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Generative Artificial Intelligence Course

Your chance: Generative Artificial Intelligence Courses

Have you always wanted to harness the power of AI to create new worlds, design unique works of art or write captivating stories? Then Generative AI is for you! This revolutionary technology allows you to unleash your creativity and explore unimagined possibilities.

Generative AI, short for Generative Artificial Intelligence, is an innovative technology that enables machines to create new content such as text, images, music and even videos that have never been seen before. Unlike traditional AI, which relies on data sets to recognise patterns and make predictions, Generative AI can create new, creative content that goes beyond the limits of human imagination.

How does Generative AI work?

Various methods enable Generative AI to achieve this. Among the best known are Generative Adversarial Networks (GANs): Two neural networks compete with each other - one creates new content while the other tries to distinguish it from real content. Through this competition, the first network "learns" to generate ever more realistic content.
Autoencoder: A neural network is trained with existing data and learns to understand the underlying patterns. It can then use these patterns to generate new, similar data.
Variational autoencoder: An extension of the autoencoder that enables the model to vary the generated data and thus create even more creativity.

What areas of application does Generative AI have?

Generative AI has a wide range of possible applications, including

  • Art and design: Generative AI can be used to create new artworks, designs and illustrations.

  • Music: Generative AI can compose new pieces of music in different styles.

  • Text generation: Generative AI can be used to generate realistic and creative texts, such as blog posts, poems or even entire novels.

  • Video production: Generative AI can be used to create realistic videos, e.g. for advertising or film effects.

  • Product development: Generative AI can be used to generate new product ideas and create prototypes.

What are the benefits of Generative AI?

Increased creativity: Generative AI can help people to develop new ideas and utilise their creativity in new ways.

  • Increased efficiency: Generative AI can automate tasks, saving time and resources.

  • Personalisation: Generative AI can be used to create personalised content that is tailored to the individual needs of each person.

  • Opening up new markets: Generative AI can help companies to develop new products and services that appeal to new target groups.

What are the challenges of Generative AI?

  • Ethical concerns: Generative AI can be used to create fake content, such as deepfakes, which can be used for disinformation.

  • Lack of control: It can be difficult to control the results of Generative AI, which can lead to undesirable outcomes.

  • Data bias: Generative AI can reflect the biases contained in the training data, which can lead to discriminatory results.

What are the future prospects for Generative AI?

Generative AI is still at an early stage of development, but the potential of this technology is enormous. It is likely that Generative AI will play an increasingly important role in our lives over the next few years and will fundamentally change the way we work, create and perceive the world around us. So if you're interested in creativity, technology and the future, Generative AI is definitely worth a look.

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Useful information

Your FAQs to Generative AI

Welcome to our Generative AI FAQ section! Here we answer the most frequently asked questions about Generative AI to give you an understanding of this crucial implementation field.

Traditional AI focuses on analysing and understanding existing data, while Generative AI can create new, creative content.

There are different types of Generative AI models, such as GANs, autoencoders and variational autoencoders. Each model has its own strengths and weaknesses.

There are various ways to learn Generative AI:

  • Online courses: there are many online courses that introduce the basics of Generative AI and show you how to use the technology yourself.

  • Bootcamps: Bootcamps offer an intensive learning experience in a short period of time and provide you with the necessary skills to work with Generative AI.

  • Self-study: You can also use books, articles and tutorials to learn Generative AI on your own.


There are many resources for Generative AI, including:

  • Open-source libraries: there are several open-source libraries that can help you work with Generative AI, such as TensorFlow, PyTorch and JAX.

  • Online communities: There are many online communities where you can interact with other people interested in Generative AI.

  • Forums and blogs: There are many forums and blogs where you can find information and tutorials on Generative AI.


There are a growing number of jobs in the field of Generative AI, including

  • Generative AI Engineer: develops and implements Generative AI models.

  • Generative AI Researcher: Researches new Generative AI technologies.

  • Generative AI Artist: Uses Generative AI to create artwork.

  • Generative AI Content Creator: Creates content with the help of Generative AI, e.g. texts, images or videos.

Based on current salary data from Germany, you can expect the following average salaries in the field of Generative AI:

  • Starting salary: approx. €54,703 gross per year

  • Advanced positions: approx. € 62,572 gross per year

  • Management positions: approx. € 97,500 gross per year

(These are only average values and your individual salary may differ)



To prepare for a career in Generative AI, you should:

  • Learn maths and computer science: basic knowledge of maths and computer science is important to understand how Generative AI works.

  • Learn programming: You should be able to programme in a programming language such as Python or R.

  • Introduce machine learning: Machine Learning is the foundation of Generative AI, so you should familiarise yourself with the basics of Machine Learning.

  • Work on Generative AI projects: There are many open source Generative AI projects that you can get involved in. This is a good way to gain practical experience and build your portfolio.

Generative AI has the potential to change society in many ways, e.g:

  • New forms of art and entertainment: Generative AI can be used to create new forms of art and entertainment that were previously unthinkable.

  • Personalised products and services: Generative AI can be used to create personalised products and services tailored to each individual's unique needs.

  • New scientific insights: Generative AI can be used to gain new scientific insights, e.g. by analysing complex data sets.

Improved quality of life: Generative AI can be used to improve people's quality of life, e.g. by developing new medical treatments or more efficient energy systems.

At neue fische, we integrate AI learning content into every bootcamp where it makes sense in terms of content. If you are interested in this, you should take a closer look at our Web Development and Data Science bootcamp. And we will soon be launching a short format on-demand Generative AI course, in which you can learn flexibly at your own pace from anywhere at any time. Stay tuned!

Bootcamps offer a structured learning environment, live lessons, practical projects and direct feedback from lecturers/coaches and fellow students. Compared to self-study, they enable faster learning progress as they focus on intensive, focussed training.


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