Algorithms design and analysis
Course: Data science
Structural unit: Faculty of information Technology
Title
Algorithms design and analysis
Code
ОК 15
Module type
Обов’язкова дисципліна для ОП
Educational cycle
First
Year of study when the component is delivered
2023/2024
Semester/trimester when the component is delivered
3 Semester
Number of ECTS credits allocated
5
Learning outcomes
Design, develop, and analyze algorithms for solving computational and logical problems, evaluate the efficiency and complexity of algorithms based on the application of formal models of algorithms and computed functions.
Form of study
Full-time form
Prerequisites and co-requisites
Know the basics of elementary mathematics, discrete mathematics, and mathematical logic, set theory, fundamental approaches, methods, and technologies of algorithmization and programming. Be able to perform an analysis of simple problems to determine the structure of input and output information, select data types and structures, and build algorithm diagrams. Have elementary skills in working with any programming environment, developing high-level language programs to implement the task at hand.
Course content
During the study of the discipline " Algorithms design and analysis ", basic concepts of algorithm theory, formal models of algorithms, issues of computability, solvability and unsolvability of mass problems, the concept of time and space complexity of algorithms in solving computational problems, generalized schemes and features of existing algorithmic strategies are considered. The study of the discipline is aimed at developing students' ability to use formal languages and models of algorithmic computations, designing, developing and analyzing algorithms, evaluating their effectiveness and complexity, applying them in solving practical and scientific tasks in the field of information systems and technologies in future professional activities, and designing and developing software using different programming paradigms.
Recommended or required reading and other learning resources/tools
1. Borodkina I.L. Theory of Algorithms: a textbook for higher education students / Kyiv: Center of Educational Literature, 2018 - 182 p.
2. Priyma S.M. Theory of Algorithms: a textbook. - Melitopol: FOP Odnorog T.V., 2018. - 116 p.
3. Gerardus Blokdyk Analysis of algorithms A Complete Guide / 5STARCooks (March 18, 2022), 307 р.
4. Tim Roughgarden Algorithms Illuminated: Part 1, 2, 3, 4 / Soundlikeyourself Publishing;(September 27, 2017)
Planned learning activities and teaching methods
Lectures, laboratory works, individual work
Assessment methods and criteria
Students are evaluated throughout the semester based on various types of assignments. The overall grade for the semester is determined by the weighted sum of the points earned by the student on different types of assignments. The maximum number of points a student can receive for an assignment in the semester does not exceed 60 points on a 100-point scale. The discipline concludes with an exam.
Throughout the semester, after completing relevant topics, three written tests (KT1, KT2) are conducted with multiple choice and open-ended questions, as well as practical tasks. All laboratory and independent work is mandatory. To receive a passing grade for the discipline, a student must achieve at least 60% of the maximum possible points.
The maximum number of points a student can receive on the exam is 40 points on a 100-point scale. If a student receives less than 24 points during the exam, they will receive a failing grade and the earned points will not be counted.
Language of instruction
Ukrainian
Lecturers
This discipline is taught by the following teachers
Departments
The following departments are involved in teaching the above discipline