requirements
Curiosity about AI - No prior technical knowledge needed, but a strong interest in understanding AI and Generative AI is essential.
Basic Math - Additions and multiplications
Openness to Concepts - Willingness to grasp new technical terms, from foundational AI concepts to advanced architectures.
No Programming Required - This course does not require coding skills, as the focus is on theory
Description
Course Description:Are you curious about AI or looking to deepen your understanding of Generative AI? This course is crafted for tech professionals, students, and even sales roles in tech companies, designed to take you from AI fundamentals to advanced concepts in an accessible and modular way.With 10 years of experience as a solution architect at major American tech companies like AWS, VMware, and Dell, I'm passionate about technology-especially AI. Over the years, I've delivered presentations to diverse audiences, making complex topics engaging and understandable. I bring that experience here, guiding you step-by-step through the essentials and beyond.What You'll Learn:AI Fundamentals & Generative AI Differences: Grasp the basics of AI and understand what sets Generative AI apart.Generative AI Applications: Explore applications of AI to generate text, images, audio, and video.Advanced Concepts Simplified: Understand the jargon, around AI, down to GEN AI, the fundamental technics behind Deep Learning, and dive into three popular Generative AI models: Transformers, GANs, and VAEs where we dismantle their architectures.Myths, Ethics & Legalities: Uncover common myths about Generative AI's ethical and legal challenges and discover how to use AI responsibly, following US and EU guidelines.Whether you're starting fresh, upskilling for a tech role, or enhancing your knowledge for a career in tech sales, this course has everything you need to get started and go further. I intentionally skip some expert concepts to maintain this course at the right level for a new (or fairly new audience) looking for fast track). If you like this course, please share feedback, and if you need to reach out please use my Linked-in or send me a message here. Happy learning, Christelle
Overview
Section 1: Introduction
Lecture 1 Course introduction
Lecture 2 Your instructor
Section 2: Introduction to AI and Generative AI
Lecture 3 Artificial Intelligence
Lecture 4 Brief history of AI
Lecture 5 Generative AI and comparison with AI
Lecture 6 Gen AI Global Impact
Lecture 7 Section 2 Summary
Section 3: Types of Generative AI (principles, demo, applications)
Lecture 8 Section introduction
Lecture 9 Generative AI for Text
Lecture 10 Demo: Text generation
Lecture 11 Popular tools (text)
Lecture 12 Generative AI for Images
Lecture 13 Demo: Image generation
Lecture 14 Popular tools (image)
Lecture 15 Generative AI for Audio
Lecture 16 Demo: Audio generation
Lecture 17 Applications (audio)
Lecture 18 Generative AI for Video
Lecture 19 Applications (video)
Lecture 20 Multimodal Gen AI
Lecture 21 Section 3 Summary
Section 4: Foundational Concepts and Key Terminology
Lecture 22 The Generative AI framework
Lecture 23 The Generative AI framework - key takeway
Lecture 24 Generative AI in Deep Learning
Lecture 25 Neural networks (fundamentals)
Lecture 26 Convolutional Neural networks (fundamentals)
Lecture 27 Section 4 Summary
Section 5: Generative Adversarial Network Model
Lecture 28 Introduction to GANs
Lecture 29 Deep dive objectives
Lecture 30 Dataset preparation
Lecture 31 Training the Discriminator
Lecture 32 Training the Generator - Equilibrium
Lecture 33 GANs Flash Card (+ Evaluation and Inference)
Section 6: Introduction to deep dives
Lecture 34 What to expect in the deep dive sections
Section 7: Transformer Model
Lecture 35 Introduction to transformers
Lecture 36 Deep dive objectives
Lecture 37 Tokens and Embeddings
Lecture 38 Positional Encoding
Lecture 39 Normalisation layer
Lecture 40 Data preprocessing principles (Tokenization, vocabulary, masking)
Lecture 41 Self-attention Mechanism
Lecture 42 Self-Attention Mechanism - Attention vectors (Q,K,V) /Attention scores
Lecture 43 Self-Attention Mechanism - Context sharing
Lecture 44 Residual connection
Lecture 45 Normalising the attention scores
Lecture 46 Feed forward layer
Lecture 47 Residual and Normalisation
Lecture 48 Multi-head attention
Lecture 49 Decoder : Output - Embedding - Positional Encoding - Normalisation
Lecture 50 Decoder : Masked multi-head attention - Residual C. - Normalisation
Lecture 51 Decoder: Multi-headed Cross-Attention + residual and normalisation (Decoder)
Lecture 52 Decoder : Feed forward Network - Residual C. -Normalisation
Lecture 53 Decoder: Linear & Softmax layers
Lecture 54 Decoder: Learning consolidation (using the decoder)
Lecture 55 Transformers- Flash card
Lecture 56 Transformers Flash Card + Evaluation and Inference
Section 8: Variational Auto Encoders
Lecture 57 VAE-Introduction to VAEs
Lecture 58 VAE-Deep dive objectives
Lecture 59 VAE-Dataset preparation
Lecture 60 VAE-Encoder - Input Layer
Lecture 61 VAE-Encoder - First Conv2D layer
Lecture 62 VAE-Encoder - Second Conv2D layer
Lecture 63 VAE-Encoder - Third Conv2D layer
Lecture 64 Encoder - Flatten layer and Dense Layer
Lecture 65 Encoder - Dense Layer
Lecture 66 Encoder - Latent Space
Lecture 67 Decoder
Lecture 68 VAEs Flash Card (+ Evaluation and Inference)
Section 9: Trust and Limitations of AI
Lecture 69 Trust and Limitations of AI
Lecture 70 True or Myth? What's Legal to Do with Generative AI
Lecture 71 Use GEN AI Responsibly
Section 10: Final Thougts & Thank you
Lecture 72 Final thoughts
Lecture 73 Thank you
Busy Professionals: Ideal for those who want a fast-track introduction to Generative AI concepts without unnecessary complexity.,AI Newcomers: Perfect for anyone curious about AI trends, applications, and key technologies.,Tech Enthusiasts: For those who want to understand the AI models driving innovation in text, image, and data generation.,Lifelong Learners: Designed for people with no coding background who are eager to explore the possibilities of AI
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