Visual Computing & Artificial Intelligence
At a glance
Academic degree
Master of Science (M.Sc.)
Form of study
Consecutive full-time Master’s degree
Standard period of study
3 semesters (incl. Master’s thesis), 90 ETCS, extension to 5 semesters possible
Place of study
Language of instruction
German and English
Start of studies
Winter and summer semester (October 01 and March 15 respectively)
Admission requirements
- University degree or other equivalent qualification in visual computing, computer science or a related course of study
- Generally 210 ECTS including a practical semester; for degrees with 180 ECTS, missing ECTS in theory or practice can be made up before the start of studies or within one year after the start of studies. Recognition is possible.
- German and English language level B2
- Further information can be found in the study and examination regulations
- For international applicants: all information about the application including an overview of the required language certificates here
Semester abroad
Possible as a theoretical or practical semester
Studying with a practice partner
Registration
May 02 – September 30 (winter semester)
November 15 – March 14 (summer semester)
Profile of the degree program
Visual computing is one of the most innovative and forward-looking fields of computer science and plays a key role in the digital society. On this course, you will learn how visual information is digitally generated, analyzed and processed. The focus is on image synthesis, image understanding and human-machine interaction. You will deal with modern approaches from computer science, mathematics, engineering, design and ergonomics. The importance of artificial intelligence in visual computing is a central component of the program and is also reflected in the name of the course. In addition to technical expertise, you will develop interdisciplinary skills to solve complex issues of visual digitalization. The courses are offered in German and English, so you will also learn international perspectives and how to work in global teams. The course is aimed at you if you have already completed a Bachelor’s degree in Visual Computing, Computer Science or a related subject and are looking for an innovative, practice-oriented Master’s degree.
What we value
Interdisciplinarity and practical relevance
We attach great importance to imparting comprehensive contextual knowledge between the generation, analysis and interaction with visual data. We focus on practice-oriented projects and cooperation with companies from various sectors in order to promote interdisciplinarity and cooperation between students from different disciplines.
Research and application orientation
The course is strongly application and research-oriented. You will be involved in current research topics and work on projects that include both practical applications and the consolidation of mathematical and scientific principles.
Supra-regional and international orientation
The Master’s is characterized by its supra-regional and international orientation. It is particularly attractive for students from Germany and abroad, as it represents a unique offer in Bavaria and is supplemented by the possibility of a foreign component, such as the Master’s thesis.
Promoting diversity and equal opportunities
We are actively committed to promoting diversity and equal opportunities, in particular by increasing the proportion of women in computer science degree programs. We also offer individual mentoring and support to specifically promote students with different prior knowledge.
Course content and schedule
In the Visual Computing & Artificial Intelligence Master’s degree course, the course content is taught in a structured and practice-oriented manner in order to develop both theoretical and applied skills in the field of visual digitization.
Basic modules
The foundation modules are to be offered jointly for the Master’s in Visual Computing & Artificial Intelligence and the Master’s in Data Science. These modules will therefore be held in English throughout. In detail, the following modules are planned, each with possible content:
- Mathematics and Multivariate Statistics
- Exponential functions
- Selected topics from linear algebra and analytic geometry
- Similarity and distance measures
- Bayesian statistics
- Linear and non-linear balancing calculation
- Dimension reduction
- Data Mining
- Basics
- Clustering
- Classification
- Association rules
- Data Visualization
- Visual perception and visual development
- Statistical plots, time series, spatial data
- Interactive visualization
These foundation modules are designated as compulsory elective subjects. This means that they can be replaced by relevant project studies in individual cases, provided that a student has already acquired the knowledge and skills taught in the respective module during their first degree.
Compulsory specialist modules
In addition, various specialist modules will also be offered, covering the subject-specific breadth of Visual Computing. Possible contents are listed for the respective subjects.
- Deep learning
- Linear and non-linear optimization
- Neural networks
- Feedforward networks
- Recurrent networks
- Deep learning
- Convolutional Neural Networks
- Autoencoder
- Long Short-Term Memories (LSTMs)
- Advanced Topics in Computer Graphics
- Real-time rendering
- Distributed and remote rendering
- Global illumination
- Advanced display systems (multi-display systems, lightfield, varifocal displays)
- Differentiable and Neural Rendering
- Immersive and situational analytics
- Advanced Topics in Human-Computer Interaction
- Multimodal interaction (e.g. Gaze+Pinch, Speech+Gesture),
- tangible interaction
- Physiological signals in the HCI (HRV, GSR, EEG)
- Evaluation using mixed-method designs
- Advanced Topics in Computer Vision
- 3D reconstruction: epipolar geometry, fundamental matrix, reconstruction of camera parameters, point correspondences using correlation and feature-based methods, triangulation, structure-from-motion, bundle block adjustment
- Human pose and shape estimation, facial models (3D morphable face models), hand tracking and reconstruction
- One-Shot and Few-Shot Reality Capture
Self-study modules
In addition to the subject-specific modules, the students’ independent scientific work is to be trained in an extensive project work and the entire process of visual computing is to be made tangible. There are different variants depending on the topic, lecturer and interests of the participants:
- Research-oriented (integrated into ongoing research projects at the university) or application-oriented (in cooperation with companies)
- Individual or team projects
Another self-study module is a seminar that focuses on intensive independent work with original scientific literature on a current research topic. This also lays the foundations for the methodology for the Master’s thesis.
Compulsory elective modules
In addition, various elective subjects are offered in the field of Visual Computing & Artificial Intelligence, which enable further specialization and deepening of the course content. From the subjects offered, 3 subjects can be selected during the course of study. The following subjects are offered (the range of electives will be expanded in the future):
- Ethics of artificial intelligence
- Knowledge Representation and Reasoning
- Virtual and augmented reality
- Reinforcement Learning
Job & Career
For graduates of the Visual Computing & Artificial Intelligence Master’s degree course, the increasing visual digitalization and the constant progress of new technologies open up exciting career opportunities in a variety of promising industries. The demand for specialists who are familiar with imaging techniques, image processing and the application of artificial intelligence in the analysis of visual data is growing rapidly – especially in the fields of medical technology, the automotive industry and Industry 4.0. Thanks to the practice-oriented training and the quick transition from a Bachelor’s degree in Visual Computing, numerous doors are open to you to get off to a successful start in these dynamic fields. Some of the particularly interesting sectors include
- Automotive industry (autonomous driving, vehicle development, infotainment systems)
- Medical technology and bioanalytics (development of systems to support diagnostics and laboratory processes)
- Image processing in medium-sized industry (automatic recognition, object identification, quality assurance)
- New media (development of interactive or mobile applications, metaverse projects)
- Additive manufacturing (3D printing)
- Software industry (visual analytics for data mining and big data, IT security protocols)
- Consulting company (consulting on visual data solutions)
- Application-oriented research (development of innovative technologies and applications)
- Games industry (development of interactive games and visual experiences)
Do your doctorate now!
Graduates with a good Master’s degree can continue to work scientifically after completing their Master’s degree. For example, they have the opportunity to do a doctorate at the Analytics4Health doctoral center at Coburg University of Applied Sciences or in cooperation with a university.
Curriculum and examination regulations
The study and examination regulations form the legal basis of the degree program. Questions about the content of the course can also be answered by the course director Prof. Dr. Stephan Streuber.
