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Master of Science in Data Science
Master of Science in Data Science
Master of Science in Data Science
The University of Guam M.S. in Data Science program is a comprehensive and cohort-based study requiring 30 credit hours. Delivered in a face-to-face format, the curriculum places a strong emphasis on the practical applications of statistical methodology, computational science, and diverse domains. It includes a range of topics, including statistical modeling, machine learning, optimization, data management, analysis of large datasets, and data acquisition.
Throughout the program, students will explore reproducible data analysis, collaborative problem-solving, and honing visualization and communication skills. Also, the curriculum addresses ethical and security issues intrinsic to data science. Students will have developed expertise in applying data science techniques to solve real-world problems across various domains.
Program Objectives
Master of Science in Data Science program objectives are:
- To establish the first regional graduate program in Data Science that provides affordable education options to local students. The program will offer lower resident tuition rates and access to financial aid and support programs compared to similar off-island programs. Additionally, the program will leverage existing UOG grants such as U54, EPSCOR, and NASA to support students.
- To equip students with the necessary skills to work as data analysts in both academic and industry settings. Graduates can contribute to existing research initiatives at UOG, further enhancing research capabilities at the university.
Program Learning Outcomes
Students completing the Master of Science in Data Science Program at UOG will be able to:
- Design and execute statistical experiments and hypothesis tests to extract meaningful insights from data.
- Analyze and interpret complex statistical data using advanced statistical methodologies and tools.
- Visualize data for exploration, analysis, and communication.
- Develop and implement predictive models and machine learning algorithms to make data-driven decisions.
- Communicate statistical analyses, findings, and recommendations to both technical and non-technical audiences effectively.
- Collaborate with interdisciplinary teams to design, implement, and evaluate statistical projects.
For more information, email:
datascience@triton.uog.edu
Application Requirements
Applicants must have the following minimum qualifications, to be eligible to apply to the program:
- Earned baccalaureate degree in mathematics, computer science, biology, chemistry, statistics, psychology, or public health from an accredited college or university.
- Graduate admission application and application fee
- Official transcripts of all coursework completed.
- At least two letters of recommendation
- Current resume
- Minimum cumulative undergraduate grade point average of 3.0.
In addition, undergraduate students must complete the following prerequisites or equivalent before entering the program:
- Multivariate Calculus, MA-205
- Linear Algebra, MA-341
- Statistics course, MA-387+MA-387L, or BI-412+BI-412L
Or Bridge Course (no credit toward degree)
The bridge course will cover calculus, linear algebra and statistics topics necessary for data science courses. The Bridge Course will take place during the UOG summer Session C, preceding the program's start.
Calculus topics and learning outcomes:
- Vector calculus and multivariate integration
- Partial derivatives and gradient descent
- Analytically optimize different types of functions commonly used in machine learning using properties of derivatives and gradients
Linear algebra learning outcomes:
- Represent data as vectors and matrices and identify their properties using concepts of singularity, rank, and linear independence
- Apply common vector and matrix algebra operations like dot product, inverse, and determinants
- Express certain types of matrix operations as linear transformation and apply concepts of eigenvalues and eigenvectors to simple machine learning problems
Statistics topics:
- Calculate the descriptive statistics
- Understand the properties of commonly used probability distributions in machine learning and data science
- Conduct various statistical tests including a T test, an ANOVA, and regression analysis
- Interpret the results of your statistical analysis after conducting hypothesis testing.
Class times and format:
All Data Science classes take place on campus in a face-to-face format, with the exception of MA-500 and MA-505, which are eight-week online courses. All required math courses will be held at 4 p.m. Elective courses may take place in the morning or other times of day.
M.S. in Data Science Degree Requirements (30 credit hours)
Required Courses (17-20 credit hours)
MA-541 REGRESSION MODELS AND APPLICATIONS (4 credit hours)
MA-551 INTRODUCTION TO PROBABILITY THEORY (3 credit hours)
MA-552 INTRODUCTION TO MATHEMATICAL STATISTICS (3 credit hours)
MA-564 MULTIVARIATE ANALYSIS (3 credit hours)
MA-571 STATISTICAL RESEARCH AND CONSULTING (1-3 credit hours)
MA-581 MACHINE LEARNING FOR DATA SCIENCE (3 credit hours)
Elective Courses (10-13 credit hours)
AL-505 NUTRITIONAL EPIDEMIOLOGY (3 credit hours)
EV-558 ADVANCED GEOSPATIAL METHODS (4 credit hours)
MA-453 OPERATIONS RESEARCH (3 credit hours)
BA-622 MULTIVARIATE ANALYSIS (3 credit hours)
CS-420 COMPUTER AND NETWORK SECURITY (3 credit hours)
MA-505 INTRODUCTION TO SAS (1 credit hour)
MA-500 INTRODUCTION TO R (1 credit hour)
AL-594 CANCER HEALTH DISPARITIES (3 credit hours)
The master's program offers flexibility by not requiring a thesis. Instead, students can pursue alternative capstone projects or practical experiences aligned with their interests and goals.
