follow-up master's program (English) with specializations

• English
• doc. RNDr. Tomáš Brázdil, Ph.D.

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 three 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.

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 linguistics or medicine; 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.

Requirements for successful graduation

• Obtain at least 120 credits overall and pass the final state exam.
• Obtain 20 credits from SDIPR course and successfully defend Master's Thesis. See more details.
• Pass all the compulsory and elective courses of the program and selected specialization with the highest possible graduation form (unless explicitly stated otherwise).
• Fulfil requirements of at least one specialization.

Compulsory courses of the program

Specialization: Machine Learning and Artificial Intelligence

Machine Learning and Artificial Intelligence specialization leads graduates to gain in-depth knowledge of machine learning and artificial intelligence techniques and to gain experience with their practical application.

Compulsory courses of the specialization

Recommended course of study

Specialization: Processing and Analysis of Large-scale Data

Processing and analysis of large-scale data specialization focuses 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.

Compulsory courses of the specialization

Recommended course of study

Specialization: Natural Language Processing

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.

Compulsory courses of the specialization

Recommended course of study