Business Analytics | Faculty of Technical Sciences

Subject: Business Analytics (17.IM2821)

Native organizations units: Department of Industrial Engineering and Engineering Management, Chair of Production Systems, Organization and Management

General information:

Category	Professional-applicative
Scientific or art field	Menadžment i investicije u inženjerstvu Proizvodni i uslužni sistemi, organizacija i menadžment
ECTS	4

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.

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.

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.

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.

Authors	Title	Year	Publisher	Language
Edward Tufte	The Visual Display of Quantitative Information (2nd Ed.)	2001	Cheshire, CT: Graphics Press	English
Gradojević N., Đaković V.	Poslovna analitika, elektronska skripta	2017	Fakultet tehničkih nauka, Novi Sad	English
Camm, Cochran, Fry, Ohlmann, Anderson, Sweeney, and Williams	Essentials of Business Analytics (2nd Ed.)	2017	Cengage Learning	English
Daniel T. Larose	Discovering Knowledge in Data: An Introduction to Data Mining (2nd Ed.)	2017	Wiley	English