Applied Statistics and Data Science (MS)
Overview
Graduates of the Master of Science (MS) in Applied Statistics and Data Science will be trained in the data science process, machine learning, data visualization, statistical inference, algorithmic and computational thinking, experimental design, coding, ethics, and algorithmic accountability. Moreover, they will acquire competency in the following areas.
- Computational and statistical thinking.
- Mathematical foundations.
- Algorithms and software foundation.
- Data curation.
- Knowledge transference—communication and responsibility.
Admission Requirements:
To be admitted to the graduate program in mathematics, prospective candidates must first meet all requirements for graduate admission to UT Rio Grande Valley, as well as the other requirements listed below:
- Bachelor’s degree in any field with a minimum of 12 hours of upper-division mathematics or statistics course work.
- Undergraduate GPA of at least 3.0 in upper-level Mathematics and/or Statistics courses.
- Official transcripts from each institution attended (must be submitted directly to UTRGV).
- Letter of Intent detailing professional goals and reasons for pursuing the graduate degree.
Application for admission must be submitted prior to the published deadline. The application is available at www.utrgv.edu/gradapply.
Program Requirements
Required Courses (21 Credits)
Prescribed Electives (9 Credits)
This degree plan includes courses that appear in more than one section of the degree plan. Such courses can only be used to fulfill one requirement in the degree plan, and credit hours will only be applied once.
Computer Science Courses (Choose one)
Statistics Courses (Choose one)
Mathematics Courses (Choose one)
Capstone Requirement
Choose one of the following options:
Thesis Option (6 Credits)
Master Project Option (6 Credits)
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Non-Thesis Option (Comprehensive Exam) (6 Credits)
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Total Credit Hours: 36