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.
Program Key Highlights
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.
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
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Contact Us
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Application Details
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Learning Outcomes
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Faculty
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Course Work
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:
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Represent, manipulate, analyze and interpret big data using exploratory, inferential methods and use packages/tools in effective ways.
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Recognize and analyze ethical and social issues in data science.
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Apply and evaluate complex models to devise solutions for data science tasks.
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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
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COSC 6510
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Business Intelligence
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3
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COSC 6520
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Business Analytics
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3
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COSC 5500
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Visual Analytics
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3
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COSC 5820
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Ethical and Social Implications of Data
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3
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COSC 6570
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Data at Scale
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3
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COSC 5610
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Data Mining
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3
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No Specialization (Generalist)
Common Core
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18
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Electives
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Graduate courses approved by advisor
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15
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Total Credit Hours
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33
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Specialization in Machine Learning
Common Core
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18
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COSC 5800
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Principles of Database Systems
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3
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COSC 5600
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Fundamentals of AI
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3
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COSC 6330
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Advanced Machine Learning
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3
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Electives
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Graduate courses approved by advisor
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6
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Total Credit Hours
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33
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Specialization in Big Data
Common Core
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18
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COSC 5800
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Principles of Database Systems
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3
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COSC 6060
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Parallel and Distributed Systems
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3
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COSC 6380
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Advanced Database Systems
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3
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Electives
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Graduate courses approved by advisor
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6
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Total Credit Hours
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33
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