Theoretical knowledge:
• knowledge of automata theory;
• knowledge of formal language theory;
• knowledge of computability theory;
• knowledge of computational complexity theory;
• knowledge of basic models of computation;
• knowledge of basic information processing algorithms;
• knowledge of the theoretical foundations of quantum computing.

Practical skills:
• be able to write and read algorithms represented by various methods;
• be able to perform algorithm analysis;
• be able to design algorithms using different algorithmic strategies;
• be able to use basic algorithms for processing information using generic programming in C++, C# and Java;
• be able to use a functional computation model and perform computer systems programming using the functional programming paradigm;
• be able to use parallel computation models and program perform computer systems using a reactive programming paradigm;
• be able to apply concurrent computation models and perform computer systems programming using the event-driven programming paradigm.

Pre-requisites:
Discrete mathematics
Programming, part 1 (Fundamentals of Algorithms and Programming)
Programming, part 2 (Object-Oriented Programming)
Programming, part 3 (Data structure and Algorithms)

Introduction to the theory of computation. Algorithm representation and algorithm design paradigms. Fundamentals of algorithm analysis. A basic information processing algorithms. Libraries of basic information processing algorithms for popular programming languages. Models of Computation. Quantum computing.

1) Cormen, Thomas H.; Leiserson, Charles E.; Rivest, Ronald L.; Stein, Clifford. Introduction to Algorithms. — 3rd. — MIT Press, 2009. — ISBN 0-262-03384-4.
2) Donald E. Knuth.The Art of Computer Programming, Volumes 1-4A Boxed Set. Third Edition (Reading, Massachusetts: Addison-Wesley, 2011), 3168pp. ISBN 978-0-321-75104-1, 0-321-75104-3.
3) Michael Sipser (2013). Introduction to the Theory of Computation. 3rd. Cengage Learning. ISBN 978-1-133-18779-0
4) Savage, John E. (1998). Models Of Computation: Exploring the Power of Computing. ISBN 978-0-201-89539-1
5) Fernandez, Maribel (2009). Models of Computation: An Introduction to Computability Theory. Undergraduate Topics in Computer Science. Springer. ISBN 978-1-84882-433-1.
6) Anany Levitin (2012). Introduction to the design & analysis of algorithms. 3rd. ISBN-13: 978-0-13-231681-1
7) https://ocw.mit.edu/courses/mathematics/18-404j-theory-of-computation-fall-2006/
8) https://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-045j-automata-computability-and-complexity-spring-2011/

Written tests during lectures (without points)
Execution and defense of laboratory and practical works: 30
Examination control: 70 (written component: 60, oral component: 10)