Businesses of all sizes are creating and storing more data than ever before according to IBM—2.5 quintillion bytes per day. Businesses are swimming in data, but often lack the talent and expertise to use it effectively for making decisions, revealing insights, and making predictions. Business analytics experts are changing that. The full-time Master of Science program in business analytics puts students on the leading edge of a burgeoning industry hungry for top notch talent.

Students learn the skills and techniques necessary to turn raw data into actionable insights. Descriptive and diagnostic analytics are just starting points in the program. The skills learned develop students into decision-makers and data scientists adept at using predictive and prescriptive analytics to solve business problems.

The full-time program is located in Iowa City. The plan of study spans 16 months, and includes core courses, internships, and electives.

The full-time Master of Science program in business analytics requires a minimum of 40 s.h. of graduate credit. Transfer credit may be accepted with approval from the program. A major g.p.a. and a cumulative g.p.a. of at least 2.75 is required in all coursework.

The M.S. with a major in business analytics requires the following coursework.

Core Courses19
Experience Course/Project3
Total Hours40

Core Courses

All of these:
BAIS:6050Data Management and Visual Analytics3
BAIS:6070Data Science3
BAIS:9100Data and Decisions3
BAIS:9110Advanced Analytics3
BAIS:9400Professional Development and Business Acumen (taken fall and spring semester for 1 s.h. each)2
MBA:8130Business Communication (taken fall and spring semester for 1 s.h. each)2
One of these:
BAIS:6040Data Programming in Python3
BAIS:6060Data Programming in R3

Experience Course/Project

The experience course consists of a group project that solves a semester-long business problem.

This course:
BAIS:6120Analytics Experience3


Elective coursework allows students to deepen or broaden their skills. Additional electives may be available for credit but must be preapproved.

18 s.h. from these:
BAIS:4280Data Security3
BAIS:6040Data Programming in Python (if not taken as core course)3
BAIS:6060Data Programming in R (if not taken as core course)3
BAIS:6100Text Analytics3
BAIS:6105Social Analytics3
BAIS:6110Big Data Management and Analytics3
BAIS:6130Applied Optimization3
BAIS:6140Information Visualization3
BAIS:6150Financial Analytics3
BAIS:6180Healthcare Analytics3
BAIS:6210Data Leadership and Management3
BAIS:6220Business Analytics Certification Workshop3
BAIS:9210Introduction to Modeling with VBA3
ACCT:9170Advanced Accounting Analytics3
BIOS:5120/IGPI:5120/STAT:5610Regression Modeling and ANOVA in the Health Sciences3
BIOS:5310/IGPI:5310/STAT:5810Research Data Management3
CS:3210Programming Languages and Toolsarr.
CS:4420Artificial Intelligence3
CS:4470Health Data Analytics3
CS:5110/IGPI:5110Introduction to Informatics3
CS:5430Machine Learning3
ECE:5450/IGPI:5450Machine Learning3
ECON:4800Econometric Analysis3
ECON:5805Statistics for Economics3
EPID:5200/IGPI:5220Principles of Public Health Informatics3
GEOG:3520/IGPI:3520GIS for Environmental Studies3
GEOG:3540/IGPI:3540Introduction to Geographic Visualization3
GEOG:4150/GHS:4150/IGPI:4150Health and Environment: GIS Applications3
GEOG:4580/IGPI:4581Introduction to Geographic Databases3
ISE:3600/CEE:3142/STAT:3620Quality Control3
ISE:6380Deep Learning3
ISE:6720Nonlinear Optimization3
ISE:6760Pattern Recognition for Financial Data3
ISE:6780Financial Engineering and Optimization3
JMC:3640Data Journalism3-4
ME:4111/CEE:4511Scientific Computing and Machine Learning3
ME:4150Artificial Intelligence in Engineering3
MKTG:9165Digital Marketing Analytics3
MKTG:9310Marketing Analytics3
POLI:3001Hawkeye Poll3
PSQF:6209/EPLS:6209Survey Research and Design3
PSQF:6243/STAT:6513Intermediate Statistical Methods4
PSQF:6246/STAT:6516Design of Experiments4
PSQF:6250Computer Packages for Statistical Analysis (not recommended if completed BAIS:6060)1-3
STAT:4100/IGPI:4100Mathematical Statistics I3
STAT:4101/IGPI:4101Mathematical Statistics II3
STAT:4200/IGPI:4200Statistical Methods and Computing3
STAT:4540/IGPI:4540Statistical Learning3
STAT:4560Statistics for Risk Modeling3
STAT:5100Statistical Inference I3
STAT:5200/IGPI:5199Applied Statistics I4
STAT:5400/IGPI:5400Computing in Statistics3
STAT:6560Applied Time Series Analysis3
STAT:7400/IGPI:7400Computer Intensive Statistics3
URP:6200/PBAF:6200Analytic Methods I1-3
URP:6225Applied GIS for Planners3
May include 6 s.h. from these:
ENTR:9800Entrepreneurship: Advanced Business Planning1-3
MBA:8140Corporate Financial Reporting3
MBA:8170International Economic Environment of the Firm3
MBA:8180Managerial Finance3
MGMT:3200Individuals, Teams, and Organizations3
MGMT:4325Team and Project Management3
MGMT:9150/HMP:6360/PBAF:6278/RELS:6070/SPST:6010/SSW:6247/URP:6278Nonprofit Organizational Effectiveness I3
MGMT:9160/HMP:6365/PBAF:6279/RELS:6075/SPST:6020/SSW:6248/URP:6279Nonprofit Organizational Effectiveness II3

