Pavol Jozef Safarik University Faculty of Science
Master in Data Analysis and Artificial Intelligence
Košice, Slovakia
Master degree
DURATION
2 years
LANGUAGES
English
PACE
Full time
APPLICATION DEADLINE
EARLIEST START DATE
STUDY FORMAT
On-Campus
Key Summary
About: Master in Data Analysis and Artificial Intelligence at the Faculty of Science, founded in 1963, has educated over 6,000 graduates. Currently over 350 bachelor’s, master’s, and doctoral students graduate each year. The program offers novel study programs, new labs, tradition, family atmosphere, with state-of-the-art research and strong cooperation with practice. The curriculum emphasizes data analysis, machine learning, deep learning, statistics, programming, hands-on lab work, and applied research.
Career Outcomes: Graduates can work as data scientist, machine learning engineer, AI researcher, data analyst, or business intelligence developer. Other paths include roles in healthcare analytics, finance, government, and tech startups, applying skills in data science, neural networks, model evaluation, Python and R programming, and applied research.
The study program Data Analysis and Artificial Intelligence is an interdisciplinary study program that combines in a balanced way the knowledge of mathematics and computer science. Interdisciplinarity gives graduates greater opportunities in the selection of follow-up study programs or in practice.
Why study with us?
- Novel study programs. We offer a novel study program Data Analysis and Artificial Intelligence.
- New labs. Use Cyber Security Laboratory, Laboratory of computer vision with virtual reality, Laboratory of Internet of Things, Laboratory of Intelligent Data Analysis, and some other laboratories in our University Science Park.
- Tradition. The Institute of Computer Science has more than thirty years of tradition and long-term experience in teaching computer science.
- Family atmosphere. In our university, each student is an individual that we can address individually and we can solve individually the possible problems. We support several events aimed exclusively at students.
- State-of-the-art research is reflected in study programs. Researchers specialize in leading areas of research and incorporate current knowledge into curricula. Programming, data analytics, machine learning, software engineering, computer security, neural networks, and many other areas are immediately presented to students at seminars and lectures.
- Cooperation with practice. The Košice region is experiencing a boom in information technology and is the seat of several leading companies. Cooperation with them takes place on several levels – either in the form of subjects directly realized by companies, participation in Košice IT Valley, or in various activities that these companies support.
Study Plan
1st year of study
- Combinatorial algorithms, Random processes, Multivariate statistical methods – the world needs to be modeled and properly understood
- Seminar on Data Management – we will look at real practical problems in cooperation with partners
- Computational Complexity, Organizing and Processing Data, Parallel and Distributed Systems – Even today’s computing capacity is not enough for all types of problems, and then “human reason must come”
- Machine Learning – Autonomous and expert systems cannot be imagined without machine learning today
2nd year of study
- Neural networks – deep neural networks celebrate one success after another and every data analyst must control them
- Classical and quantum calculations – quantum computers are no longer a utopian dream and our graduates walk with the times
- Approximation and probabilistic algorithms – tools to solve various problems is never enough
Seminar on Data Management – we will look at real practical problems in cooperation with partners - And moreover, we have an offer of other subjects from different fields of science (not only at our faculty), through which the student can create an individual profile.
And if they know something else or do it differently, then we will create the conditions for the student to complete part of their studies outside the home faculty.
