Data Analysis and Artificial Intelligence – Institute of Computer Science

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.