M.S./M.S. in Finance

The combined Master of Science in business analytics (career subprogram)/Master of Science in finance allows students to pursue two degrees simultaneously, earning both more quickly than they would if the degrees were pursued separately. The Department of Business Analytics collaborates with the Department of Finance to offer the combined program.

Separate application to each degree program is required. Applicants must be admitted to both programs before they may be admitted to the combined program. For more information, see the M.S. in finance in the Catalog.

Applicants must meet the admission requirements of the Graduate College and of the program; see the Manual of Rules and Regulations of the Graduate College on the Graduate College website and program requirements on the Full-Time Master of Business Analytics Admissions web page.

Sample Plan of Study

Sample plans represent one way to complete a program of study. Actual course selection and sequence will vary and should be discussed with an academic advisor. For additional sample plans, see MyUI.

Business Analytics (career), M.S.

Plan of Study Grid (Manual)
Academic Career
Any SemesterHours
40 s.h. of graduate level coursework must be completed; up to 6 s.h. of graduate transfer credits allowed upon approval. More information is included in the General Catalog and on department website. a  
Maintain at least a 2.75 cumulative and program GPA.  
First Year
Any Semester
Meet with your Career Management coach and Professional Director.  
Attend Career Management Center sessions offered.  
Apply to and secure a summer internship or arrange a summer research project.  
BAIS:6050 Data Management and Visual Analytics 3
Data Programming in R
or Data Programming in Python
BAIS:9100 Data and Decisions 3
BAIS:9400 Professional Development and Business Acumen b 1
Elective course c 3
Arrange for the Career Management Center to review updated resume, then upload to Handshake.  
BAIS:6070 Data Science 3
BAIS:9110 Advanced Analytics 3
BAIS:9400 Professional Development and Business Acumen b 1
MBA:8130 Business Communication d 1
Elective course c 3
Elective course c 3
Complete end of semester employment placement survey as requested by Career Management.  
Internship: complete a summer internship e  
Research: complete a summer research project e  
Second Year
Any Semester
Meet with your Career Management coach and Professional Director.  
Attend Career Management Center sessions offered.  
BAIS:6120 Analytics Experience 3
MBA:8130 Business Communication d 1
Elective course c 3
Elective course c 3
Elective course c 3
Complete end of semester employment placement survey as requested by Career Management.  
Verify completion of all degree requirements with program administrator.  
Apply to and secure post-graduation employment.  
 Total Hours40