This course introduces advanced concepts in predictive modeling and techniques to discover patterns in data, identify variables with the most predictive power, and develop predictive models. Students are introduced to descriptive, predictive, prescriptive analytics, and optimization models. The course utilizes Microsoft Excel to engineer and analyze business models. Students identify the proper use of complete regression, optimization, and exponential smoothing models.

Upon completion of this course, students are expected to be able to do the following:

• Utilize datasets to develop statistics and probability to predict future outcomes
• Implement appropriate models needed to analyze and critically evaluate business objectives
• Develop written and oral communication skills required to report on data-intensive business situations
• Organize data-intensive content in a professional setting.
• Execute advanced analytics techniques

This course explores best-practice data visualization techniques. Professional storytelling and graphic design skills are introduced. Students study effective strategies and visualization tools to communicate with business decision-makers.

Upon completion of this course, students are expected to be able to do the following:

• Source appropriate data to create effective visualization’s
•  a compelling story with data to drive business action
• Design persuasive data visualizations to communicate information to the viewer
• Build visualizations that assist in error detection and data preparation

This course focuses on explaining complex datasets, models, and analyses to stakeholders, including internal and external organizations and personnel of multiple disciplines. Audience analysis and effective strategic communication are studied. Students identify and analyze problems. Professionalism in both oral and written communication is expected.

Upon completion of this course, students are expected to be able to do the following:

• Conduct stakeholder analysis and communications results
• Identify business problems and create analytical approaches to solve them
• Write reports based on best-practice data analysis frameworks
• Demonstrate best practice communication techniques to visualize, explore, and act on data science findings

Prerequisites: BIA 630, MBA 633, DIGA 605, BIA 640

This course introduces the concepts of spatial data creation, editing, and analysis using GIS software. Emphasis is placed on spatial concepts and understanding and utilizing standard operating procedures. Topics covered include coordinate systems, data creation, derivation, editing, metadata, proximity and overlay analysis, and cartography. Technical proficiency is a primary objective of the course, reinforced by effective practical exercises utilizing GIS software. Examples of how the geospatial industry provides location intelligence to various disciplines are explored.

Upon completion of this course, students are expected to be able to do the following:

• Apply knowledge of principles, theories, and concepts of spatial data analysis
• Demonstrate standard techniques for creating, editing, storing, querying, and analyzing geospatial data
• Use cartographic design principles for visual storytelling and effective communication
• Implement practices to promote spatial data integrity based on understanding sources of error in spatial data

• An undergraduate degree from a regionally accredited institution
• A minimum GPA of 2.75 on a 4.0 scale
• A written statement: Your background and future goals all impact your success with Saint Mary’s and inform your education. As you prepare your written statement, think about including previous experiences, education, and your strengths and interests. Share your motivations for entering the online human resource management certificate program and how it will contribute to your career

No prerequisite coursework is required for the Business Analytics certificate online program.

You don’t need GRE/GMAT scores to apply for this program.

Transfer credits are not accepted for this program.

Students with transcripts from universities outside the United States, the United Kingdom, Ireland, New Zealand, Australia, and Canada (except for the Quebec Province) must take and pass English proficiency testing

• Test of English as a Foreign Language (TOEFL) with a minimum score of 72
• International English Language Testing System (IELTS) with a minimum score of 6.0
• Michigan Language Assessment Battery (MELAB) with a minimum score of 74%
• International Test of English Proficiency (ITEP) with a minimum score of 4.0 or Pearson Test of English with a score of 51
• Duolingo with a minimum score of 100

Whether you apply through our online application via hard copy, or in-person with a Saint Mary’s admissions counselor, your application must include the following items:

Official transcripts: An official transcript issued to Saint Mary’s University of Minnesota from the institution posting the applicant’s completed degree and other relevant transcripts documenting program prerequisites and potential transfer credits must be sent separately and directly from your institution. Saint Mary’s University of Minnesota accepts official transcripts electronically from previously attended institutions. Transcripts should be sent to oladmissions@smumn.edu or mailed to:

Transcript Processing Center
Saint Mary’s University of Minnesota
851 Trafalgar Court, Suite 420
Maitland, FL 32751

An up-to-date résumé: Include both your educational and professional experience.

Two references: Provide the names of two people (including title, organization, email, and phone number) who can serve as professional references, if needed, during the application review process. The best references are those who know you professionally, such as current or former supervisors.

Upcoming application deadlines for Saint Mary’s Business Analytics certificate online program:

• Spring: December 18, 2023
• Summer: April 22, 2024
• Fall: August 20, 2024

Upcoming start dates for Saint Mary’s Business Analytics certificate online program:

• Spring: January 8, 2024
• Summer: May 6, 2024
• Fall: September 3, 2024

Once you’ve submitted your application, expect to be notified about acceptance approximately two weeks after your submission date.