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Overview

Artificial intelligence (AI) and data science are the driving forces behind the rapid advances in digitization and automation that will change our everyday lives. The two-year master’s course focuses on the theoretical foundations of artificial intelligence and statistical learning and their application to real problems. In-depth lectures lead you to specific research areas such as computational linguistics, language processing, computer vision, causality, generative modeling, logical reasoning and the analysis of biological-medical data. This course focuses on the methods of machine learning and their applications, with a strong focus on deep learning.

PROGRAMME STRUCTURE

Mandatory Courses and Practical Work:

Foundations of Mathematical and Statistical Methods in Data Science (10 CP)
Advanced Programming and Algorithms (10 CP)
Machine Learning (10 CP)
Deep Learning (5 CP)
Interdisciplinary Lecture Series (5 CP)
Lab rotation I ( 10 CP)
Lab rotation II (10 CP)
Master Thesis (30 CP)
Examples of Elective Courses:

Optimization Algorithms (5 CP)
Philosophy of Intelligence (5 CP)
Reinforcement Learning (5 CP)
Deep Generative Models and Sampling Methods (5 CP)
Data Visualization (5 CP)
Logic Programming (5 CP)
Relational Databases and Data Analysis (5 CP elective module)
Natural Language Processing (5 CP)
Machine Translation and Sentiment Analysis (5 CP)
Legal issues of Artificial Intelligence (5 CP)
Data & Knowledge Engineering (5 CP)
Advances in Data Science (5 CP)
Neuroimaging and precision medicine (5 CP)
Algorithmic Game Theory (5 CP)
Numerical Methods for Data Science (5 CP)
Causality (5 CP)
Markov Chains (5 CP)
Statistical Learning (5 CP)

ENTRY REQUIREMENTS

B.Sc. in math, physics, computer science, electrical engineering, or a related field.

CAREER PROSPECTS

Data scientist, AI specialist


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