Subject: Business Analytics (17.IM2821 )
Native organizations units: Department of Industrial Engineering and Engineering Management, Chair of Production Systems, Organization and Management
Study programmes of the course:
| Type of studies | Title |
|---|
Educational goal:
This course aims at acquiring practical and theoretical knowledge and competencies for problem-solving in various business situations. Some of the areas that will be covered include working with business data, their transformation, visualization as well as designing business models (optimization, simulation and regression). The primary focus of the course will be solving problems that require descriptive, predictive and prescriptive analytics.
Educational outcome:
Students will learn to work individually and in teams at private and public companies that use business analytics. Graduate engineer-master of industrial engineering and management acquires the competencies for big data analysis using statistics, probability and simulations as analytical tools.
Course content:
Introduction to statistics and Excel. Decision-making in business. Monte Carlo simulation. Linear regression. Time series analysis. Forecasting. Data visualization. Data mining. Linear optimization models.
Teaching methods:
Classes include lectures that include practical examples of business modeling and simulation. Tutorial sessions encourage team work on analysis of simulations and data processing by using various methods. Tutorial sessions are held in computer labs.
Literature:
| Authors | Title | Year | Publisher | Language |
|---|---|---|---|---|
| Gradojević N., Đaković V. | Poslovna analitika, elektronska skripta | 2017 | Fakultet tehničkih nauka, Novi Sad | English |
| 2017 | English | |||
| 2001 | English | |||
| 2017 | English |
Knowledge evaluation:
| Course activity | Pre-examination | Obligations | Number of points |
|---|---|---|---|
| Project | Yes | Yes | 15.00 |
| Written part of the exam - tasks and theory | No | Yes | 50.00 |
| Project task | Yes | Yes | 25.00 |
| Lecture attendance | Yes | Yes | 10.00 |
Lecturers:
Naučni saradnik dr Todić Vladimir
Science Associate
Computational classes
prof. dr Gradojević Nikola
Full Professor
Lectures
prof. dr Đaković Vladimir
Full Professor
Computational classes
prof. dr Đaković Vladimir
Full Professor
Lectures
prof. dr Gradojević Nikola
Full Professor
Computational classes
Faculty of Technical Sciences
© 2024. Faculty of Technical Sciences.
Contact:
Address: Trg Dositeja Obradovića 6, 21102 Novi Sad
© 2024. Faculty of Technical Sciences.