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
- 30 credit hours of approved graduate work
- Capstone Experience: DATA-793 Data Science Practicum (3)
Course Requirements
Required (12 credit hours)
- DATA-612 Statistical Programming in R (3)
- DATA-613 Data Science (3)
- STAT-615 Regression (3)
- STAT-627 Statistical Machine Learning (3)
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).
- GOVT-653 Introduction to Quantitative Methods in Political Science (3)
- 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:
- GOVT-520 Campaign Management Institute (4)
- GOVT-618 Bayesian Statistics (3)
- GOVT-620 Applied Politics and American Public Policy (3)
- GOVT-641 The Politics of Mass Communication (3)
- GOVT-670 Introduction to Applied Political Data Science (3)
- PUAD-672 Advanced Quantitative Methods for Policy Analysis (3)
- STAT-522 Time-Series Analysis (3)
- STAT-605 Introduction to Survey Sampling (3)
- STAT-616 Generalized Linear Models (3)
Business Analytics
Required (6 credit hours)
Elective (3 credit hours)
Complete 3 credit hours from the following:
Business Analytics (Online)
Required (6 credit hours)
Elective (3 credit hours)
Complete 3 credit hours from the following:
Computer Science
Required (3 credit hours)
Electives (6 credit hours)
Complete 6 credit hours from the following, or other graduate courses approved by advisor:
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).
- CSC-646 Introduction to Computer Networks (3)
- CSC-647 Introduction to Cybersecurity (3)
- CSC-648 Network Security (3)
- CSC-649 Secure Software Development (3)
- CSC-681 Machine Learning for Cybersecurity (3)
- ITEC-666 Cybersecurity Risk Management (3)
- ITEC-667 Cybersecurity Governance (3)
- JLC-683 Cyber Threats and Security (3)
- MATH-616 Cryptography (3)
- MATH-631 Information Theory (3)
- SIS-653 Topics in U.S. Foreign Policy (3)
Environmental Science
Complete 9 credit hours from the following:
- ENVS-655 Environmental Geographic Information Systems (3)
- ENVS-660 Climatology (3)
- ENVS-685 Remote Sensing: Environmental Measurement from Satellites and Drones (3)
- STAT-628 Spatial Data Analysis (3)
Finance
Required (6 credit hours)
Elective (3 credit hours)
Complete 3 credits from the following:
International Economic Relations
Required (6 credit hours)
Elective (3 credit hours)
Complete 3 credits from the following:
Investigative Journalism
Required (3 credit hours)
Selection (3 credit hours)
Complete 3 credits from the following:
Elective (3 credit hours)
Complete 3 credits from the following:
Microeconomic Analysis
Required (3 credit hours)
Electives (6 credit hours)
Complete 6 credit hours from the following:
- ECON-547 Economics of Antitrust and Regulation (3)
- ECON-624 Applied Econometrics II (3)
- ECON-633 Financial Economics (3)
- ECON-639 Policy Issues in Financial Economics (3)
- ECON-642 Public Economics (3)
- ECON-646 Industrial Economics (3)
- ECON-650 Growing Artificial Societies (3)
- ECON-662 Development Microeconomics (3)
- ECON-665 Economic Experiments and Impact Evaluation (3)
- ECON-671 International Economics: Trade (3)
- ECON-673 Labor Economics (3)
- ECON-674 Gender Economics I (3)
- ECON-676 Applied Microeconometrics for Labor and Development (3)
- ECON-679 Introduction to Environmental Economics (3)
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).
- CSC-660 Tools of Scientific Computing (3)
- CSC-668 Artificial Intelligence (3)
- CSC-676 Computer Vision (3)
- CSC-680 Introduction to Data Mining (3)
- CSC-681 Machine Learning for Cybersecurity (3)
- DATA-641 Applied Natural Language Processing (3)
- DATA-642 Advanced Machine Learning (3)
- DATA-645 Neural Networks and Deep Learning (3)
- GOVT-618 Bayesian Statistics (3)
- ITEC-600 Programming Tools for Analytics: Python (3)
- SPA-620 Institute for Data Science and Big Data (4)
- STAT-520 Applied Multivariate Analysis (3)
- STAT-605 Introduction to Survey Sampling (3)
- STAT-616 Generalized Linear Models (3)
Specialized Methods in Data Science (Online)
Complete 9 credits from the following: