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Graduate Certificate in Business Analytics

Choose the format best for you: online or on-campus

In today’s fast-paced, competitive and dynamic business environment, organizations often face complex 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 to leverage this wealth of data to make the best decisions, increase efficiency, and potentially discover new opportunities.

Our four course certificate program will bridge the gap between data collection and data analysis, allowing you to make well-informed, strategic business decisions.  In as little as two semesters, you will build advanced quantitative skills and gain experience with various analytics applications and methods.

You can choose to complete the Graduate Certificate in Business Analytics entirely online or entirely on-campus, or possibly a mix of course formats.  Students selecting the entirely online format at admission will have registration priority for the online course sections.

PROGRAM SCHEDULE
Part-time graduate certificate program
  • Choose between evening on-campus or online course formats
  • Complete at your own pace taking one or two courses per term
  • Flexibility and convenience for working professionals
CREDENTIAL EARNED

Graduate Certificate in Business Analytics

DISTINGUISHING CHARACTERISTICS
The Graduate Certificate in Business Analytics provides:
  • The option to complete the certificate fully online, starting Fall 2018
  • An immersive curriculum balancing technical skills and business application
  • A program developed in partnership with industry experts and employers
  • All graduate certificate courses/credits can be applied to complete the MS in Business Analytics or St. Thomas Flex MBA degree programs

On-campus Certificate Curriculum

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 analytics 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.


Elective Courses (3 credits)

*course has prerequisite(s); may be waived for those with appropriate academic background. Contact program advisor for more information.

Second Analytics Tool Course (OPMT 621 or SEIS 632)

3 credits

Students can take both analytics tool courses (OPMT 621 or SEIS 632), and one will apply as their elective.  This is an ideal option for business analytics certificate-only students (those not concurrently completing a degree program), who may not have required prerequisites for other advanced elective options.

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 or SEIS 631.

Health Care Analytics (SEIS 735*)

3 credits

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.  Prerequisites: SEIS 632 or SEIS 763, and requires knowledge of SQL.


Online Certificate Curriculum

12 credits total

Complete your entire certificate in the online format with these four courses.

Online Certificate: Two Term Completion Plan

Example Plan: Two terms, two courses per term

Fall Term
Statistical Methods for Decision Making (OPMT 600)
Spreadsheet Modeling and Data Visualization (OPMT 621)

Spring Term
Applied Advanced Business Statistics (OPMT 605)
Data Analytics Methods and Applications (OPMT 714)

Online Certificate: One Course per Term Plan

Example Plan: Four terms, one course per term

Fall Term
Statistical Methods for Decision Making (OPMT 600)

Spring Term
Data Analytics Methods and Applications (OPMT 714)

Summer Term
Spreadsheet Modeling and Data Visualization (OPMT 621)

Fall Term
Applied Advanced Business Statistics (OPMT 605)

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