Machine Learning
Machine Learning is a central subfield of artificial intelligence. Many digital applications in our daily lives use machine learning: spam filters sort out unwanted emails, streaming services recommend suitable content, and voice assistants respond to spoken requests. In all these cases, the systems use large amounts of data to recognise patterns and derive decisions from them.
Discover now on the AI Campus how different algorithms and learning methods work, what they are suitable for, and how you can use them in a targeted way.
Selected courses
The MLOps Workbook · A Guided Online Course for Getting Started with MLOps
Introduction to Machine Learning - Start of the Micro Degree
Holistic applied AI in engineering – launch of the micro-degree
Dr Matthieu Deru is a senior software engineer (R&D) and UX designer for interactive systems at the German Research Center for Artificial Intelligence GmbH (DFKI). His project experience covers topics as diverse as the application fields of AI, from intelligent user interfaces to complex prediction models for electromobility.
Ute Schmid is Professor of Applied Computer Science, in particular Cognitive Systems. She has been teaching and researching knowledge-based methods of AI and machine learning for more than 15 years. She is internationally visible in the field of human-like machine learning and is currently researching explanation generation and the use of explanations in interactive learning. Ute Schmid also has experience in the development of intelligent tutoring systems and in the use of analogue examples in the context of knowledge and skill acquisition. In addition to a degree in computer science, she also holds a degree in psychology and has many years of experience in empirical research.