Data Analysis and Artificial Intelligence is an interdisciplinary study programme at the Faculty of Science at the Pavol Jozef Šafárik University in Košice, which combines the theoretical and practical skills from the field of mathematics and computer science in a balanced manner. Interdisciplinarity provides the graduate greater opportunities in choosing follow-up studies or on the labor market.
For more info, see the faculty page.
Selection of courses
1st year of study
- Introduction to data analysis – The student will get an idea of what the focus and application of their studies will be right at the beginning.
- Algebra I, Algebra II for informaticians, Function of real variable, Function of real variables, Introduction to study of informatics – The level of mathematic skills is what distinguishes our graduates from users of various analytical tools.
- Programming, algorithms and complexity – The student will acquire the ability to process data but also have the possibility to change their specification.
- Mathematical software – Many problems can no longer be solved without a computer. We will teach the student how to chose and use the right software.
- Linux Basics – working with different operating system is a benefit for everyone in IT sphere
2nd year of study
- Introduction to Machine Learning –Machine Learning moves today’s world.
- Database systems for mathematicians – Data need to be stored and handled correctly.
- Linear and Integer programming, Discrete mathematics I and II – A further dive into exact foundations is needed after a warm-up.
- Introduction to Information Security – One has to be careful when dealing with data.
- Automata and formal languages – Programming languages change while the foundations they are built on stay invariant.
- Advanced programming in Python – We are keeping up with current trends in the field.
- Probability theory – Plenty of events around us is non-deterministic.
- Data analysis project I – Practical experience in the data processing life cycle is invaluable.
3rd year of study
- Image analysis
- Mathematical statistics – Ordinary methods of data analysis are still going strong.
- Data analysis project II – There is no such thing as having enough of practical experience.
- Numerical Methods – An exact answer to some problems does not always exist, but real life expects a solution.
- Functional Programming – Each problem has to be analyzed from different angles.
- Introduction to neural networks – students will get a glimpse into the world of predicting various situations
- Technologies of big data processing
- Vybrané aplikácie dátovej analýzy