Develop Autonomous Mobile Robots: Understand and integrate the subsystems of autonomous robots, apply concepts such as kinematics, sensor fusion, and control engineering, and develop your own solutions for motion and path planning in hands-on research projects.

Design Successful Software Projects: Elicit, analyze, and document requirements for complex software systems, translate customer needs into precise specifications, and use modern tools and language models to improve the quality and efficiency of the development process.

Operate Modern Software Platforms: Develop microservice-based applications, containerize them with Docker, and orchestrate their deployment using Kubernetes. Apply DevOps practices to efficiently develop, deploy, and scale software.

Design Domain-Specific Languages: Analyze domain-specific languages (DSLs) in medical informatics and develop your own DSLs by applying concepts such as parsing, syntax trees, and execution logic.

Analyze Data with R: Develop scripts and notebooks in R, apply statistical methods and machine learning techniques to biomedical and business datasets, and validate hypotheses using data-driven analyses.

Understand the Limits of Computation: Explore computability, decidability, and computational complexity theory while analyzing fundamental questions in computer science—from Turing machines and the Halting Problem to NP-completeness and the P vs. NP problem. Learn to recognize and classify the fundamental limits of algorithmic problem solving.

Study Software Systematically: Plan and evaluate empirical studies in software engineering, formulate hypotheses, collect and analyze data, and critically interpret research findings using sound scientific methods.

Design Intuitive Data Interaction: Develop and evaluate innovative interactive systems for the visualization and analysis of complex data, combining concepts from perceptual psychology, interaction design, and data visualization.

Create Your Own Computer Science Workshop: Independently explore a new topic in computer science, collaborate with a team to design a workshop, and teach both the theoretical and practical aspects to your fellow students.

Analyze Clinical Data with Machine Learning: Learn how to analyze large collections of electronic patient data using statistical and machine learning methods, apply R for implementation, and interpret the results to generate new medical insights.

Protect Information with Cryptography: Deepen your understanding of modern cryptographic methods and protocols—from digital signatures and zero-knowledge proofs to elliptic curve cryptography and post-quantum cryptography—and learn to evaluate their security and applications.

Improve Patient Care with Intelligent Decision Support Systems: Develop Clinical Decision Support (CDS) functions for electronic health records, learn how medical knowledge can be processed automatically, and evaluate the benefits, limitations, and practical applications of modern clinical decision support systems.

Create Intuitive Digital Experiences: Explore innovative interaction techniques such as voice, gesture, and multi-touch interfaces, develop your own prototypes, and design user experiences that naturally connect people and technology.

Develop Mobile Apps Professionally: Plan, design, and implement mobile applications—from requirements analysis and UX design through prototyping, architecture, security, testing, and deployment.

Dive into how modern AI works: You will develop a deep understanding of neural network methodologies – from feedforward and convolutional networks to transformers, large language models and generative models – including their mathematical foundations and typical application areas. You also learn how to implement, train and apply these methods in practice using a deep learning framework such as PyTorch.

Tackle real-world challenges in medical data science: You independently develop data-driven solutions for a problem in healthcare - from data preparation and method selection through implementation and evaluation to the presentation of your results.

Understand What Users Really Need: Deepen your knowledge of requirements engineering—from requirements elicitation and prioritization to documentation and quality assurance—and develop precise specifications for complex software projects.

Design the Architecture of Complex Software Systems: Explore modern software architectures, analyze their impact on quality attributes, and learn how to systematically model and evaluate architectural concepts.

Understand software and business processes: Learn how software development and business processes are modeled, managed, and improved. You will explore software lifecycle models, traditional and agile development approaches, process selection, and methods for analyzing and optimizing workflows to support efficient and high-quality software development.

Ensure Software Quality Systematically: Learn how to define quality objectives, analyze and improve development processes, and apply quality assurance methods ranging from metrics and reviews to test management and audits.

Turn Technological Breakthroughs into Innovative Solutions: Work in interdisciplinary teams on real-world challenges, explore emerging technologies, and develop innovative concepts that connect scientific advances with societal needs.

Develop Digital Innovations from the User`s Perspective: Identify real user needs, apply design thinking methods, and iteratively develop digital solutions—from user research and ideation to prototyping, user testing, and persuasive product pitches.

Prepare for Your Master`s Thesis: Learn scientific methods, models, and ways of thinking, and apply them to systematically investigate IT-related problems, evaluate research studies, and plan and conduct your own research according to academic standards.