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[1] Management Information Systems (MIS)
5320 CRITICAL THINKING AND EXPERIMENTAL DESIGN This course provides a foundation for critical thinking in business. It examines the problem-solving process and applies this process to different cases, using a variety of tools, including root cause analysis and mind mapping. Using this process, students apply it in the design of experiments; including randomization, factorial, and block designs.
5330 PRESCRIPTIVE ANALYTICS This course emphasizes an understanding of quantitative aids to decision analysis, utility and game theory, linear programming, queuing theory, simulation techniques, network analysis, and/or Markov processes. Lecture/discussion. Prerequisite: QMTH 2330 Business Statistics [ACTS: BUSI2103] or equivalent.
5380 BUSINESS INTELLIGENCE AND DATA VISUALIZATION This course focuses on business intelligence (Bl), a broad category of technologies, applications, and processes for visualizing and modeling data to help users make better decisions. The course offers coverage of BI processes and technologies, data visualization, and management concerns such as measurement, performance, and individual/organizational impacts. Practical experience in data visualization is provided through projects using leading-edge tools.
5381 DATA MINING AND APPLIED ANALYTICS This course focuses on development of the quantitative and analytical skills required to model, analyze, interpret, and solve managerial decision-making problems. Students will use current techniques and tools to develop the ability to answer business questions through the analysis of data. Techniques include classification, clustering, text mining, and other appropriate techniques. Tools introduced include the R statistical environment and current graphical data mining tools.
6325 PREDICTIVE ANALYTICS This course focuses on predictive data analytics. It is an option for the Graduate Certificate in Data Analytics and an elective in the MBA and MAcc programs. The course stresses using data analytics software to solve business problems and explain results. The course includes in-depth study of problem-solving methodologies, regression, forecasting, data modeling, and technical report writing. Students will be expected to do more than understand how to use analytics software; they will be required to synthesize and interpret results. Prerequisite: QMTH 2330 Business Statistics [ACTS: BUSI2103] or equivalent.
6335 PYTHON FOR DATA ANALYTICS This course introduces students to data analytic concepts using one of the leading toolsets in this field, the Python language and its related analytical ecosystem. Students will learn fundamental data analytics techniques and apply them using Python-based tools to clean, transform, and analyze data.
6365 DATA WAREHOUSING AND DATA MANAGEMENT This course examines data management concepts and techniques via a blended approach of student-led discussions and hands-on directed labs. Topics will range from conceptual discussions of data governance and stewardship to combined concept and application approaches surrounding database administration and data quality management. It will include more advanced topics such as data warehousing, document management, and using structured query language (SQL) statements.
6370 APPLIED DATA ANALYTICS PROJECT This course is a culminating course in the MS Applied Data Analytics program and should be taken in the student’s final term. It is also an elective in the MBA program. Students will conduct an original project in which they apply one or more data analytical methods to a dataset to create an actionable recommendation. The deliverables for the course include a paper documenting the student’s project and the presentation of their results. Prerequisite: 15 hours in the MS-Applied Data Analytics or MBA program (MBA classes must include a minimum of 9 hours of Data Analytics course hours).