This course provides students with basic knowledge of Information Systems and Business Analytics and their use for business operations, managerial decision-making, and strategic advantage. The computer hardware, software, and networks are discussed. The development and use of databases and data warehouses are addressed. Various tools and techniques for data interrogation, visualization, presentation, data mining, and predictive analytics are examined. Students will gain hands-on experience and develop skills necessary for working with large data sets from various business areas.
This course provides knowledge and practical skills involving contemporary techniques and methods for data mining and predictive analytics. Methods and techniques covered include cluster analysis, associations, multiple and logistic regressions, classification, and regression trees. Several software packages used for contemporary data analytics will be reviewed and compared. The course includes practical experience using MS Excel and IBM SPSS.
Topics are selected on basis of student need and academic qualifications of staff. If regular lectures are not given, a minimum of 30 hours of work for each hour credit must be included. This course may be repeated for credit.
