Master in Applied Statistics and Data Science

  • Program Overview

  • The Master of Science in Applied Statistics and Data Science (ASDS) in the Division of Data Science is designed for students with a wide range of backgrounds, including degrees in STEM fields, and those with non-technical backgrounds, such as business majors. The program trains students in statistical methodologies, data science, big data analytics, and machine learning to prepare work-ready students for statistics/data science positions in multiple disciplines and industries. 

  • The ASDS curriculum focuses on applied statistics and data science and is designed for hands-on experience through in-class learning and opportunities for research project internships in different settings. Students will increase their knowledge of statistical research, machine learning, and big data analytics and be proficient in various programming languages at a suitable level for data analytics.

  • Coursework

  • The total proposed length to complete the Master of Science in ASDS is 18 months (3 semesters). The program is in a cohort style to guarantee the most interactions and community-building between students and faculty. The requirements for the Master of Science in ASDS are 27 hours of graduate courses from the Department of Mathematics and a 3-hour summer internship or a capstone project course.

  • All students must complete 6 required courses, 3 elective courses, and 1 research capstone project course or a summer internship.

  • Required Courses (6)

  • ASDS 5301 Statistical Theory and Applications  

  • ASDS 5302 Principles of Data Science

  • ASDS 5303 Statistical and Scientific Computing I  

  • ASDS 6301 Advanced Regression Analysis 

  • ASDS 6302 Machine Learning with Applications

  • ASDS 6303 Data Mining with Information Visualization 

  • Elective Courses (3 out of 5)

  • ASDS 5304 Applied Multivariate Statistical Analysis

  • ASDS 5305 Deep Learning and Artificial Neural Networks  

  • ASDS 5306 Applied Time Series Analysis in Data Analytics  

  • ASDS 6304 Optimization and Big Data Analytics

  • ASDS 6305 Statistical and Scientific Computing II 

  • Summer Internship or Research Capstone Project

  • ASDS 6306 Summer Internship or Capstone Research Project 

  • Admission Requirements:

  • See UTA Admissions (note that during the application process, you should choose ASDSMSNT as the major code for this program).

  • Undergraduate preparation equivalent to a baccalaureate degree in natural, physical, or social sciences, technology, engineering, mathematics, business, or related fields

  • At least a 3.0 undergraduate GPA on a 4.0 scale

  • GRE scores are suggested but not required

  • Two favorable letters of recommendation from people familiar with the applicant’s academic work and/or professional work

  • Applicants may gain provisional admittance to the program without a Linear Algebra course but will be required to take one during the summer prior to starting the program.

  • Applicants who do not meet the requirements for admission may be considered after further review. We will consider other factors such as professional experience and prior success in related courses to not disadvantage qualified candidates.

  • Fall and Spring admissions

  • For regular admissions deadlines please go here

  • For further information and application forms, visit the website of the Office of Graduate Studies

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Be A Maverick Scientist

Discover your future in one of the world’s fastest growing disciplines and upgrade your traditional science area of focus with a Data Science Bachelor’s Degree in UT-Arlington’s College of Science through the program’s unique Data Science + Science Area of Focus format.