Artificial intelligence and data processing

Building intelligence from zeros and ones

Degree programme objectives

The Artificial Intelligence and Data Processing program prepares students to work in the areas of design and development of intelligent systems and analysis of big data. These areas are currently undergoing very fast development and are becoming increasingly important. The program leads students to a thorough understanding of basic theoretical concepts and methods. During the study students also solve specific case studies to familiarize themselves with the currently used tools and technologies. Students will thus gain experience that will allow them to immediately use the current state of knowledge in practice, as well as solid foundations, which will enable them to continue to independently follow the developments in the field.

The program is divided into four specializations that provide deeper knowledge in a chosen direction. Specializations share a common core, where students learn the most important mathematical, algorithmic, and technological aspects of the field. Machine Learning and Artificial Intelligence specialization lead graduates to gain in-depth knowledge of machine learning and artificial

intelligence techniques and to gain experience with their practical application. Natural Language Processing specialization prepares graduates to work with natural languages (eg. Czech, English) in written and spoken form from the perspective of computer science. Data Management and Analysis specialization focus on data science, which creates value from big data by collecting, exploring, interpreting, and presenting data from different viewpoints with the goal of so-called business intelligence. Bioinformatics and Systems Biology specialization focuses on computational methods for automated analysis of large biological data and on creating predictive models of biological processes with the goal to better understand complex biological systems.

Study plans

Machine learning and artificial intelligence

full-time, specialized

Natural language processing

full-time, specialized

Processing and analysis of large-scale data

full-time, specialized

Studies

Hide Show

Objectives
The Artificial Intelligence and Data Processing program prepares students to work in the areas of design and development of intelligent systems and analysis of big data. These areas are currently undergoing very fast development and are becoming increasingly important. The program leads students to a thorough understanding of basic theoretical concepts and methods. During the study students also solve specific case studies to familiarize themselves with the currently used tools and technologies. Students will thus gain experience that will allow them to immediately use the current state of knowledge in practice, as well as solid foundations, which will enable them to continue to independently follow the developments in the field.

The program is divided into four specializations that provide deeper knowledge in a chosen direction. Specializations share a common core, where students learn the most important mathematical, algorithmic, and technological aspects of the field. Machine Learning and Artificial Intelligence specialization lead graduates to gain in-depth knowledge of machine learning and artificial
intelligence techniques and to gain experience with their practical application. Natural Language Processing specialization prepares graduates to work with natural languages (eg. Czech, English) in written and spoken form from the perspective of computer science. Data Management and Analysis specialization focus on data science, which creates value from big data by collecting, exploring, interpreting, and presenting data from different viewpoints with the goal of so-called business intelligence. Bioinformatics and Systems Biology specialization focuses on computational methods for automated analysis of large biological data and on creating predictive models of biological processes with the goal to better understand complex biological systems.
Learning Outcomes
After successfully completing his/her studies the graduate is able to:
- design systems and technologies for processing and analyzing data, including large data requiring distributed architectures;
- design, implement, and evaluate methods for the intelligent behavior of computer systems;
- identify problems that can be solved by artificial intelligence and machine learning techniques and formally describe and apply an appropriate approach to solving them;
- perform a practical analysis of large data, including visualization, statistical analysis, and interpretation of results;
- take into account the social impact and ethical aspects of the development of intelligent systems and the privacy issues in the analysis of potentially sensitive data;
- continue to independently follow the developments in the field and educate themselves.
Occupational Profiles of Graduates
Due to the dynamic development of the area, the graduates have a wide range of career opportunities, with specific employment positions being created continuously during the course of their studies. Examples of different types of possible positions:
- positions in applied and basic research, typically concerning extensive data processing, often also in collaboration with experts from other disciplines
such as biology or linguistics;
- positions in companies with an immediate interest in artificial intelligence and data processing (e.g., Seznam, Google) such as "Data Scientist" and "Machine Learning Engineer";
- positions in companies that have extensive, valuable data (such as banking, telecom operators) or companies focusing on cloud data analysis, e.g., "Business Intelligence Analyst" or "Data Analyst";
- graduates can also start their own start-up specializing in the use of artificial intelligence methods in a particular area.
Practical Training
The practical training in not an obligatory part of the study program.
Goals of Theses
The goal of Maters's thesis is to demonstrate that student is capable of working on a project of non-trivial size (e.g. to create a useful application, or to formulate and prove advanced mathematical thesis), as well as to demonstrate the capability of presentation and positioning of the results in the context of actual state-of-the-art in the field. Bachelor's thesis is expected to be written in Czech, Slovak or English language. Expected structure of the work includes declaration of the author about the thesis being a school work, declaration of authorship, contents, the proper text, and references. The expected scope of the work is 40 regular pages of the proper text (including illustrations).
Access to Further Studies
After completion of the studies, it is possible to continue in doctoral degree programme at the faculty (after satisfying the admission requirements).