Data Science Master's Degree Program

Tackle today’s high tech data-driven problems 

Data plays an ever-increasing role in today’s society and the increase in volume, velocity and variety of data has driven the demand in employees skilled in data science and analytics. The “2020 Emerging Jobs Report” from LinkedIn include Artificial Intelligence Specialist and Data Scientist in the top three emerging jobs in the U.S.

 

MS Data Science Program Highlights

Program Key Highlights

  • Tackle today’s problems in the ever-growing data-driven world through theory-based and hands-on data analytics courses.
  • Grow your knowledge in both data analytics and computing, and the relationship between them.
  • Choose a specialization or complete the research-based thesis option.

Choose a Data Science Master's Specialization

Choose Your Specialization

Big Data

Develop a deep understanding of complex data sets and how to solve business decisions. 

Machine Learning

Gain the experience that is sought after in nearly every industry by learning to develop repeatable procedures through algorithms used in applications, AI and predictive learning.



 

33

30-33 Program Credits

2

Years to Complete*

online program delivery

Part-Time, Online Options

 

 

 

 

 

*full-time completed in 2 years, part-time completed in 3 years.

In-Demand Data Science Industries and Careers

Data Scientists are in-demand and industries everywhere are seeking advance learners in data science. It is one of the few degrees that has few boundaries to where it can lead you.

  • Communication/Media
  • Construction
  • Finance
  • Government
  • Gaming
  • Healthcare
  • Insurance
  • Manufacturing
  • Retail

Students with an advanced Master's in Data Science degree can seek careers in professions including:

  • Applications Architect
  • Big Data
  • Data Analyst
  • Data Scientist
  • Data Engineer
  • Systems Software
  • Machine Learning Scientist
  • Business Intelligence Analyst
  • Search Marketing Strategist


Take the next step towards your future


  • Contact Us
  • Application Details
  • Learning Outcomes
  • Faculty
  • Course Work 

Request more information now or schedule a visit.

Graduate Program Recruiter

Tim Carter

(414) 288-7139

timothy.carter@marquette.edu


Email the Graduate School

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Application Deadline

This program has rolling admission, which means you may apply any time before the following dates:

  • Fall term admissions – August 1 (June 1 for international applicants and February 15 for financial aid and priority consideration)
  • Spring term admissions – November 15

Your application must be complete and all required documentation must be received in the Graduate School by the above date.


 

Prerequisites for Admission

Applicants should have:   

  • An earned baccalaureate degree in a relevant field such as data science, computer science, statistics, information science, and mathematics with a GPA of at least 3.000. 
  • Basic computational thinking competency as demonstrated by completion of an introductory course (e.g., COSC 1010 Introduction to Software Development or equivalent). Alternatively, proof of successful completion of a recommended introductory online Python programming course as recommended by the program director. 
  • A foundational statistics course (e.g., PSYC 2001 Psychological Measurements and Statistics, SOCI 2060 Social Statistics or equivalent) with familiarity in programs such as R, MATLAB, SAS, Stata, etc. Alternatively, proof of successful completion of an introductory online foundational statistics course as recommended by the program director. 
  • The program accommodates students from a wide variety of disciplines. 

Application Requirements

Read all application instructions prior to beginning an application.

  • A completed online application form and fee.
  • Copies of all college/university transcripts except Marquette*
  • Statement of purpose
  • 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)

*Upon admission, final official transcripts from all previously attended colleges/universities, with certified English translations if original language is not in 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.

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:

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.

Plan A: Thesis Option Completion Requirements

  • Common core in data science- 18 credits
  • Thesis- 6 credits 
  • Approved Electives- 6 credits

Total Credits: 30  

Plan B: Non-Thesis Option Completion Requirements

  • Common core in data science-18 credits
  • Approved Electives- 15 credits

 

Total Credits: 33


COMMON CORE 

COSC 6510 

Business Intelligence 

3 

COSC 6520 

Business Analytics  

3 

COSC 5500 

Visual Analytics 

3 

COSC 5820 

Ethical and Social Implications of Data 

3 

COSC 6570 

Data at Scale 

3 

COSC 5610 

Data Mining 

3

 

No Specialization (Generalist) 

Common Core

 

18

Electives

Graduate courses approved by advisor

15

Total Credit Hours

 

33

 

Specialization in Machine Learning 

Common Core

 

18

COSC 5800

Principles of Database Systems

  3

COSC 5600

Fundamentals of AI

  3

COSC 6330

Advanced Machine Learning

  3

Electives

Graduate courses approved by advisor

  6

Total Credit Hours

 

33

 

Specialization in Big Data 

Common Core

 

18

COSC 5800

Principles of Database Systems

  3

COSC 6060

Parallel and Distributed Systems

  3

COSC 6380

Advanced Database Systems 

  3

Electives

Graduate courses approved by advisor

  6

Total Credit Hours

 

33