Courses
OPSM 490
ORGB 401
Basic functions of Human Resource Management from a generalist perspective for all managers; job design, recruitment, selection, training and career development, compensation and benefits, performance appraisal and discipline in organizations; current developments in HRM abroad and in Türkiye.
QMBU 401
Computer simulation as a means of evaluating designs and operating procedures for complex systems; systems analysis, modeling, use of simulation languages/software, experimental design and statistical analysis.
QMBU 451
QMBU 454
ORGB 302
This course is designed to provide students with an understanding of the behavior of individuals and groups in organizations. Students will identify and develop the skills needed to make an effective contribution to organization, to manage others, and to maintain a high quality of work life. Topics covered include: motivation, communication, conflict negotiation, group dynamics, leadership, organizational&job design, and change management
QMBU 310
Fundamental quantitative methods for business decision making: problem formulation, analysis, and use of management science tools, such as linear and integer programming, decision analysis and Monte Carlo simulation with spreadsheets. Extensive use of business applications.
QMBU 450
QMBU 453
QMBU 456
OPSM 495
QMBU 301
Statistical techniques in business data analysis; decision making under uncertainty. Concept of loss functions, decision trees, Bayes' Rule; correlation analysis, simple and multiple regression analysis (variable selection, model building, residual analysis); exponential smoothing methods; autoregressive (AR), moving average (MA), and ARMA models; introduction to intervention analysis, outlier-level shift-variance change detection procedures , and autoregressive conditional heteroscedasticity models. Extensive use of computer-based computational tools and business applications.
QMBU 420
Business Value Creation with Big Data. Data sources. Data mining tasks and supervised/ unsupervised learning. Evaluation criteria. Generalizing from data versus overfitting. Data mining process. Data collection strategy. Security, privacy and ethical considerations. Case studies.
