Analysis and Modelling of Informational Processes and Systems
Description: This course offers the development of the system for creating dashboards and the formation of students' practical skills in mathematical and computer modeling of information systems for various purposes, the practical implementation of models in the most common software packages for computer modeling, which allows for a deep and versatile analysis of information, and then present the result in an interactive form.
Amount of credits: 5
Пререквизиты:
- Statistical methods of data analysis
Course Workload:
| Types of classes | hours |
|---|---|
| Lectures | 15 |
| Practical works | |
| Laboratory works | 30 |
| SAWTG (Student Autonomous Work under Teacher Guidance) | 30 |
| SAW (Student autonomous work) | 75 |
| Form of final control | Exam |
| Final assessment method | Written exam |
Component: Component by selection
Cycle: Base disciplines
Goal
- The purpose of studying the discipline is to form special knowledge in the field of building models and methods for developing information systems of various classes and purposes.
Objective
- Classify the initial problem to determine how to model systems
- Apply standard and non-standard software to model deterministic and stochastic models and processes
- Use specialized simulation software packages depending on the class of the simulation task
Learning outcome: knowledge and understanding
- qualitative and quantitative methods for describing information systems
- the methodology of setting and algorithmic tasks at the macro- and microlevels
Learning outcome: applying knowledge and understanding
- be able to make a mathematical description of information processes and systems
- be able to make an aggregate description of information systems
Learning outcome: formation of judgments
- understand the terminology of systems theory
- have an idea of methods for synthesizing the structures of information systems
Learning outcome: communicative abilities
- ability to analyze systems under study and reasonably communicate the results to specialists and non-specialists
Learning outcome: learning skills or learning abilities
- Skills that allow you to continue studying in different areas of scientific research on your own
Teaching methods
technologies of educational and research activities
Communicative technologies (discussion, press conferences, brainstorming, academic debates, and other active forms and methods)
information and communication (including distance learning) technologies
Assessment of the student's knowledge
Teacher oversees various tasks related to ongoing assessment and determines students' current performance twice during each academic period. Ratings 1 and 2 are formulated based on the outcomes of this ongoing assessment. The student's learning achievements are assessed using a 100-point scale, and the final grades P1 and P2 are calculated as the average of their ongoing performance evaluations. The teacher evaluates the student's work throughout the academic period in alignment with the assignment submission schedule for the discipline. The assessment system may incorporate a mix of written and oral, group and individual formats.
| Period | Type of task | Total |
|---|---|---|
| 1 rating | Laboratory work 1. Working with the MOOC course “Tableau Fundamentals” | 0-100 |
| Lab Activity 2. Conducting analytics and visualizing results on your own data | ||
| Laboratory work 3. Analytical modeling. Model building by verbal description | ||
| Control work R1 | ||
| 2 rating | Laboratory work 4. Analytical modeling. Model building based on experimental data | 0-100 |
| Laboratory work 5. Simulation modeling. Discrete event modeling | ||
| Laboratory work 6. Simulation modeling. Agent-based modeling | ||
| Control work R2 | ||
| Total control | Exam | 0-100 |
The evaluating policy of learning outcomes by work type
| Type of task | 90-100 | 70-89 | 50-69 | 0-49 |
|---|---|---|---|---|
| Excellent | Good | Satisfactory | Unsatisfactory |
Evaluation form
The student's final grade in the course is calculated on a 100 point grading scale, it includes:
- 40% of the examination result;
- 60% of current control result.
The final grade is calculated by the formula:
| FG = 0,6 | MT1+MT2 | +0,4E |
| 2 |
Where Midterm 1, Midterm 2are digital equivalents of the grades of Midterm 1 and 2;
E is a digital equivalent of the exam grade.
Final alphabetical grade and its equivalent in points:
The letter grading system for students' academic achievements, corresponding to the numerical equivalent on a four-point scale:
| Alphabetical grade | Numerical value | Points (%) | Traditional grade |
|---|---|---|---|
| A | 4.0 | 95-100 | Excellent |
| A- | 3.67 | 90-94 | |
| B+ | 3.33 | 85-89 | Good |
| B | 3.0 | 80-84 | |
| B- | 2.67 | 75-79 | |
| C+ | 2.33 | 70-74 | |
| C | 2.0 | 65-69 | Satisfactory |
| C- | 1.67 | 60-64 | |
| D+ | 1.33 | 55-59 | |
| D | 1.0 | 50-54 | |
| FX | 0.5 | 25-49 | Unsatisfactory |
| F | 0 | 0-24 |
Topics of lectures
- Tableau tools
- Calculation fields
- Tableau Products
- Analytical modeling
- Analytical modeling
- Simulation modeling
Key reading
- Бугаев Ю.В. Исследование и моделирование информационных процессов и систем : учебное пособие / Бугаев Ю.В., Коробова Л.А., Черняева С.Н.. — Воронеж : Воронежский государственный университет инженерных технологий, 2022. — 108 c. — ISBN 978-5-00032-589-6. — Текст : электронный // Цифровой образовательный ресурс IPR SMART : [сайт]. — URL: https://www.iprbookshop.ru/128225.html
- Громакова, В. Г. Системный анализ и моделирование социальных процессов : учебное пособие / В. Г. Громакова. — Ростов-на-Дону, Таганрог : Издательство Южного федерального университета, 2022. — 122 c. — ISBN 978-5-9275-4301-4. — Текст : электронный // Цифровой образовательный ресурс IPR SMART : [сайт]. — URL: https://www.iprbookshop.ru/131461.html
- Шагрова Г.В. Методы исследования и моделирования информационных процессов и технологий : учебное пособие / Шагрова Г.В., Топчиев И.Н.. — Ставрополь : Северо-Кавказский федеральный университет, 2016. — 180 c. — Текст : электронный // Цифровой образовательный ресурс IPR SMART : [сайт]. — URL: https://www.iprbookshop.ru/63100.html
- Левенец, А. В. Основы теории информационных процессов и систем : учебное пособие / А. В. Левенец. — Москва, Вологда : Инфра-Инженерия, 2024. — 324 c. — ISBN 978-5-9729-1859-1. — Текст : электронный // Цифровой образовательный ресурс IPR SMART : [сайт]. — URL: https://www.iprbookshop.ru/143547.html
Further reading
- Лихтенштейн В.Е. Математическое моделирование экономических процессов и систем : учебное пособие / Лихтенштейн В.Е., Росс Г.В.. — Саратов : Ай Пи Эр Медиа, 2018. — 129 c. — ISBN 978-5-4486-0350-1. — Текст : электронный // Цифровой образовательный ресурс IPR SMART : [сайт]. — URL: https://www.iprbookshop.ru/74969.html
- Душин, В. К. Теоретические основы информационных процессов и систем : учебник / В. К. Душин. — 5-е изд. — Москва : Дашков и К, 2018. — 348 c. — ISBN 978-5-394-01748-3. — Текст : электронный // Цифровой образовательный ресурс IPR SMART : [сайт]. — URL: https://www.iprbookshop.ru/85208.html
- Захаров О.В. Компьютерное моделирование технологических процессов и систем : учебное пособие / Захаров О.В.. — Саратов : Саратовский государственный технический университет имени Ю.А. Гагарина, ЭБС АСВ, 2023. — 160 c. — ISBN 978-5-7433-3554-1. — Текст : электронный // Цифровой образовательный ресурс IPR SMART : [сайт]. — URL: https://www.iprbookshop.ru/131666.html
