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Information Modeling & Analysis


While the world provides an endless source of data, it does not come with a pre-defined model to understand it. Turning data into information requires to ask the right question and know how to find an answer. This course teaches students to turn data into information by using advanced modeling and analytics techniques based on machine learning. Like programming, teaching a machine to learn requires to design models selecting the most appropriate representation techniques. Unlike programming, teaching a machine to learn requires to select the right amount of training data and evaluate the quality of the predicted outcome. As they work through concrete application case studies, students will also gain a good understanding of the limitations and the assumptions behind each data mining technique so that they can be properly and correctly applied.

Additional information

Academic year
Master of Science in Informatics, Elective course, Lecture, 1st and 2nd year

Master of Science in Software & Data Engineering, Core course, Lecture, 1st year