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
Schriftfarbenorakel
Bundeswettbewerb KI
Deutsch
Extern
Machine Learning
KI in der Schule
The MLOps Workbook · A Guided Online Course for Getting Started with MLOps
appliedAI
5 Stunden
English
External
AI Literacy
Machine Learning
Introduction to Machine Learning - Start of the Micro Degree
Munich Center for Machine Learning
about 120 hours
Micro Degree
English
AI Campus Original
Machine Learning
Data Science & Big Data
AI in Higher Education
Experts
Fraunhofer IIS
Universität Bamberg
Visit Prof. Dr. Ute Schmid homepage (opens in a new tab)
Visit Prof. Dr. Ute Schmid LinkedIn (opens in a new tab)
Introduction to Machine Learning - Start of the Micro Degree
Munich Center for Machine Learning
To Micro Degree
Micro Degree
about 120 hours
Introduction to Machine Learning
Omar Eladawy
appliedAI
Omar Eladawy is an AI Trainer at appliedAI Initiative GmbH. His prior positions include AI Engineer at VoiceLine GmbH and Visiting Student Researcher at the Designing Education Lab at Stanford University. With this unique blend, Omar’s experiences bridges Tech, Education and Product. He has been trained in Electrical Engineering and Information Technology.
The MLOps Workbook · A Guided Online Course for Getting Started with MLOps
Introduction to Machine Learning Part 3: Evaluation and Tuning
Munich Center for Machine Learning
Anytime
Record of Achievement
40 hours
Introduction to Machine Learning Part 2: Algorithms
Munich Center for Machine Learning
Anytime
Record of Achievement
40 hours
Introduction to Machine Learning Part 1: Foundation
Munich Center for Machine Learning
Anytime
Record of Achievement
40 hours
GeoAI
Prof. Dr. Marius Lindauer
Universität Hannover
Marius Lindauer is a full professor at Leibniz University Hannover and a recipient of the prestigious ERC grant.
He completed his PhD at the University of Potsdam. After completing his doctoral studies, he joined the AutoML group at the University of Freiburg as a Postdoctoral Researcher. Marius is the co-head of the AutoML.org super-group, a member of the advisory board of COSEAL, a co-founder of the Leibniz Data Science Lab, and a member of several other networks, including ELLIS and CLAIRE. His research interests lie primarily in the field of AutoML, with additional expertise in Reinforcement Learning and Interpretable Machine Learning.