Artificial Intelligence
Course: Information Systems
Structural unit: Faculty of information Technology
Title
Artificial Intelligence
Code
ВБ 4.4.А
Module type
Вибіркова дисципліна для ОП
Educational cycle
Second
Year of study when the component is delivered
2023/2024
Semester/trimester when the component is delivered
2 Semester
Number of ECTS credits allocated
3
Learning outcomes
Ability to demonstrate knowledge and understanding of key concepts, goals, and tasks of using artificial intelligence methods; methodological foundations of applying AI algorithms. Applying AI algorithms to solve tasks, interpreting the results obtained. Ability to effectively form a communication strategy through precise argumentation, independently solve professional tasks, and take responsibility for the solutions obtained.
Form of study
Full-time form
Prerequisites and co-requisites
Having a bachelor's degree. Have elementary skills in in higher mathematics, algorithm theory, and programming.
Course content
The study the course “Artificial Intelligence” aims to acquire theoretical knowledge and practical skills in the methods and systems of artificial intelligence, as well as to equip students with tools for working with intelligent information systems and to develop their skills as researchers and developers of mathematical models, methods, and algorithms designed to solve artificial intelligence problems.
The goal of this discipline is to provide future professionals with a theoretical and practical foundation of knowledge, methods, and tools necessary to solve current artificial intelligence problems using modern methods and approaches in this field, and possible practical implementations.
Recommended or required reading and other learning resources/tools
5. Stepashko V., Bulgakova O., Zosimov V. Construction and research of the generalized iterative GMDH algorithm with active neurons. Advances in Intelligent Systems and Computing Vol. 689, 2018, Pages 492-510 Springer Verlag
6. Krotov, 2017 V. KrotovThe Internet of Things and new business opportunities Business Horizons, 60 (6) (2017), pp. 831-841
7. Bostrom N. Superintelligence. Paths, Dangers, Strategies / N. Bostrom. – Oxford University Press, 2016. – 432 p.
8. Advances in Intelligent Systems and Computing, 2019
9. https://drive.google.com/file/d/1CyjXhk8JVvlb4apbDbv95xXpo0WIvsvh/view
10. Advances in Intelligent Systems and Computing, 2020 https://drive.google.com/file/d/1x227JuzaLH8RiqkIBi9fYBcMX2Pni3P4/view
11. Artificial Intelligence (AI). https://www.edx.org/course/artificial-intelligence-ai-columbiax-csmm-101x-1
12. Artificial Intelligence https://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-034-artificial-intelligence-fall-2010/
Planned learning activities and teaching methods
Lectures, practical activities, individual work
Assessment methods and criteria
The level of achievement of all planned learning outcomes is determined based on the results of the defense of practical work and individual work. The overall grade is formed (maximum of 100 points) as the sum of points for systematic work throughout the semester, taking into account the control work. The credit is given based on the results of the student's work throughout the semester. Students who have accumulated a total of fewer points than the recommended minimum of 48 points must work on the missed material and pass the credit to obtain it.
At the student's request and if they have credit points, they can improve their result by taking an additional credit test, which is evaluated at 20/12 points, but the total number of points cannot exceed 100 points. Thus, the final evaluation for the discipline (minimum of 60, maximum of 100 points) is determined by the sum of the points for the semester work.
Language of instruction
Ukrainian
Lecturers
This discipline is taught by the following teachers
Departments
The following departments are involved in teaching the above discipline