Project management
Course: Applied mathematics
Structural unit: Faculty of Computer Science and Cybernetics
Title
Project management
Code
ОК.06
Module type
Обов’язкова дисципліна для ОП
Educational cycle
Second
Year of study when the component is delivered
2023/2024
Semester/trimester when the component is delivered
1 Semester
Number of ECTS credits allocated
3
Learning outcomes
PLO1. Possession of in-depth professional knowledge and practical skills to solve specific problems of designing intelligent information systems of different physical nature.
PLO3. Gaining knowledge for the ability to evaluate existing technologies and based on analysis to form requirements for the development of advanced information technologies.
PLO9. Collect and interpret relevant data and analyze complexities within their specialization to make judgments that reflect relevant social and ethical issues.
Form of study
Full-time form
Prerequisites and co-requisites
To successfully study the discipline "Project Management" the level of knowledge and skills of the student must meet the following requirements:
Know:
1. fundamental principles and practical approaches to the construction and analysis of qualitative characteristics of mathematical models.
2. methods of building mathematical and computer models of static and dynamic systems.
Be able:
1. apply methods of analytical and numerical modeling in solving applied problems.
2. formulate optimization problems for applied problems of linear and nonlinear programming.
Have the skills:
1. skills in using MATLAB application packages.
2. in English at a level not lower than Intermediate.
Course content
The discipline aims to master students' constructive approaches to project management in various applications. Familiarization with life cycle models in software development, analysis of such models, and optimization is an important aspect of this discipline.
Recommended or required reading and other learning resources/tools
1. www.pmi.org/PMBOK-Guide-and-Standards. 2. Kulian V.R. Metody optymalnoho keruvannia v zadachakh dyversyfikatsii portfelia invectytsii. Visnyk KNU imeni Tarasa Shevchenka. S.: kibernetyka. – vyp. 1(15). – 2015. – pp. 18-32. 3. Kulian V.R. Matematychne modeliuvannia ta optymizatsiia finansovo-ekonomichnykh protsesiv. Kurs lektsii. [Elektronnyi resurs]. Rezhym dostupu www.195.68.210.50/moodle/. – 2012. – 84 p. 4. Kulian V.R., Yunkova O.O. Matematychne modeliuvannia ta optymizatsiia finansovo-ekonomichnykh protsesiv. Navchalnyi posibnyk. K.: «Kyivskyi universytet», – 2014. – 112 p. 5. Kulian V.R., Yunkova O.O. Optimal Stock Portfolio Diversification Under Market Constraints // Systemni doslidzhennia ta informatsiini tekhnolohii. – No 1. – 2020. – pp. 90-97.
Planned learning activities and teaching methods
Lectures, independent work, elaboration of recommended literature, homework.
Assessment methods and criteria
Semester assessment:
The maximum number of points that can be obtained by a student is 60 points:
Test work №1: - 30/18 points.
Test work № 2: - 30/18 points.
Final assessment in the form of an exam.
Language of instruction
English
Lecturers
This discipline is taught by the following teachers
Victor
R.
Kulian
Complex systems modelling
Faculty of Computer Science and Cybernetics
Faculty of Computer Science and Cybernetics
Departments
The following departments are involved in teaching the above discipline
Complex systems modelling
Faculty of Computer Science and Cybernetics