Computer Science and Artificial Intelligence

["They have acquired a basic understanding of the central concepts and methods of computer science – especially the competence of algorithmic thinking.", "They can think in abstract models and assess the possibilities and limitations of algorithmic processes.", "They are proficient in the mathematical, logical and statistical basics that are required for computer science.", "They know the structure and operations of computer hardware and significant software systems, such as operating systems, database systems and communication networks, and can assess different peculiarities in each case.", "They are familiar with the central artificial intelligence (AI) techniques and methods such as knowledge representation, heuristic search processes, inference processes, planning processes, pattern recognition (natural language processing and computer vision), data mining and machine learning processes, and they know how to properly use them.", "They are aware of the ethical, privacy and security issues associated with the use of information processing systems and see their effects on the economy and society.", "They are able to work scientifically and to transfer scientific knowledge into professional practice.", "They can methodically solve problems that can be solved by computers, i.e. choose suitable analysis, structuring, modelling, simulation and optimisation methods and apply them purposefully.", "They can work on complex tasks in a team and take over team management.", "They are able to communicate and argue convincingly.", "They can organise themselves and meet deadlines, they have the willingness to perform, and they show a sense of responsibility and duty."]