Bringing technology to life

Computer science in the bachelor's degree

No other discipline develops as fast as computer science, no other discipline yields as many innovations relevant to our daily life. Computer scientists are allrounders who shape the future. Your fields of application could be the automotive industry, aerospace or medical technology, public administrations and many more.
Computer scientists plan and program software systems to develop new improved algortihms which help control the complex digital world, reliably control processes, connect companies globally or develop human-machine interaction.

Computer science in the bachelor's degree programme

In the bachelor's program DIGITAL TECHNOLOGIES, we impart the fundamental technical and methodological knowledge of computer science and mathematics. This is a prerequisite for later broadening, deepening and specialization in the subsequent master's program DIGITAL TECHNOLOGIES or for entry into the working world. At the beginning of the program, the focus is on the fundamentals of software development.

In addition to these fundamentals of software development, you will acquire in-depth knowledge of special topics in computer science in the bachelor's degree program DIGITAL TECHNOLOGIES.

In addition to the ability to develop software for digitalization, it is also important to reflect on the opportunities and risks of the technologies.

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Student advisory service computer science

TU Clausthal

Prof. Dr. Andreas Rausch
digitec@tu-clausthal.de

Ostfalia University of Applied Sciences

Prof. Dr.-Ing. Reinhard Gerndt
digitec@ostfalia.de

 

 

Mathematics

Computer science cannot do without mathematics. Mathematics is essential so that robots can move, machines can learn and artificial intelligence can analyse huge amounts of data and make predictions. Likewise, there is a lot of mathematics behind the route calculation of navigation systems or the processing of graphics on the computer. The knowledge of how to use mathematical models, statistics or graphs is the content of the courses:

  • Basic Mathematics in Computer Science I and II
  • Stochastics and Statistics
  • Basics of optimisation

 

Computer science in the master's programme

An essential element of the thematic orientation of the DIGITAL TECHNOLOGIES study programme is that the interface between application and informatics in particular is strengthened and expanded. For the digitalisation of sustainable industrial processes and services, the following informatics areas are of particular importance in the above application areas.

You can choose from these informatics disciplines:

  • Cooperative Human-Machine Interaction
  • Engineering Methods and Dependability
  • Machine Learning and Big Data
  • Smart Cyber-Physical Systems
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Student advisory service computer science

TU Clausthal

Prof. Dr. Andreas Rausch
digitec@tu-clausthal.de

Ostfalia University of Applied Sciences

Prof. Dr.-Ing. Reinhard Gerndt
digitec@ostfalia.de

 

 

 

Computer Science Discipline #1

Cooperative Human-Machine Interaction

Digitalisation is changing the world of work. This change is particularly characterised by the increase in autonomously acting machines. The cooperation of man and machine is evolving from the instruction of a tool to a bidirectional interaction, and the use of machines is evolving from co-existence to cooperation and collaboration. This requires new types of user interfaces that are designed for safe cooperation. In particular, learning modelling and prediction is a decisive factor of such an intelligent user interface for intelligent human-machine cooperation.

 

Computer Science Discipline #2

Engineering Methods and Dependability

In addition to these technological aspects of digitisation, engineering methods in particular are also central in order to be able to implement the innovation potential of digitisation in the application areas on the one hand and to develop reliable systems of high quality on the other. This includes software and system development models, taking into account interdisciplinary and agile development methods. Approaches must be established within the framework of dependability engineering in order to guarantee the requirements for safety, security and privacy throughout the entire life cycle.

 

Computer science discipline #3

Machine Learning and Big Data

Machine Learning and Big Data are central concepts of Artificial Intelligence, whose potential is compared by the European Commission to innovations such as electricity or the steam engine: Instead of programming an algorithm for an application, it is learned automatically on the basis of data through training. Machine learning enables the intelligent processing of sensor data, especially audio and video data streams, and thus creates the basis for the realisation of complex autonomous systems, for example in robotics and autonomous driving. The challenges here are the lack of transparency of these processes, which often function purely as black box models and harbour risks in the areas of safety, security and privacy.

 

Computer Science Discipline #4

Smart Cyber-Physical Systems

Cyber-physical systems (CPS) describe the networking of the physical world of machines, plants and devices with the virtual world of the internet. As a result, CPS are no longer networked but isolated controllers, but rather become open networked system networks via the internet that interact with other systems in a variety of ways. These can be sensors in fleets of autonomous vehicles or remote-controlled robots in telemedicine, for example. An important step on this path is currently the introduction of the 5G mobile communications standard.