Key areas of the Master’s degree programme
Machine Learning and Neural Networks
High performance and cloud computing form the basis for modern and computationally intensive machine learning applications. Complex deep learning architectures allow the solving of sophisticated tasks using supervised or unsupervised learning, as well as reinforcement learning (RL) and multi-agent reinforcement learning (MARL).
Generative AI and LLMs
Large intelligent language models deliver impressive results and are indispensable in today’s world. A deep understanding of probabilistic and generative AI algorithms, as well as the structure and functionality of large language models (LLMs), is essential for their secure use and successful integration within companies.
Computational Intelligence
Discovering hidden patterns and relationships in data is central to data mining. Using numerical and statistical methods, as well as the fundamentals of machine learning and neural networks, custom algorithms can be implemented and optimised for these purposes.
Data Storage and Processing
Proficiency in relevant and current scripting languages is an essential qualification in the fields of data science and AI. Additionally, skilled use of query languages and a deep understanding of data storage and transformation are crucial competencies for efficient data processing and storage.
Interdisciplinarity and Practical Applicability
The programme enhances scientific research skills and competencies in modern, practical project management. A special emphasis is placed on sensitivity to ethical issues and data protection. Projects and electives allow for individual specialisation in cutting-edge areas. Through case studies, intensive exchange with companies and project work, on the importance of practical applicability is highlighted.
