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Gain Knowledge & Expertise

Graduate Certificate in Business Analytics Curriculum

Develop Technical and Decision-Making Skills

Bridge the gap between data collection and data analysis, and learn to make more informed, strategic business decisions. In this four-course certificate program, you will build advanced quantitative skills and gain experience with various analytics applications and methods.

The curriculum is developed in partnership with industry experts, to ensure that what you learn at St. Thomas is up-to-date and highly applicable in the real world. You’ll take a combination of required and elective courses.

Complete the Graduate Certificate in Business Analytics entirely online or entirely on campus, or a mix of both. Complete the program at your own pace, taking one or two courses each semester, and finish in as few as 9 months.

Plan Out Your Program

Follow these sample plans to complete the Graduate Certificate in Business Analytics in 2 or 4 semesters. An asterisk (*) denotes courses that are offered online.

Semester I (6 credits)
Statistical Methods for Decision-Making*
Spreadsheet Modeling and Data Visualization*
Semester II (6 credits)
Applied Advanced Business Statistics*
Elective
Semester I (6 credits)
Statistical Methods for Decision-Making*
Spreadsheet Modeling and Data Visualization*
Semester II (6 credits)
Applied Advanced Business Statistics*
Elective
Semester I (3 credits)
Statistical Methods for Decision-Making*
Semester II (3 credits)
Spreadsheet Modeling and Data Visualization*
Semester III (3 credits)
Applied Advanced Business Statistics*
Semester IV (3 credits)
Elective
Semester I (3 credits)
Statistical Methods for Decision-Making*
Semester II (3 credits)
Spreadsheet Modeling and Data Visualization*
Semester III (3 credits)
Applied Advanced Business Statistics*
Semester IV (3 credits)
Elective

Certificate Curriculum

12 Credits Total

Statistical Methods for Decision Making (OPMT 600)

3 credits

Gain a basic understanding of the role of statistics in the gathering of data, the creation of information and its use in decision-making. Learn methods for summarizing data, both numerically and graphically, and for drawing conclusions from sample data. Carry out statistical analyses using the computer and statistical software. The course focuses on how statistical methods can be placed on the design of statistical studies, collection of data, and the interpretation of results (rather than the details of computation). *online option offered

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

3 credits

Get a broad introduction of data analysis, focusing on relevant methods for performing data collection, representation, transformation and data-driven decision-making. Develop proficiency in the widely-used R language.


Applied Advanced Business Statistics (OPMT 605)

3 credits

Gain a better understanding of data analysis for business research, with an emphasis on the interpretation of data rather than calculations. Building upon the groundwork provided by the core MBA statistics course (OPMT 600), we’ll explore techniques commonly used in business such as logistic regression, two-way analysis of variance and statistics for scale development. You’ll create a project, potentially based on a situation or analysis from your workplace or industry.  Prerequisite: OPMT 600 or SEIS 631. *online option offered


Spreadsheet Modeling and Data Visualization (OPMT 621)

3 credits

Develop the quantitative, analytical skills needed to resolve practical business problems. Learn to analyze and solve management problems using spreadsheet-based methods. Explore specific methods of clarifying objectives, developing alternatives, addressing trade-offs and conducting a defensible quantitative analysis. 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). *online option offered

Data Analytics and Visualization (SEIS 632)

3 credits

Learn about concepts and techniques used in the field of data analytics and visualization. Develop proficiency with analytics tools. Use insights discovered from the data to communicate using data visualization. Topics include predictive analytics, pattern discovery and best practices for creating effective data visualizations.

You can take both analytics tool courses (OPMT 621 and SEIS 632), and one will apply as your elective. This is a good option if you don’t meet the prerequisites for the other, more advanced elective courses.


To complete your Graduate Certificate in Business Analytics, you must take one 3-credit elective. You can take both analytics tool courses (OPMT 621 and SEIS 632), and one will apply as your elective. Or if you meet the prerequisites, you can take one of these more advanced electives.

Marketing Analytics (MKTG 729)

Marketing decisions are increasingly data driven. In this course, you’ll learn to analyze marketing data for more informed, strategic decision-making. Develop a deeper and more fully informed understanding of current and emerging customer needs using a broad range of marketing analytic techniques. Work hands-on with marketing data, to uncover the customer insights that can guide marketing decisions. Prerequisites: OPMT 600 or SEIS 631.

Health Care Analytics (SEIS 735)

Learn about 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 analyzing patient records and identifying frequent medical sequences for treatment and prevention; and evaluating medical text and generating aggregated summary based on hierarchical medical concepts. We’ll use Amazon Cloud to analyze multi-million records of numeric and text data. Prerequisite: SEIS 630 and SEIS 632


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