https://herbert.miami.edu/graduate/find-and-compare-programs/business-analytics/index.html

Overview

The Master of Science in Business Analytics program is an intensive experience that develops well-trained business analysts armed with the skills necessary to understand, manage and make use of big data in a business context. Over the course of 10 months, students learn how to turn abstract data into meaningful information with which to predict consumer behavior and forecast revenue and expenses for virtually any business model and any industry sector.

To obtain detailed program admission information, please reference the program brochure which can be requested by contacting Graduate Business Admissions at 305-284-2510, by email @mba@miami.edu, or visiting the Miami Herbert Business School website.

Admission Requirements

  • Completed application for admission submitted through BusinessCAS

  • A baccalaureate degree from an accredited institution

    • Official academic transcripts from all previously attended post-secondary institutions must be submitted directly to BusinessCAS.

    • International applicants must have their educational credentials from institutions outside of the United States verified by an approved international credentialing evaluation service such as World Education Services to confirm degree equivalency and GPA calculation.

  • Statement of purpose and short-essay responses to the career goal and program-related questions in BusinessCAS

  • Current resume outlining your professional and/or academic achievements

  • At least one letter of recommendation is required. Up to three may be submitted.  

  • Official GMAT (or GRE) score to be sent directly to the University of Miami Herbert Business School by using the institution code below.

    • GMAT Institution Code is 7NV-S1-00

    • GRE Institution Code is 5815

  • An official TOEFL or IELTS score is required as proof of English proficiency for international  applicants who did not receive a degree in the United States or a foreign country where English is the primary language. The following minimum score is required for admission to a graduate business degree program.

    • TOEFL - 94 or above, institution code is 5815

    • IELTS - 7.0 or above, institution code is 4861 

If you do not yet have a GMAT or GRE score and/or TOEFL or IELTS score (international candidates only), you may complete and submit your application prior to taking the exam by indicating your approximate date within the Standardized Tests tab in the Academic History section. Select “Add Test Score” by the relevant test, then indicate that you have not yet taken the exam and add your estimated test date in the section provided.

GMAT/GRE waivers can be granted on a case-by-case basis. Should you wish to request a waiver, in your BusinessCAS application make sure to "opt-out" of submitting a test score. You will then need to upload a page summary of why you should be considered for a waiver.

Conditional Admission:  If you have not achieved the minimum TOEFL or IELTS score but possess a strong academic performance you may be considered for conditional admission. A minimal TOEFL score of 80 or an IELTS score of 6.5 is required to be considered for conditional admission. These students must successfully complete a 4-week Graduate Business English Certificate Course prior to matriculating in the academic program. Click here for more information about the English for Graduate Business English Certificate Course.

We encourage candidates to upload unofficial transcripts and test scores (if required) with their BusinessCAS application in order to expedite the review of their file while official documents are processed.

QUESTIONS?

Connect with Miami Herbert Business School’s graduate enrollment advisors at (305) 284-2510, by email at mba@miami.edu, or visit the Miami Herbert Business School website.

 

Curriculum Requirements

Required Courses
BUS 610Communicating for Career Success2
MAS 627Programming for Data Analytics2
MAS 631Statistics for Managerial Decision Making2
MAS 632Management Science Models for Decision Making2
MAS 637Applied Regression Analysis I2
MAS 639Data Acquisition, Preparation, and Visualization2
MAS 648Machine Learning for Data Analytics I2
MAS 650Business Analytics Internship 12
or MAS 652 Business Analytics Capstone Project
MGT 697Graduate Business Career Connect Course1
Electives16
At least two of the following: 2
Applied Time Series Analysis and Forecasting
Applied Regression Analysis II
Big Data Analytics
Machine Learning for Data Analytics II
Additional Electives: 3 and 4
SAS Programming for Business Analytics
Introduction to Quality Management
Dashboard Tools for Visual Analytics
Administrative Systems for Quality Management
Business Analytics Consulting
Business Analytics Capstone Project
Introduction to Accounting Analytics
Financial Reporting and Analysis
Python Programming
Foundations in Management Consulting
Supply Chain Analytics
Marketing Analytics
Total Credit Hours33
1
Students may take MAS 652 Business Analytics Capstone Project as a replacement of MAS 650 Business Analytics Internship if an internship cannot be obtained.
2

Students must take at least two courses between MAS 640, MAS 646, MAS 649 & MAS 651

3

16 credits of electives (approximately 8 courses) are required.  Elective offerings are based on class demand.

4

List contains commonly taken electives but is not exhaustive.

The curriculum defines a common core of required courses (17 credits) and allows the selection of elective courses (16 credits). A minimum of 4 elective credits must be taken from MAS 640, MAS 646, MAS 649, or MAS 651. 

At least one term of part-time (10-20 hours per week) practical training and concurrent enrollment in MAS 650 is mandatory for the Master of Science in Business Analytics degree. Practical training is defined as "alternative work/study, internship, cooperative education, or any other type of required internship or practicum that is offered by sponsoring employers, conforming to the academic calendar."  The practical training and concurrent enrollment in MAS 650 must be approved in advance by the faculty director. International students in F-1 status are required to obtain authorization for Curricular Practical Training (CPT) from the Department of International Student and Scholar Services (ISSS) prior to engaging in off-campus employment. A student may take MAS 652 Business Analytics Capstone in place of MAS 650 if the student is unable to secure practical training, provided that the student can show that they have put sufficient effort into seeking practical training opportunities. Requests to enroll in MAS 652 in place of MAS 650 must be approved by the faculty director.

Sample Plan of Study

Plan of Study Grid
Year One
FallCredit Hours
MAS 631 Statistics for Managerial Decision Making 2
Session I
MAS 627 Programming for Data Analytics 2
MAS 637 Applied Regression Analysis I 2
MAS 639 Data Acquisition, Preparation, and Visualization 2
MGT 697 Graduate Business Career Connect Course 1
Elective 2
Session II
BUS 610 Communicating for Career Success 2
MAS 632 Management Science Models for Decision Making 2
MAS 648 Machine Learning for Data Analytics I 2
Elective 2
 Credit Hours19
Spring
Session I
MAS 640 Applied Time Series Analysis and Forecasting 2
MAS 646 Applied Regression Analysis II 2
MAS 651 Machine Learning for Data Analytics II 2
Elective 2
Session II
MAS 649 Big Data Analytics 2
MAS 650 or 652 Business Analytics Internship
or Business Analytics Capstone Project
2
Elective 2
 Credit Hours14
 Total Credit Hours33

Mission

  • To develop individuals that are prepared to use the methods and technology of analytics and data science to impact global business and society.

Student Learning Outcomes

  • Students will develop skills in acquiring, preparing and visualizing data.
  • Students will develop and use data mining methods and software tools.
  • Students will learn to use decision models.
  • Student will develop and use predictive models.
  • Student will demonstrate an understanding of career acceleration and lifelong learning strategies.