The classic course on Generative AI by Martin Musiol

The classic course on Generative AI by Martin Musiol, available at $94.99, has an average rating of 4.24, with 39 lectures, 5 quizzes, based on 466 reviews, and has 2190 subscribers.

You will learn about How to implement Generative AI models. We focus on proper concept implementation and relevant code (no administrative code) Get to know the broad spectrum of GAI applications and possibilities tangibly eg. 3D object generation, interactive image generation, and text generation How to identify great ideas in the GAI space and make best use of already developed models for realising your projects and ideas How to augment your dataset such that it ultimately improves your machine learning performance eg. for classifiers of rare diseases Learn about the ethical side: what are the concerns around GAI, incl. deep fakes, etc. The technical side: from the evolution of generative models, to the generator-discriminator interplay, to common implemenation issues and their remedies This course is ideal for individuals who are Potential entrepreneurs, as we will provoke various project ideas or Tech-enthusiasts that want to learn/ stay up-to-date with the newest advancements in AI or Visionaries that want to help shaping the future with (G)AI or Everyone who would enjoy a smooth journey through the world of Generative AI It is particularly useful for Potential entrepreneurs, as we will provoke various project ideas or Tech-enthusiasts that want to learn/ stay up-to-date with the newest advancements in AI or Visionaries that want to help shaping the future with (G)AI or Everyone who would enjoy a smooth journey through the world of Generative AI.

Enroll now: The classic course on Generative AI by Martin Musiol

Summary

Title: The classic course on Generative AI by Martin Musiol

Price: $94.99

Average Rating: 4.24

Number of Lectures: 39

Number of Quizzes: 5

Number of Published Lectures: 39

Number of Published Quizzes: 5

Number of Curriculum Items: 44

Number of Published Curriculum Objects: 44

Original Price: 129.99

Quality Status: approved

Status: Live

What You Will Learn

How to implement Generative AI models. We focus on proper concept implementation and relevant code (no administrative code)

Get to know the broad spectrum of GAI applications and possibilities tangibly eg. 3D object generation, interactive image generation, and text generation

How to identify great ideas in the GAI space and make best use of already developed models for realising your projects and ideas

How to augment your dataset such that it ultimately improves your machine learning performance eg. for classifiers of rare diseases

Learn about the ethical side: what are the concerns around GAI, incl. deep fakes, etc.

The technical side: from the evolution of generative models, to the generator-discriminator interplay, to common implemenation issues and their remedies

Who Should Attend

Potential entrepreneurs, as we will provoke various project ideas

Tech-enthusiasts that want to learn/ stay up-to-date with the newest advancements in AI

Visionaries that want to help shaping the future with (G)AI

Everyone who would enjoy a smooth journey through the world of Generative AI

Target Audiences

Potential entrepreneurs, as we will provoke various project ideas

Tech-enthusiasts that want to learn/ stay up-to-date with the newest advancements in AI

Visionaries that want to help shaping the future with (G)AI

Everyone who would enjoy a smooth journey through the world of Generative AI

Recently, we have seen a shift in AI that wasn’t very obvious. Generative Artificial Intelligence (GAI) – the part of AI that can generate all kinds of data – started to yield acceptable results, getting better and better. As GAI models get better, questions arise e.g. what will be possible with GAI models? Or, how to utilize data generation for your own projects?

In this course, we answer these and more questions as best as possible.

There are 3 angles that we take: 

1. Application angle: we get to know many GAI application fields, where we then ideate what further projects could emerge from that. Ultimately, we point to good starting points and how to get GAI models implemented effectively.

   The application list is down below.

2. Tech angle: we see what GAI models exist. We will focus on only relevant parts of the code and not on administrative code that won’t be accurate a year from now (it’s one google away). Further, there will be an excursion: from computation graphs, to neural networks, to deep neural networks, to convolutional neural networks (the basis for image and video generation).

   The architecture list is down below.

3. Ethical angle/ Ethical AI: we discuss the concerns of GAI models and what companies and governments do to prevent further harm.

Enjoy your GAI journey!

