Courses in machine learning

Machine learning is a branch of artificial intelligence focusing on algorithms that enable computers to learn from and change behavior based on empirical data. The course gives an understanding of the theoretical basis for machine learning and a set of concrete algorithms including decision tree learning, artificial neural networks, Bayesian learning, and support vector machines. The course also includes programming and use of machine learning algorithms on real-world data sets.

Click here → INF264

Artificial neural networks are flexible and powerful machine learning models. Modern deep learning has had tremendous success in applying complex neural networks to problems from a wide range of disciplines. This course gives and understanding of the theoretical basis underlying neural networks and deep learning. Furthermore, the course includes implementation of neural components and as well as applying deep learning on real-world data sets using modern deep learning packages.

Click here → INF265

Reinforcement learning is one the main paradigms of modern machine learning, artificial intelligence and robotics, with wide applications for decision-making and for the training of autonomous agents. This course provides an understanding of the foundation of reinforcement learning, analyzes classical reinforcement learning algorithms, and shows how practical problems can be modelled and solved with a reinforcement learning approach.

Click here → INF266

Fall 2025: Diamonds and Rust in the AI Treasure Chest

Spring 2025: Applied Machine Learning

Fall 2024: Quantum Computing and Quantum Machine Learning

Fall 2023: Quantum Computing and Quantum Machine Learning

Spring 2023: Geometric deep learning

Fall 2022: Natural language processing

Spring 2022: Topological machine learning

Fall 2021: Ontologies and Knowledge Graphs

Spring 2021: Machine learning and societal questions

Fall 2020: Learning Theory and Neuro-symbolic AI

Click here → INF367

Spring 2024: Reinforcement learning

Spring 2023: Reinforcement learning

Fall 2022: Advanced deep learning

Spring 2022: Reinforcement learning

Fall 2021: Natural language processing

Spring 2021: Reinforcement learning

Spring 2020: Deep learning

Click here → INF368