Sample Schedule for Covering Requirements
Below is a sample schedule of the program across four semesters (two years), offering flexibility in personalizing your educational journey:
| Fall 2024 | Spring 2025 | Fall 2025 | Spring 2026 |
|
MA-551 (3 credits) MA-541 (4 credits) MA-500 (1 credit) MA-505 (1 credit) |
MA-552 (3 credits) MA-564 (3 credits) Elective (3 credits) |
MA-581 (3 credits) MA-571 (2 credits) Elective (3 credits) |
MA-571 (1 credit) Elective (3 credits) |
| Total credits: 9 | Total credits: 9 | Total credits: 8 | Total credits: 4 |
Program Chair
Associate Professor of Mathematics
Office Hours: Mon/Wed: 11am-1pm 
Office Location: Science Building, Room 201
CREDENTIALS
- B.S., Mathematics, Wayne State University (Mich.)
- M.A., Statistics, Wayne State University (Mich.)
- Ph.D., Mathematics, Wayne State University (Mich.)
Faculty
Associate Professor of Mathematics
Office Location: Warehouse Annex B, Room 10CREDENTIALS
- B.A., Mathematics, University of Guam
- M.S., Mathematics, Rensselaer Polytechnic Institute (N.Y.)
- Ph.D., Mathematics, Rensselaer Polytechnic Institute (N.Y.)
Assistant Professor of Mathematics / I Meyeng UOG-Certified Online Teacher
Office Location: ALS 203Expertise
CREDENTIALS
- B.A., Mathematics, Korea University
- M.S., Mathematics, University at Albany, State University of New York
- Ph.D., Mathematics, University at Albany, State University of New York
- I Meyeng UOG-Certified Online Teacher
Professor of Mathematics
Office Location: ALS 316Expertise
CREDENTIALS
- B.S., Mathematics, Sungkyunkwan University (South Korea)
- M.S., Mathematics, University of Arizona
- Ph.D., Mathematics, New Mexico State University
Interim Associate Director of Research / Professor of Biology
Office Location: ALS 206BCREDENTIALS
- Ph.D., Biology, The University of Alabama at Birmingham
- M.S., Biology, University of Guam
- B.A., Biology, University of Guam
Director of Water and Environmental Research Institute (WERI) of the Western Pacific
Office Location: WERI 111CREDENTIALS
- B.S., Surveying, Shandong University of Science and Technology (China)
- M.S., Engineering Surveying, Southwest Jiaotong University (China)
- Ph.D., Environmental Sciences, University of Rhode Island
Associate Professor of Bioinformatics
Office Location: ML 106RESEARCH INTERESTS
Patterns and processes of marine biodiversity evolution. Cnidariologist by training and heart; most of my work focuses on jellyfish, hydroids, corals and their relatives.
APPOINTMENTS
Assistant Professor (Bioinformatics), Marine Laboratory, University of Guam
Research Associate, National Museum of Natural History, Smithsonian Institution
CREDENTIALS
- Diplom (M.S.), Zoology, Ecology, and Hydrobiology, University of Hannover (Germany)
- Ph.D., Ecology and Evolutionary Biology, University of Kansas
ResearchGate
Google Scholar
Dean / Professor of Health Sciences / I Meyeng UOG-Certified Online Teacher
Office Location: SOH 100CREDENTIALS
- B.A., M.S., Biology, University of Guam
- Ph.D., Epidemiology, University of Hawaii at Manoa
- I Meyeng UOG-Certified Online Teacher
Extension Agent IV / Associate Professor of Nutrition
Office Location: ALS 113CCREDENTIALS
- Registered Dietitian Nutritionist
- Ph.D., Nutrition, University of Hawaii at Manoa
- M.S., Nutrition, Eastern Michigan University
- B.S., Food Science and Human Nutrition, University of Hawaii at Manoa
RESEARCH and EXTENSION Interests:
- Childhood obesity prevention and treatment
- Overall health for Guam's people through a Pacific cultural context.
hobbies
Dancing, running, spending time at the beach, spending time with husband and son
Chen Kuan-ju
Office Hours: Office Location: Expertise
Assistant Professor of Management
Office Location: SBPA 232CREDENTIALS
- B.A., Asian American Studies, University of California, Los Angeles
- PMBA, University of Guam
- MAT, University of Guam
- DBA, Management, Argosy University, Hawaii
ABOUT
Dr. James Ji Jr. officially joined the University of Guam in August 2020 but has taught courses at UOG since 2013. He is also a licensed realtor and the general manager of J.J. Pacific Development Corp. He previously served as an advisor to the Public Policy Institute under the speaker of the 35th Guam Legislature.
RESEARch interests
His previous research focused on cultural and generational distinctions regarding commitment levels in management. The primary focus of his research includes new forms of leadership and management with the intention of assisting the public and private sectors on Guam. Other research interests include technology-based education and management, an area that has become more relevant during the COVID-19 pandemic.
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