List of discussed application fields:

Cybersecurity 2.0 (Adversarial Attack vs. Defense)

3D Object Generation

Text-to-Image Translation

Video-to-Video Translation

Superresolution

Interactive Image Generation

Face Generation

Generative Art

Data Compression with GANs

Domain-Transfer (i.e. Style-Transfer, Sketch-to-Image, Segmentation-to-Image)

Crypto, Blockchain, NFTs

Idea Generator

Automatic Video Generation and Video Prediction

Text Generation, NLP Models (incl. Coding Suggestions like Co-Pilot)

GAI Outlook

etc.

Generative AI Architectures/ Models that we cover in the course (at least conceptually):

(Vanilla) GAN

AutoEncoder

Variational AutoEncoder

Style-GAN

conditional GAN

3D-GAN

GauGAN

DC-GAN

CycleGAN

GPT-3

Progressive GAN

BiGAN

GameGAN

BigGAN

Pix2Vox

WGAN

StackGAN

etc.

Course Curriculum

Chapter 1: Introduction

Lecture 1: Lets get started

Lecture 2: What is Generative AI?

Lecture 3: Your Instructor Martin

Lecture 4: The Course Overview

Lecture 5: Your Feedback is valuable

Chapter 2: Discriminative vs. Generative AI

Lecture 1: Discriminative vs. Generative AI

Chapter 3: Why does Generative AI matter?

Lecture 1: Broad Application Fields and Potential

Lecture 2: GAI in Top Strategic Tech Trends

Lecture 3: Example: Face Generation

Lecture 4: Example: Do-as-I-do-motion Transfer

Lecture 5: [Part 1] Example: GAI-generated Art AND the Interlock with Crypto & NFTs

Lecture 6: [Part 2] Example: GAI-generated Art AND the Interlock with Crypto & NFTs

Lecture 7: [Part 3] Example: GAI-generated Art AND the Interlock with Crypto & NFTs

Chapter 4: Where is Generative AI located?

Lecture 1: Where is GAI located?

Lecture 2: The Evolution of Deep Generative Models

Chapter 5: The Power of Generative Adversarial Networks (GANs)

Lecture 1: GANs are Powerful

Lecture 2: How does a GAN work?

Lecture 3: [Part 1] Excursion: Neural Networks

Lecture 4: [Part 2] Excursion: Neural Networks

Lecture 5: What GANs do exist? + Generative AI Ideation

Chapter 6: Why did it take them so long?

Lecture 1: Why did it take them so long?

Chapter 7: The implementation of a simple GAN

Lecture 1: [Part 1] GAN Demo

Lecture 2: [Part 2] GAN Demo

Chapter 8: A Deep-Dive into Various Application Fields

Lecture 1: 3D-Object Generation

Lecture 2: 3D-Object Generation – Ideas

Lecture 3: Interactive Image Generation

Lecture 4: [Part 1] Conditional GAN (cGAN) Demo

Lecture 5: [Part 2] Conditional GAN (cGAN) Demo

Lecture 6: How does a GauGAN work – Ideas

Lecture 7: How to augment Data and Why

Lecture 8: What Data Augmentation Techniques exist & what is their Effectiveness

Lecture 9: Data Augmentation with a GAN – Demo

Lecture 10: Data Augmentation: Lessons Learnt & Outlook

Chapter 9: Concerns around Generative AI Models

Lecture 1: Concerns around Generative AI Models

Chapter 10: Noteworthy GAN Architectures

Lecture 1: [Part 1] Noteworthy GAN Architectures

Lecture 2: [Part 2] Noteworthy GAN Architectures

Chapter 11: GAI Applications and further Ideas

Lecture 1: GAI can learn to simulate full Games & how to remaster Games

Lecture 2: [Part 1] Text Generation with (NLP) Language Models

Lecture 3: [Part 2] Text Generation with (NLP) Language Models

Instructors

Martin Musiol
Data Scientist at IBM

Rating Distribution

1 stars: 10 votes

2 stars: 20 votes

3 stars: 71 votes

4 stars: 164 votes

5 stars: 201 votes

Frequently Asked Questions

How long do I have access to the course materials?

You can view and review the lecture materials indefinitely, like an on-demand channel.

Can I take my courses with me wherever I go?

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