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Get Familiar with the Generative AI Models Structure

What you will learn

Learn the basic structure and paradigms of modern Generative AI

What Generative Adversarial Networks (GANs) are and what they are used for

What Variational Autoencoders (VAEs) are and how they work

What the applications of the Neural Network models are

Description

Good [morning/afternoon/evening], learners, and welcome to our online course on Generative Artificial Intelligence! I am thrilled to be your guide on this journey into the fascinating realm where creativity and technology converge.

I am Tsvety, and I bring to you a wealth of knowledge in cultural studies and law, coupled with a passion for languages, teaching, and the exploration of cutting-edge technologies. Today, we embark on a quest to understand and harness the power of Generative AI—a field that has revolutionized the way we perceive creativity in machines.

**Course Overview:**

Generative AI represents a pivotal milestone in the evolution of artificial intelligence. Unlike traditional AI systems that follow pre-programmed rules, generative models have the ability to create, innovate, and produce content autonomously. Whether it’s generating realistic images, composing music, or crafting human-like text, the possibilities are as vast as the imagination.

**Why Generative AI Matters:**

As we delve into the intricacies of Generative AI, we’ll explore its real-world applications and understand why it matters in today’s technological landscape. From content creation to personalized user experiences, Generative AI has the potential to reshape industries and redefine the limits of what machines can achieve.

**Course Structure:**


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Our journey will be divided into modules, each focusing on a specific aspect of Generative AI. We’ll start with the fundamentals, gradually progressing to advanced topics. Along the way, we’ll delve into practical examples, hands-on exercises, and case studies to reinforce your understanding and application of the concepts.

**Your Role in this Learning Experience:**

Active participation is key to mastering the material. Engage in discussions, ask questions, and challenge your understanding. This course is designed not just to impart knowledge but to empower you to apply Generative AI principles in your respective fields.

**Final Thoughts:**

In the words of Arthur C. Clarke, “Any sufficiently advanced technology is indistinguishable from magic.” Generative AI, in many ways, embodies this sentiment. As we navigate through this course, let’s marvel at the magic of machines creating art, generating ideas, and pushing the boundaries of what we thought possible.

Get ready for an intellectually stimulating and creatively invigorating experience. Let’s embark on this journey into the realm of Generative AI together!

Thank you for joining, and let the exploration begin!

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Content

Introduction

Introduction

The Fascinating Evolution of Generative AI

The History of Generative AI

Neural Networks

Neural Networks
Neural Networks Structure

Deep Learning

Deep Learning Fundamentals

Generative Adversarial Networks(GANs)

Generative Adversarial Networks (GANs)
GANs Architecture
GANs Variants
GANs Training
GANs Challenges

Variational Autoencoders (VAEs)

Variational Autoencoders (VAEs)
VAEs Paradigm
Encoder
Latent Space Representation
Decoder

Normalizing Flows

Normalizing Flows

Generative Models Core Elements and Training

Generative Models Overview
Probabilistic Latent Space
Reparameterization Trick
Optimization Algorithms
Feedforward and Backpropagation

Generation Process and Different Types of Generative Models Application

Generative Models Key Components and Training
Generation Process
The Loss Function
Large Scale Pretrained Models
Natural Language Processing (NLP)
Language Modelling
Generative Writing
Style Transfer
Copyright Concerns
Art Generation with Generative AI

The Future of Generative AI

What will the future bring?