Maschinelles Lernen MA

Studying Machine Learning will give you skills in:

• programming in Python using ML libraries, e.g. TensorFlow, PyTorch, scikit-learn,
• implementing and training ML and AI models on real-world datasets,
• creating ML processing pipelines and deploying ML models in production environments,
• optimizing code and models for performance and efficiency

In addition, we will prepare you for the changing needs of the environment by developing your social competences in:

• critical and analytical thinking - the ability to assess the quality of models and select appropriate algorithms,
• solving problems using ML algorithms in real-world applications,
• teamwork
• communicating results - presenting analysis and recommendations in a way that can be understood by a wide audience,
• the need for continuous improvement - ML is a fast-paced and dynamic field that requires constant learning of new technologies and methods.

Studying ML will provide you with not only theoretical knowledge, but also practical skills that are valued in the technology industry.

Where you can find a job after completing studies

With a degree in Machine Learning, you can find work in a wide range of industries, as machine learning is widely used in data analysis, automation and artificial intelligence. Common career paths include positions such as ML Engineer, Data Scientist, AI Researcher or ML Software Engineer. While tech companies such as Google, Meta, Microsoft and OpenAI are heavily recruiting ML specialists, the financial, medical, e-commerce or industrial sectors are also increasingly deploying AI models to optimize processes. You can find jobs in large corporations, start-ups, as well as in academic or research environments.

What will you learn during the studies

Mathematical foundations are a key part of the ML degree programme, as they pave the way to development of models and algorithms in the field of machine learning. We develop competence in fundamental mathematical skills, providing proficiency in advanced statistical methods and neural network architectures. Mathematical analysis supports the understanding of data and the interpretability of models, which is important for the ethical implementation of artificial intelligence.

During ML studies you will explore advanced neural networks, learn how to train, optimize and solve typical problems. You will get to know how to control intelligent systems combining decision-making algorithms and machine learning in robotics. You will master image analysis and natural language processing techniques. You will understand how reinforcement learning can be applied to robotics, games and recommender systems.

We also offer activities to develop practical skills in machine learning. You will learn how to communicate effectively in teams and manage projects. During internships you will gain experience in companies, working on real projects and networking with experts. You will learn how to design algorithms for large datasets and how to use modern computational tools. Team projects will help you improve your collaborative and problem-solving skills. And during the MSc seminar you will deepen your knowledge in your chosen area before defending your thesis.