Application for Summer 2016 will be available in September 2015
The M.S. Analytics program starts once each year in July (summer admission). The early application date for admission and scholarship consideration is December 4. The final application date is March 1.
PLEASE NOTE: As you start your application, click here for important instructions and items required by all graduate programs. In addition, read below for instructions specific to the M.S. in Analytics.
International applicants please click here for important instructions.
Bachelor's Degree Background
Applicants who hold a Bachelor’s degree in any field and have fulfilled the M.S. Analytics admission requirements (see below) are considered for admission. Applicants with academic or professional backgrounds in math, computer science, engineering, finance, economics or equivalent skills are encouraged to apply.
Admission Requirements for M.S. Analytics
These course requirements must be completed at an accredited college or university before starting the graduate program:
- Inferential Statistics
- Linear Algebra
- Programming experience (abilities described below) in one or more of the following: Java, Mathematica, Matlab, Python, C++:
- Ability to write structured programs in a high-level language (for example: objects, methods, functions)
- Ability to read/write data from files
- Facility with the three basic control structures (block, conditional, iteration)
- Understanding of variables and data types (int, float, string, boolean)
- Familiarity with basic data structures (list, dictionary, stack, queue)
- Beginning with the 2016-2017 cohort, a social science course will be required as well.
Other courses or experience (recommended but not required for admission):
- Data Structures
- Programming in R
Statement of Purpose
Upload a 1-2 page statement that describes your educational and work experience as it relates to the Analytics Program, and your career goals. You may also use this statement to explain any deficiencies in your academic record (e.g., failing or low grades in quantitative courses such as math, economics, computer science, or engineering; a low GPA in one semester, year or degree program; lack of relevant coursework that is compensated by self-study or work experience, etc.), gaps in educational or employment history, reasons for low quantitative or verbal scores on the GRE or GMAT tests, and any other topics in your background and experience that you would like to address.