Annotated Course Catalog BSc Computer Science

Find better solutions: In the “Introduction to Theoretical Computer Science I”, you will learn everything important about the theoretical concepts that form the basic framework of computer science.
Like an algorithm - namely step by step - we deal with central terms and concepts such as propositional and predicate logic, formal languages, the (non)computability of functions and the famous halting problem. As a practical component in which you learn to work with macros, the module includes an introduction to the word processing system LaTeX, which you can use to create your academic work in a professional manner.

You will be able to develop your first computer programmes yourself after completing the programming degree. You will acquire one of the most important skills for your studies and your future career as a computer scientist. Computer scientists and data science students learn how to write their own programmes in practice. We start with the programming language PYTHON - a scripting language - and then programme with the object-oriented language JAVA. Computer exercises are an important part of the module, where we start with simple programming tasks and later develop a smaller project. You will not only acquire programming skills (in PYTHON and JAVA) but also learn how to use software development environments to create your programmes.

How can software and devices such as computers, smartphones or tablets be made as user-friendly as possible? This module is all about the design of interactive systems and what needs to be considered so that people can interact with machines intuitively and efficiently. You will learn the basics of human information processing and the technical realisation of interactive systems. You will learn how to design such systems in a user-orientated way and how to test the extent to which a system is user-friendly.

How is computer science changing and shaping our society? What influence does our society have on developments in the field of computer science? Experts from various fields will use examples to illustrate how computer science and society interact and discuss the social impact of computer science with you. Together we want to understand how computer science shapes our world and how we can actively and responsibly help to shape it.

Let's talk about computer science! The majority of technical terms used in computer science come from English. In the IT sector, most communication is in English. That's why we want to make you fit and offer you the opportunity to expand your English skills in general and with regard to the technical language in the computer science domain with this language course.

The language course is offered at CEFR language level B2 and at level C1. To participate in the C1 course, you must first take a short online Placement Test, which you automatically take when you register for the C1 course in SPUR.

Computer science is only half the story without mathematics. So you should make mathematics your ally! That's what this module is all about. Students of computer science and data science practize mathematical thinking together and expand their mathematical skills.

In the first half of the module, you will learn how mathematical thinking makes you a better computer scientist and data scientist, repectively. For example, you will learn about the mathematics of graphs and trees. You will use these concepts to give structure to data or detect and describe structures that are inherent in data. You can also use graphs and trees to develop algorithms that make searching for data more efficient and much more. The better you internalize the underlying mathematics concepts, the better you will be able to use them.

The second part of the module is dedicated to Linear Algebra (LA). Without LA, there would be no computer graphics, no neural networks, no data science. All of this requires insight into high-dimensional spaces. You get that here. We examine systems of linear equations, vector spaces and their subspaces, bases, linear mappings and their description as matrices. Once you have an overview of LA, we really get going in the second semester in Data Science and Computer Science.