Data Science Master's Degree Program

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Graduate Program Recruiter

Tim Carter

(414) 288-7139

tim.carter@marquette.edu

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To be eligible for admission to the Graduate School at Marquette University, applicants must meet the following requirements:

• A bachelor's degree in data science, computer science, statistics, information science, mathematics, or related field from a regionally accredited institution or international equivalent must be completed prior to starting graduate school.
• A minimum grade point average (GPA) of 3.00 on a 4.00 scale.
• Basic computational thinking competency as demonstrated by completion of an introductory course (e.g., COSC 1010 Introduction to Software Development or equivalent) or proof of successful completion of a recommended introductory online Python programming course as recommended by the program director. 
• Completion of a foundational statistics course (e.g., MATH 1700 Modern Elementary Statistics PSYC 2001 Psychological Measurements and Statistics: Lecture Only, SOCI 2060 Social Statistics or equivalent) with familiarity in programs such as R, MATLAB, SAS, Stata, etc or proof of successful completion of a recommended introductory online foundational statistics course as recommended by the program director.
• Demonstrated English proficiency for non-U.S. citizens.

Application Requirements

Read all application instructions prior to beginning an application.

• A completed online application form and fee.
• Transcripts:
  • If coursework was completed within the United States, submit copies of all current and previous college/universities except Marquette¹
  • If coursework was completed outside of the United States, a transcript evaluation is required. A copy of a course-by-course evaluation is approved for the application process.²
• Statement of purpose essay outlining relevant work experience or education, career goals, possible areas of interest and reasons for seeking admission to this program.
• For international applicants who have not attended an English-speaking university only: TOEFL score or other acceptable proof of English proficiency.
• GRE (recommended for domestic applicants, required for international applicants)
• Resume (recommended)
• Three letters of recommendation (recommended)

^{1Upon admission, final official transcripts from all previously attended colleges/universities, with certified English translations if original language is not English, must be submitted to the Graduate School within the first five weeks of the term of admission or a hold preventing registration for future terms will be placed on the student’s record.} 

^{2Upon admission, an official course-by-course transcript/academic record evaluation must be submitted to the Graduate School within the first five weeks of the term of admission or a hold preventing registration for future terms will be placed on the student’s record.} 

January 15: For priority consideration. After the priority consideration, applications are reviewed on a rolling basis and should be submitted any time before the folliwng dates:

• Fall term admissions- August 1 (June 1 for international applicants)
• Spring term admissions- December 15 (October 1 for international applicants)

Applicants who wish to be considered for merit-based financial aid (graduate assistantships/scholarships) should be aware of the merit-based financial aid deadlines by which all applicant materials must be received by the Graduate School:

• Fall term: February 15
• Spring term: November 15

Students completing this certificate program will be able to:

• Represent, manipulate, analyze and interpret big data using exploratory, inferential methods and use packages/tools in effective ways.

• Recognize and analyze ethical and social issues in data science.

• Apply and evaluate complex models to devise solutions for data science tasks.

• Interpret data science analysis outcomes and draw conclusions using effective written, graphical and verbal tools and techniques.

Data science courses led by respected faculty

Expect excellence from the program, led by respected faculty members including:

• Praveen Madiraju – Director
• Michael Zimmer – Co-director

The MS in Data Science offers specializations in Machine Learning and Big Data, with the choice to complete the degree with the following plan options.

No Specialization (Generalist) 

Specialization in Machine Learning 

Specialization in Big Data 

Specialization in Statistics and Modeling