Computer Applications (CAP)
This is an introductory course in the theory and application of storing, retrieving, and analyzing big data using the Hadoop framework. Topics include an overview of historical and future trends in big data, an overview of the Hadoop ecosystem, planning a Hadoop cluster, installing and configuring Hadoop, the Hadoop Distributed File System, MapReduce, managing and scheduling jobs, and cluster administration and management.
This course consists of a supervised work experience in an approved training environment. The internship provides an opportunity for students to develop the appropriate attitudes and skills necessary for success in data management science.
This is an introductory course in the theory and application of automatic knowledge exploration and discovery from data. Topics include data transformations, classification, regression, rule induction, clustering, and graphical models.
This course integrates the knowledge, skills, and abilities learned in the Data Management Science Program through the completion of a comprehensive capstone project. This capstone course must be taken in the last semester of the program.