Applied artificial intelligence (M. Sc.)

Artificial intelligence has developed from a promising technology of the future into the basis of the business models of the world's most successful companies. As a result, the potential applications of AI can be found across all industries and more and more organisations are recognising the disruptive significance of artificial intelligence. In order to bring AI into business practice, experts are now needed who can provide trend-setting impetus for the future.

The Master's in Applied Artificial Intelligence prepares you for the world of tomorrow and qualifies you as a data scientist, machine learning engineer or data engineer alongside your career. As a graduate of this degree programme, you will have the relevant basic skills in AI as well as various specialisation skills, such as for the development of deep neural networks in the fields of computer vision and text and speech understanding.

Degree
Master of Science (M. Sc.)
Duration
4 semesters (with typical crediting)
Start of studies
Summer & Winter

Accreditation
Yes
Main teaching language
German

Study fee
3,725 per semester + € 82 student union fee
Location
THI

Curriculum

1. Semester

Wahlpflichtmodule: Mathematik & Statistik, Methodenkompetenz, Selbst- und Sozialkompetenz am Arbeitsplatz
5 ECTS

Programmieren I
5 ECTS

Programmieren II
5 ECTS

2. Semester

Algorithmen des Maschinellen Lernens
5 ECTS

Vertiefende Mathematik und Statistik
5 ECTS

Programmierung mit KI Frameworks
5 ECTS

3. Semester

Neuronale Netze
5 ECTS

Data Handling & Technologies
5 ECTS

Angewandtes Wissenschaftliches Arbeiten
5 ECTS

4. Semester

Deep learning for computer vision
5 ECTS

Deep learning für Sprach- und Textverstehen
5 ECTS

Projekt
5 ECTS

5. Semester

Masterarbeit
30 ECTS

Quick Info

Admission requirements:

Proof of successful completion of a technical or scientific degree programme at a German university with at least 210 ECTS credit points or equivalent or an equivalent successful domestic or foreign degree

and

proof of at least one year of relevant professional experience in the field of software development, business informatics, bioinformatics/technology, electrical engineering and information technology, data processing/analysis, aircraft and automotive development or mechanical engineering.

Admission is possible if you have a university degree with fewer than 210 ECTS credit points:

if you have a university degree with less than 210 ECTS credits or your degree is recognised with less than 210 ECTS credits, there is the possibility of crediting up to 30 ECTS credits from qualified professional experience.

Application and counselling:

For individual counselling before and during the application phase, please get in touch with your contact person at the Campus for Continuing Education. You will find the relevant contact details on this page.

Applications for this degree programme are made online. There you will receive all relevant information on the application formalities and have the opportunity to track your application progress. The application period for the summer semester begins on 15 November, for the winter semester on 2 May of each year.

University entrance qualification acquired abroad

If the higher education entrance qualification was obtained abroad, a preliminary examination of the higher education entrance qualification by uni-assist is required.

Please note that it may take 4 to 6 weeks for uni-assist to process your application.

You can find further information on applying to university from abroad on the website Applying to university from abroad.

University graduates with a degree in engineering, natural sciences or technology as well as computer science in Germany or abroad and at least one year of relevant professional experience, e.g. in the fields of software development, business informatics, bioinformatics/technology, electrical and information technology, data processing/analysis, aviation and automotive development or mechanical engineering.

You will be able to competently evaluate AI-based solution approaches and their probability of success in different problems
You will be able to successfully carry out development and research projects in the field of AI in companies
You will train machine learning models independently and apply them to practical examples
You will learn the mathematical and statistical principles of AI and how to apply them confidently
You will familiarise yourself with the most important software packages and tools

You can find the accreditation status or the accreditation certificate on the website for quality management.

Apply online