Decision Sciences

Decision Sciences Course Offerings

Decision Sciences course offerings will be found under the 4 letter code of DSCI in the course listings.  

219 – Foundations for Data Science (3)

Skills and tools in acquiring, parsing, manipulating, and preparing data for statistical analysis. Course previously taught as BUAD 219.

259 – Applied Statistics and Business Research (3)

Prerequisite: MATH 200 or similar Statistics course. This course introduces students to the scientific method to facilitate their understanding of what constitutes good and bad research and enable them to design and conduct research studies.  In addition, the course provides students with skills necessary to analyze, synthesize and evaluate statistical information in order to make informed and appropriate decisions in the workplace and to prepare students for research courses in graduate school.  Course previously taught as BUAD 259.

353 – Decision Analysis (3)

Prerequisite: MIST 201 or equivalent and MATH 200 or similar statistics course.  This course introduces a variety of Management Science models for use in analysis of “business” problems.  A computer software package provides the computational basics for case analysis of problems in linear programming, inventory, waiting lines, PERT/CPM, and simulation.  Course previously taught as BUAD 353.

363 – Operations Management (3)

Prerequisite: DSCI 353 or equivalent; and business administration major or permission of the Associate Dean for Faculty.  Operations management is an area of business concerned with the production of goods and services.  It involves the study of concepts, theories and techniques relating to the operations functions in both manufacturing and service organizations.  Lectures, discussions, and case studies are used to provide a comprehensive knowledge of the theories, current practices, and trends in several topical areas of operations management.  Quantitative tools of analysis used to support decision making in the various operations management are surveyed.  Course previously taught as BUAD 363.

401 – Foundation and Applications of Data Analytics (3)

Prerequisite: Grade of C or better in CPSC 220 or equivalent.  This course develops an overview of the challenges of developing and applying analytics for insight and decision making.  Examples and cases will come from customer relation management, price modeling, social media analytics, location analysis and other business domains.  Course previously taught as BUAD 403.

402 – Analytics Applications and Development (4)

Prerequisite: Grade of C or better in CPSC 220 or equivalent.  A course in programming and data manipulation techniques for constructing analytics-based applications.  Topics include SQL or no-SQL databases, using web service API’s to acquire data, introduction to Hadoop and MapReduce, and use of third-party analytic component API’s.  Course previously taught as BUAD 400.