Data Analysis and Artificial Intelligence

The Minister of Education, Science, Research and Sport of the Slovak Republic granted the right to award bachelor’s and master’s degrees in the Data Analysis and Artificial Intelligence study program based on the statement of the Accreditation Commission of the Slovak Republic.

Study plan for bachelor study program Data Analysis and Artificial Intelligence

Study plan for master study program Data Analysis and Artificial Intelligence

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.

Bachelor’s degree
1st year of study

  • Introduction to data analysis – from the very beginning of the study the student gets an idea of ​​what and why he will study and how it can be used
  • Algebra – mathematics distinguishes our graduates from users of various analytical tools (we show that you can learn interestingly and with applications)
  • Mathematical software – many things can not be counted without a computer, but software also needs to be chosen and used
  • Introduction to Computer Science – if someone has missed something in high school, they have a chance
  • Operating system user environments – using a computer is a prerequisite for working with data
  • Database systems – data must be stored somewhere and manipulated effectively
  • Programming, algorithms, complexity – data needs to be processed and prepared, and a “back door” is also required if a graduate wants to change profiling in the future
  • Professional English for Science – Data analysis and artificial intelligence cannot be done without a foreign language

2nd year of study

  • Real Variable Functions, Linear and Integer Optimization, Discrete Mathematics for Computer Science, Real Variable Functions
  • Probability Theory – Many things around us are not deterministic
    Introduction to machine learning – machine learning today “moves the world” and needs to be known
  • Introduction to Information Security – Data should be handled with care
    Automata and formal languages ​​- programming languages ​​are changing, but the principles remain
  • Programming in Python for Advanced – We keep up with the times and current trends
    Project – practical experience from processing life cycle is priceless


3rd year of study

  • Mathematical statistics – nor classical methods of data analysis “did not say the last word”
    Project – practical experience is never enough
  • Numerical methods – not everything can be calculated accurately, but real life expects a solution
    Functional programming, Competitive programming – you have to look at every problem from several sides
  • Introduction to Neural Networks
  • Big Data Processing Technologies – Anyone talks about big data, but our graduates also have experience from large corporations (Google, Facebook, T-Systems,…) and are willing to teach our students
  • Selected applications of data analysis – data and artificial intelligence have applications in astronomy, nuclear physics, bioinformatics, geographic information systems,… – we have the experts


Master’s degree
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.