University of Texas at Dallas

Overview

The Master of Science in Data Science and Statistics at the University of Texas at Dallas equips students with the ability to apply statistical reasoning and contemporary machine learning techniques to solve complex data challenges. This program develops expertise in analytics, predictive modeling, and research methodologies, offering a flexible curriculum that can be completed through either a thesis or a non-thesis option.

What You'll Study

Program Structure: The degree requires the completion of 12 courses, each worth three semester credit hours, totaling 36 semester credit hours. Students can opt for a thesis plan or a non-thesis plan.

• Thesis Plan: This option involves completing a thesis that replaces two elective courses, accounting for 6 semester credit hours. The thesis is supervised by a faculty member and must be defended according to departmental standards.
• Non-Thesis Plan: Students can fulfill the credit requirements through required coursework and electives without completing a thesis.

Coursework Examples

• Statistical Inference
• Advanced Statistical Methods
• Linear Statistical Models
• Statistical and Machine Learning

Note: The courses listed are examples; your final coursework will include additional required and elective classes to meet the total credit requirement.

Entry Requirements

To be eligible for admission, applicants must maintain a minimum GPA of 3.0 in their prior academic work. Non-native English speakers are required to demonstrate English proficiency through an accepted test.

Career Prospects

Graduates of the Master of Science in Data Science and Statistics can pursue a range of career opportunities in various sectors, including technology, finance, healthcare, and research. Potential roles include data scientist, statistician, data analyst, and machine learning engineer, among others. This program prepares students to contribute effectively to data-driven decision-making in organizations.