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Graduate Certificate in Business Analytics

Develop your skills in making informed, data-based business decisions

In today’s fast-paced, competitive and dynamic business environment, organizations make decisions that have potential impact not only on their operations, but on the extended enterprise, including suppliers and end consumers. With the explosion of data collection tools and methods, business leaders are faced with a fundamental problem – how do you analyze and use the wealth of data to make smart business decisions that positively impact your organization?

Our certificate program will help you bridge the gap between data collection and data analysis. In just two semesters, you will gain and hone critical skills in statistics, data modeling, data analysis and industry analytics.

PROGRAM SCHEDULE
Part-time graduate certificate program
  • Evening courses designed for working professionals
  • Complete at your own pace taking one or more courses per term
CREDENTIAL EARNED

Graduate Certificate in Business Analytics

DISTINGUISHING CHARACTERISTICS
The Graduate Certificate in Business Analytics provides:
  • An immersive curriculum balancing technical skills and business application
  • Embedded action-based learning projects
  • A program developed in partnership with industry experts and employers
  • Option to apply graduate certificate credits to a degree program, either the MS in Business Analytics or St. Thomas Flex MBA 

Curriculum and Course Descriptions

12 credits total

Required Courses (9 credits) 

Choose One Statistics Course

Statistical Methods for Decision Making (OPMT 600)
3 credits

This course examines statistical and analytical methods including sampling concepts, regression analysis, hypothesis testing, forecasting, quality control, simulation and database management.

Foundations of Data Analysis (R-Environment) (SEIS 631)
3 credits

This course provides a broad introduction to the subject of data analysis, focusing on relevant methods for performing data collection, representation, transformation and data-driven decision making. You will also develop proficiency in the widely-used R language which will be used throughout the course to reinforce the topics covered.

Applied Advanced Business Statistics (OPMT 605)

3 credits

The primary goal of this course is to develop a better understanding of data analysis for business research, emphasizing the interpretation of data rather than calculations. Building upon the groundwork provided by the core MBA statistics course (OPMT 600), topics will include techniques commonly used in business such as logistic regression, two-way analysis of variance and statistics for scale development. These skills are relevant for students involved in marketing research and survey development. Course deliverables will include a project, potentially based on a situation or analysis from students' workplaces or industries. Prerequisites: OPMT 600 or SEIS 631.

Choose one tool course

Spreadsheet Modeling and Data Visualization (OPMT 621)
3 credits

This course is focused on developing the quantitative, analytical skills needed to gain insight into the resolution of practical business problems. Learn to analyze and solve management problems using spreadsheet-based methods. Specific methods of clarifying objectives, developing alternatives, addressing trade-offs and conducting a defensible quantitative analysis will be presented. Topics include spreadsheet modeling, linear programming, transportation modeling, decision analysis, project management and simulation. You will also be introduced to building decision support models using Visual Basic Applications (VBA).

Data Analytics and Visualization (SEIS 632)
3 credits

The course provides an introduction to concepts and techniques used in the field of data analytics and visualization. Insights discovered from the data are then communicated using data visualization. Topics covered in the course include predictive analytics, pattern discovery and best practices for creating effective data visualizations. Through practical application of the above topics, you will also develop proficiency in using analytics tools.

Students can take both courses, and one will apply as their elective.


Elective Courses (3 credits)

Marketing Analytics (MKTG 729)

3 credits

Marketing decisions are increasingly data driven. In this course, students will learn how to analyze marketing data to inform effective decision making. Students will learn how they can develop a deeper and more fully informed understanding of current and emerging customer needs using a broad range of marketing analytic techniques. Students will work hands-on with marketing data as they learn how to master the tools necessary to develop useful customer insights that can guide marketing decisions. Prerequisites: OPMT 600 and MKTG 600 or 625.

Health Care Analytics* (SEIS 735)

3 credits
*requires SQL knowledge

This course will discuss processes in health care analytics, including data acquisition, storage, retrieval, management and analysis of health care data in heterogeneous formats (i.e. numeric health records, medical text and medical images). Major topics include: (1) analyzing patient records and identifying frequent medical sequences for treatment and prevention; (2) evaluating medical text and generating aggregated summary based on hierarchical medical concepts; (3) retrieving information from different types of medical images; (4) building clinic decision support systems to detect possible medical mistakes; and (5) comparing brain connectivity graphs from patients with different neurological conditions. Amazon Cloud will be used to analyze multi-million records of numeric and text data.

Data Mining and Pred. Analytics (SEIS 734)

To overcome data overloading problems, this course will discuss how to apply big data analytics to extract useful patterns from huge datasets and generate visual summary of data. This course will also demonstrate mining and analyzing big data on Amazon Cloud.

Supply Chain Analytics (OPMT 729)

3 credits

The aim of this course is to provide a foundation in the use of a variety of analytical tools for managerial decision making in a supply chain context. The course covers two separate areas of analytics. The first is statistical tools and the second is mathematical modeling and optimization. Both are important areas that are increasingly being utilized in business decision making at all levels. The emphasis of the course will be on the understanding and application of these techniques and tools for decision making, and not on the mathematics of these techniques.

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