Businesses of all sizes are creating and storing more data than ever before according to IBM—2.5 quintillion bytes per day. In fact, 90 percent of all data that exists today was created in the last two years. 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 39 s.h. of graduate credit. Transfer credit may be accepted with approval from the program. 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.
|All of these:|
|MSCI:6050||Data Management and Visual Analytics||3|
|MSCI:6060||Data Programming in R||3|
|MSCI:9100||Data and Decisions||3|
The experience course consists of a group project that solves a semester-long business problem.
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:|
|MSCI:6040||Data Programming in Python||3|
|MSCI:6110||Big Data Management and Analytics||3|
|MSCI:6160||Big Data Analytics||3|
|MSCI:6170||Directed Readings - Graduate Business Analytics||arr.|
|MSCI:6210||Data Leadership and Management||3|
|MSCI:6500||Social Network Analytics: Models and Algorithms||3|
|MSCI:7000||Management Sciences Topics||3|
|MSCI:9010||Contemporary Topics in Analytics||1-3|
|MSCI:9130||Lean Process Improvement||3|
|MSCI:9160||Supply Chain Analytics||3|
|MSCI:9210||Introduction to Modeling with VBA||2-3|
|ACCT:9170||Advanced Accounting Analytics||3|
|BIOS:5120||Regression Modeling and ANOVA in the Health Sciences||3|
|BIOS:5310||Research Data Management||3|
|CS:3210||Programming Languages and Tools||arr.|
|CS:4470||Health Data Analytics||3|
|CS:5110||Introduction to Informatics||3|
|ECON:5805||Statistics for Economics||3|
|EPID:5200||Principles of Public Health Informatics||3|
|GEOG:3520||GIS for Environmental Studies||3|
|GEOG:3540||Introduction to Geographic Visualization||3|
|GEOG:4150||Health and Environment: GIS Applications||3|
|GEOG:4580||Introduction to Geographic Databases||3|
|ISE:4172||Big Data Analytics||3|
|ISE:6780||Financial Engineering and Optimization||3|
|ME:4111||Scientific Computing and Machine Learning||3|
|ME:4150||Artificial Intelligence in Engineering||3|
|MKTG:9165||Digital Marketing Analytics||3|
|PHYS:4905||Special Topics in Physics (when topic is scientific computing using Python)||arr.|
|PSQF:6209||Survey Research and Design||3|
|PSQF:6243||Intermediate Statistical Methods||4|
|PSQF:6246||Design of Experiments||4|
|PSQF:6250||Computer Packages for Statistical Analysis||1-3|
|STAT:4100||Mathematical Statistics I||3|
|STAT:4101||Mathematical Statistics II||3|
|STAT:5101||Statistical Inference II||3|
|STAT:5400||Computing in Statistics||3|
|STAT:5810||Research Data Management||3|
|STAT:6560||Applied Time Series Analysis||3|
|STAT:7400||Computer Intensive Statistics||3|
|URP:6200||Analytic Methods I||1-3|
|URP:6225||Applied GIS for Planners||3|
|May include 6 s.h. from these:|
|MBA:8140||Corporate Financial Reporting||2-3|
|MBA:8170||International Economic Environment of the Firm||2-3|
|MGMT:3200||Individuals, Teams, and Organizations||3|
|MGMT:4325||Team and Project Management||3|
|MGMT:9150||Nonprofit Organizational Effectiveness I||3|
|MGMT:9160||Nonprofit Organizational Effectiveness II||3|
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 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.