M.Sc. AI Engineering
| 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 |
About the programme
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.
Features
- Research-oriented master's degree leading to excellent career opportunities in a multitude of industries
- Study a subject at the interface between computer science and mathematics and gain insights into a wide range of cross-disciplinary areas of application (e.g. media, Industry 4.0, mobility)
- Broad selection of state-of-the-art subjects with an international outlook
- Superb staff-student ratio: study in small learning groups
- The chairs and institutes maintain excellent relations with industrial and business partners
- The whole programme is taught in English
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:
- systems development and data analysis in the area of digital media
- software engineering and IT systems development
- data analysis in the financial and service sectors
- development of AI-based solutions in the transport and mobility sector
- control of industrial plants; Industry 4.0
- the medical and pharmaceutical industries as well as life sciences
- insurance companies and banks
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.
Compulsory elective modules
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.
1) Algorithm Engineering and Mathematical Modelling
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.
1) Algorithm Engineering and Mathematical Modelling
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.
2) Artificial Intelligence Methods
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.
2) Artificial Intelligence Methods
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.
3) Artificial Intelligence Systems Engineering
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.
3) Artificial Intelligence Systems Engineering
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.
4) Artificial Intelligence Applications
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.
4) Artificial Intelligence Applications
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.
5) Cross-Cutting Concerns
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.
5) Cross-Cutting Concerns
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.
6) Research Seminars
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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