First online course on Generative Artificial Intelligence

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Why should I take this course?


Generate Images,
Videos and Music

Build an AI that generates images, videos, music, etc. that you like. For example, describe a scene and the AI generates an image that fits best.

Augment your
Data Set

Do you lack data for a better performance of your applications? Then learn here how to improve your data set, having the right variance and purity.

Generate 3D Objects
for Product Design

Build an AI that disrupts (physical) product design. For example, when designing a chair add and subtract features, e.g. armrests as needed.

Stay up-to-date
with Ai

The topic of artificial intelligence is moving fast. We will keep you up-to-date for a long time, as it recaps what research has accomplished and where it is going.


The Power of Generative AI


Improve your dataset for a better AI performance.

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Photo-realistic images from a descriptive text only.

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Better product design: 3D objects out of images, text, etc. Further, add/subtract features (e.g. armrests) as it is best.

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Style-transformations on Images or Video.

AI can not only boost our analytic and decision-making abilities but also heighten creativity.
— Harvard Business Review

What does the course comprise?

This course provides you all relevant concepts of Generative AI. It is structured in the following way:

  1. Introduction + AI Overview

  2. Programming

  3. Generative AI and core concepts

  4. Applications

  5. What’s next?

First, we will introduce the broad topic of artificial intelligence (AI), what it exactly is, and what its fundamental subfields are - such as Machine Learning (ML), Deep Learning (DL), Reinforcement Learning (RL), Natural Language Processing (NLP), etc. Furthermore, a short introduction to the programming language Python and helpful libraries such as TensorFlow will be provided optionally. In the next part we dive deep into Generative AI. This part of the course is going to be structured in application modules that are rich with examples. Each module elaborates on what it is, where it brings value, and how you can build such an AI yourself.

The course is in English. We are dealing with concepts that achieve top performance results. Lastly, one of our top priorities is it to have visually appealing examples throughout the course.

Outline of the Course

  1. Introduction

  2. AI Overview

    • ML - Machine Learning

    • DL - Deep Learning

    • RL - Reinforcement Learning

    • NLP - Natural Language Processing

    • GAI - Generative AI

  3. Programming (short & sweet)

    • Python

    • TensorFlow, Keras, etc.

    • Git Repo and Project Administration

  4. Generative AI and its core algorithms

    • GANs - Generative Adverserial Networks

    • Autoencoder (Universal Neural Style-Transfer)

    • VAEs - Variational Autoencoders

    • RNNs - Recurrent Neural Networks

  5. Application Modules (incl. real-world examples and how to implement it)

    • Text-to-Image

    • Interactive Image Generation

    • Domain-transfer (i.e. image style-transfer, sketch-to-image)

    • Synthetic Data Generation

    • Automatic Video Generation

    • Video Prediction

    • 3D Object Generation

    • Cybersecurity 2.0 (Adversarial Defense vs. Attack)

    • [Bonus] Super Resolution Images

    • [Bonus] Generative Art

    • [Bonus] Human Pose Estimation

  6. What’s next?

    • How to read research paper efficiently?

    • Strategy on how to develop your own application using Generative AI

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