Mathematical methods will help you get to the bottom of information technology. At school, you will learn to understand and apply them practically. You will deepen your knowledge of mathematics, computer science, game theory, automated analysis, verification and correctness testing of computer systems. After graduation, you will become in-demand specialists - you will be able to apply highly advanced modern technologies in practice, including unconventional ones. Thanks to your in-depth knowledge of algorithmization, you will find employment in the commercial sphere or in industries focused on developing and operating demanding software systems.
Information technology moves the world
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79 %
students gain practical experience
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98 %
students successfully pass the State Final Examination
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99 %
graduates find work in the month
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40 938 Kč
is the average starting salary for graduates
1st Year
Compulsory Programme Courses - Winter
Compulsory Programme Courses - Summer
The common basis of the programme
The common core of the program consists of courses that will give you the knowledge important for all IT engineers:
- Computation Systems Architectures will teach you how to think about how your code will run on modern computing platforms, how to think about programming in a way that makes the most efficient use of resources, i.e., that your application makes the best use of the power of modern platforms, makes efficient use of system memory resources, and is also efficient in terms of energy consumed.
- Functional and Logic Programming will teach you that although classical imperative programming is a very widely used paradigm and is very close to machine-level implementation, there are other approaches that will give you a new perspective on some key problems and help you get novel and often more efficient solutions to them.
- Modern Trends in Informatics (in English) you need to know to see where the field is going and what to expect in practice in a few years.
- Parallel and Distributed Algorithms is a course that will show you the patterns, limits, and pitfalls of parallel and distributed algorithmic solutions and the associated synchronization mechanisms, without which you will hardly succeed in solving many of the more complex problems.
- Statistics and probability is the right hand of every engineer to process numerical results of experiments or data obtained while running your application, analyze them and learn from them to make further decisions is almost his daily bread.
- Theoretical Computer Science shows the limits of computer science capabilities through formal languages and mathematical models of computation. This is the only way to understand whether your problem is even solvable and, if so, with what resources and means to prove it.
- Data Storage and Preparation, especially big data, and extracting knowledge from it is a valuable art to any computer scientist. It is a key aspect that strongly influences the effectiveness of many solutions and applications.
- Artificial Intelligence and Machine Learning is a course where you will learn how to teach computers to understand our world and make them solve problems that are easy for humans but difficult for an algorithmic machine to handle.
Recommended course compositions
Basic course composition
1st year of study, winter semester
- Artificial Intelligence and Machine Learning
- Computation Systems Architectures
- Data Storage and Preparation
- Statistics and Probability
- Theoretical Computer Science
- English for Europe
1st year of study, summer semester
- Complexity (in English)
- Functional and Logic Programming
- General Algebra
- Modern Trends in Informatics (in English)
- Parallel and Distributed Algorithms
- Fault Tolerant Systems
- Fundamentals of Law
2nd year of study, winter semester
- Compiler Construction (in English)
- Game Theory
- Graph Algorithms
- Semester Project
- Static Analysis and Verification
- Advanced Digital Systems
2nd year of study, summer semester
NMAT ++
For students interested in mathematics, we recommend that the following free courses taught by the Institute of Mathematics at FSI be included in the curriculum:
* FSI-SOP: Optimization I (summer semester, 3cr) https://www.vut.cz/en/students/courses/detail?apid=261005
* FSI-SN1: Numerical Methods I (summer semester, 4cr) https://www.vut.cz/en/students/courses/detail?apid=261000
* FSI-SN2: Numerical Methods II (winter semester, 4cr) https://www.vut.cz/en/students/courses/detail?apid=261001
* FSI-SPP: Stochastic Processes (winter semester, 4cr) https://www.vut.cz/en/students/courses/detail?apid=261020
Possible pass: winter 1: FSI-SPP, summer 1: FSI-SN1, winter 2: FSI-SN2, summer 2: FSI-SOP
1st year of study, winter semester
- Artificial Intelligence and Machine Learning
- Computation Systems Architectures
- Data Storage and Preparation
- Statistics and Probability
- Theoretical Computer Science
1st year of study, summer semester
- Complexity (in English)
- Functional and Logic Programming
- General Algebra
- Modern Trends in Informatics (in English)
- Parallel and Distributed Algorithms
2nd year of study, winter semester
- Compiler Construction (in English)
- Game Theory
- Graph Algorithms
- Semester Project
- Static Analysis and Verification
- Advanced Digital Systems
2nd year of study, summer semester
They will pass on all their knowledge and hold you in difficult moments
Doc. Mgr.
Rogalewicz Adam
Ph.D.
Doc. RNDr.
Češka Milan
Ph.D.
Prof. RNDr.
Češka Milan
CSc.
Doc. Mgr.
Holík Lukáš
Ph.D.
Ing.
Hrubý Martin
Ph.D.
Prof. RNDr.
Meduna Alexander
CSc.
He is a theoretical computer scientist and expert on compiler design, formal languages and automata. Formerly, he taught theoretical computer science at various Asian, European and American universities, including the University of Missouri, where he spent a decade teaching advanced topics of formal language theory. He wrote over ninety scientific papers and several books.
Prof. Ing.
Vojnar Tomáš
Ph.D.
Tomas likes to work on the edge between mathematics, formal methods, and their applications in computer science and engineering. He is interested in static analysis and verification with formal roots but also dynamic analysis and testing. He lectures on operating systems too. Apart from the factual contents of the different courses, he strives to teach students to think systematically and to precisely formulate their ideas.
What are we talking about?
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