Machine Learning

Machine Learning is a branch of Artificial Intelligence concerned with the design of algorithms that improve their performance based on data. Machine Learning has grown into one of the most active and exciting areas of computer science. Being inundated with data, we turn to Machine Learning for effective and innovative solutions to a wide range of hard-to-tackle problems, ranging from data mining and pattern recognition to robotics, computer vision, computational biology, and computational linguistics.

Course description

Our Machine Learning course gives an in-depth coverage of the theory and principles of machine learning. The course covers two major approaches to machine learning: supervised learning (classification and regression) and unsupervised learning (clustering and dimensionality reduction). We give a systematic insight into the key models from the generative, discriminative parametric, and nonparametric flavors. With our course, the students gain a deep understanding of the theoretical foundations of these models, the underlying assumptions, and their advantages and disadvantages. Moreover, they gain extensive hands-on experience in programming and evaluating a variety of machine learning algorithms and models.

We consider Machine Learning to be our backbone course. Our research revolves around machine learning models, which are the real engines behind natural language processing, text analysis, and most of the Big Data applications out in the wild. We are excited to have the opportunity to equip our students with the essential tools and skills they need to become specialists in this amazing and growing field.

Additional information

The course is currently offered in Croatian only.
Browse the official course website at

Learn more about these and other courses offered at UNIZG FER in the UNIZG FER Course Catalogue (Graduate Study).