Data Science Online MS Curriculum

Our online MS in Data Science program curriculum features 6 core courses,and the opportunity to select from predesigned tracks in Business Analytics or Specialized Methods, along with a range of electives to personalize your executions and meet your career goals. 

All classes prepare students to succeed in their individual tracks and the capstone: DATA-793 Data Science Practicum, where students get hands-on experience working directly with faculty and other researchers on projects.

Data Science Practicum

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Students in the Data Science Practicum (DATA-793) provide project-specific technical, analytic, and research assistance to faculty, government, and business clients.

See also our Data Science Lifecycle video mapping out the stages of data science project development and their relationships with AU course options.

Course Requirements & Degree Tracks

Degree Requirements

Course Requirements


Required (12 credit hours)

Analysis/Statistics (3 credit hours)

Methods (3 credit hours)


Please see below for complete degree and admission requirements, the 10 on-campus degree tracks, and course descriptions for both online and on-campus Data Science MS:
 

Data Science (MS)

Offered jointly by the Department of Government, School of Public Affairs and the Department of Mathematics and Statistics, College of Arts and Sciences, the Data Science (MS) is designed for individuals augmenting or beginning studies in data science. The program prepares students for data analytic positions in academia, government, and industry that require extensive knowledge of statistical and computational tools applied to political, social, and institutional problems. Having trained in the collection, organization, analysis, interpretation, and presentation of data, graduates can process, understand, and explore a wide class of human-generated information to solve complex problems and produce new knowledge.

Admission to the Program

Open to students with a bachelor's degree from an accredited institution. Formal admission to the program requires a cumulative grade point average of 3.00 (on a 4.00 scale) and departmental approval. Prior to enrollment in the program, applicants must have completed one of the following: STAT-202 Basic Statistics  (4) or STAT-203 Basic Statistics with Calculus  (4) or STAT-204 Introduction to Business Statistics  (4). This may be waived for qualified persons with comparable prior education or experience. Students are required to complete a mathematical boot camp prior to starting the program.

Degree Requirements

Course Requirements

Required (12 credit hours)

Analysis/Statistics (3 credit hours)

Complete 3 credit hours from the following:

Note: Students in the online program are required to complete GOVT-650 Political Analysis  (3).

Methods (3 credit hours)

Complete 3 credit hours from the following:

Note: Students in the online program are required to complete STAT-614 Statistical Methods  (3).

Track (9 credit hours)

Complete 9 credit hours from one of the following tracks:

Applied Public Affairs

Complete 9 credit hours from the following if not taken to fulfill Analysis/Statistics, or other graduate courses approved by advisor:

Business Analytics

Business Analytics (Online)

Computer Science

Cybersecurity

Complete 9 credit hours from the following:

Note: Students may receive credit for no more than 3 credit hours from ITEC-666 Cybersecurity Risk Management  (3), ITEC-667 Cybersecurity Governance  (3), JLC-683 Cyber Threats and Security  (3), and SIS-653 Topics in U.S. Foreign Policy  (3).

Environmental Science

Complete 9 credit hours from the following:

Finance

International Economic Relations

Investigative Journalism

Microeconomic Analysis

Required (3 credit hours)
Electives (6 credit hours)

Complete 6 credit hours from the following:

Specialized Methods in Data Science

Complete 9 credit hours from the following if not taken to fulfill Analysis/Statistics, or other graduate courses approved by advisor:

Note: Students may receive credit for no more than 3 credit hours from CSC-668 Artificial Intelligence  (3), CSC-676 Computer Vision  (3), and CSC-680 Introduction to Data Mining  (3).

Specialized Methods in Data Science (Online)

Complete 9 credits from the following:

Capstone (3 credit hours)