Computer Science

This course introduces artificial intelligence and neural computing as both technical subjects and as fields of intellectual activity. The course introduces basic concepts of artificial intelligence for reasoning and learning behavior; and introduces neural computing as an alternative knowledge acquisition/representation paradigm, to explain its basic principles and to describe a range of neural computing techniques and their application areas.

This course examines deep learning. It covers the motivations and principles for building deep learning systems; how deep learning relates to the broader field of artificial intelligence; problems associated with domain specific data; recognition; image generation; reinforcement learning; language translation; computer vision; natural language processing; PyTorch; Tensorflow; and numerical optimization algorithms.

This course explains the techniques behind compilers, lexers and parsers. It looks into mathematical formalisms of regular expressions, context-free grammars, and shows their applications to computer languages and illustrates low level machine languages and compiler techniques. Students learn how to use regular expressions to scrape information from the web, how to design grammars for parsing languages and how to implement a small interpreter and compiler. Students will be able to implement the central components of a small compiler. Students will also know the theory behind lexing and parsing so that they canchoose an appropriate algorithm for recognising a computer language.

A mobile robot is a machine controlled by software that uses sensors and other technology to identify its surroundings and move around its environment. This course provides a general understanding of mobile robotics and related concepts, covering topics such as sensing, computer vision (i.e., visual perception), state estimation (e.g., localization and mapping), and motion planning. The emphasis is on algorithms, probabilistic reasoning, optimization, inference mechanisms, and behavior strategies, as opposed to electromechanical systems design. Practically useful tools and simulators for developing real robotic systems are also covered in this course. 

The course provides an introduction to e-health by introducing basic concepts and describe how added value can be created in health care processes by the use of e-health systems. The course also provides knowledge about process analysis and information security in health care as well as an overview of current e-health research.

Ethical hacking tests the vulnerabilities of an organization's network. It is more than using IT, but involves an understanding of the psychological and sociological frameworks within which uses that network functions. This explores the basics of hacking and Open Source Intelligence gathering techniques, and teaches students how to use these skills practically and within legal boundaries of the European Union. Both theoretical and practical aspects of (ethical) hacking are covered with an emphasis on follow-through.