| Degree awarded | Master of Science (M.Sc.) |
|---|---|
| Duration and credits | 4 semesters; 120 ECTS credits |
| Starts in | April (summer semester) and October (winter semester) |
| Language of instruction | English |
Artificial intelligence (AI) now permeates all areas of our lives and holds enormous potential for the future. Mathematics and computer science provide the foundations for understanding and developing core AI technologies.
In the Master of Science programme in Artificial Intelligence Engineering (AI Engineering) you will deal with scientific theories, algorithms and methods for designing and developing AI-based systems. You will also acquire the ability to integrate artificial intelligence into existing real-world systems (e.g. media systems, information systems, industrial processes) or to develop these yourself.
In addition, you will study artificial intelligence from the perspective of other academic disciplines, as the widespread use of AI-based systems raises not only technical but also legal, ethical, social and economic questions.
The demand for AI competencies in the labour market is increasing significantly. With a master's degree in Artificial Intelligence Engineering, you are able to work independently or take on executive positions and challenging jobs in the private and public sectors or academia. This degree opens up outstanding career opportunities in a wide range of industries, such as:
Finally, the degree opens up an academic career path if you continue studying for a doctorate in artificial intelligence development.
The M.Sc. AI Engineering programme is divided into compulsory and compulsory elective module areas. In the compulsory area you will attend the Introduction to AI Engineering lecture (with accompanying exercise course) as well as an AI Engineering seminar. You will also write your master's thesis in this area.
You can find all the modules in the module catalogue.
The compulsory elective area is divided into the following six module groups:
You will study the construction of deterministic and stochastic algorithms, their implementation, evaluation and optimisation as well as the modelling and complexity analysis of discrete and continuous problems using mathematical methods. In addition, you will acquire fundamental knowledge of mathematical logic, stochastics, functional analysis and discrete mathematics to enable a deeper algorithmic mathematical understanding of AI-based systems.
You will examine methods and algorithms of symbolic and sub-symbolic artificial intelligence and machine learning (e.g. reinforcement learning, knowledge representation and deduction systems). Furthermore, you will study underlying theories of learning systems and the application of algorithmic and mathematical principles for the realisation of artificial intelligence.
You will learn methods and structured process models for the development of AI-based systems. In particular, these include testing and evaluation strategies (e.g. generative adversarial testing or simulation), data and knowledge modelling methods, methods and systems for operationalising AI-based systems and the evaluation of properties such as security, traceability, reliability, explicability and transparency.
You will gain insight into different application areas and possibilities of artificial intelligence, such as speech, text and media analysis, business information systems or energy informatics. Also covered are the specific characteristics of the application domains and their influence on the selection of AI methods and the development of AI-based systems.
You will learn about the legal, ethical, social and economic considerations involved in using AI-based systems and reflect on the societal impact of AI. Language courses and writing workshops, soft-skills seminars and practical courses will complement your academic studies and prepare you for your professional life.
You will learn to familiarise yourself independently with the current state of research in the AI Engineering field, collate this information and deliver oral presentations. You will acquire in-depth knowledge of research work in the field of artificial intelligence and get the preparation for a future research role.
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