The program’s four required courses must be taken in the following sequence.
Applied Statistics – This course teaches quantitative methods used in business analysis. Statistics is a key component both in the planning and evaluation of business projects across finance, marketing and operations. Topics include descriptive statistics, analysis of variance, statistical process control, correlation, regression, hypothesis testing and decision trees.
Database Management Systems – This course will offer an introduction to the principles, design, implementation and applications of database management systems. Topics include introduction to normalization, database creation and maintenance, data loading, recovery planning, security, generating reports and changing databases in response to business demand.
Predictive Modeling – This course teaches students to make effective use of scientific research processes to enhance decision-making. This process involves understanding how to develop key research questions, model and theory building, information uncertainty, data collection methods, data cleaning, analytics and reporting. Through business cases, students will learn about qualitative and quantitative research, experimental design, offline vs. online data collection, interviews and surveys, multivariate analysis, text analytics, reporting and data visualization.
Data Mining – This course will offer an introduction to the major principles and techniques used in data mining from an algorithmic perspective, and using a database management system (DBMS). Topics include data preparation and feature selection, association rules, classification, clustering, evaluation and validation, scalability, spatial and sequence mining and data mining application.