Application and registration process

• Declared Bachelor of Science in Data Science (BSDS) students with:
  • a cumulative GPA 3.5 or higher for the last 60 hours completed;
  • 75 or more credit hours completed; and
  • who are registered within the BSDS degree as pursuing one of the focus areas, may apply during their junior year.
• The following courses must be completed with a grade of C or higher or be in progress at the time of application:
  • MATH 1650  - Pre-Calculus
  • MATH 1680  - Elementary Probability and Statistics
  • CSCE 1030  - Computer Science I
  • CSCE 1040  - Computer Science II
• Students apply to the University of North Texas Toulouse Graduate School.
• Students apply to the College of Information, Department of Information Science.
• Students may not take a graduate class until 90 credit hours have been completed, and must complete their BSDS degree within one year of taking their first graduate course within the track in order to have the courses transferred to their graduate plan.

Admission process and standards

To be admitted to the program, students submit the following items as detailed in the College of Information, Department of Information Data Science application portal: https://informationscience.unt.edu/admission-ms-data-science

• Submit an experience write-up;
• resume or CV;
• Data Science application; and
• Two (2) recommendations.

Communication and monitoring

Students are given a copy of this process form by their BSDS advisor to

• clarify all application and admissions requirements;
• notify students that they remain undergraduates until all undergraduate degree requirements and their BSDS degree is posted to their transcript;
• notify students that they are not eligible for most graduate perquisites, including teaching and research assistantships and related health insurance, financial aid, or graduate award programs until their undergraduate degree is posted; and
• notify students that graduate courses successfully completed as a part of the grad track will be transferred officially as pass/fail credits to their graduate transcript, not factoring into the graduate GPA.

Student progress will be monitored through transcript and academic progress reports to the BADS faculty coordinator and the MS Data Science graduate coordinators after each term, provided by the advisor. The cumulative GPA must remain above 3.0, with no course grades below C for the student to be considered to be making satisfactory academic progress in the grad track. A student who fails to meet this standard will be removed from the grad track program.

Course options

Accepted students will complete two graduate courses (6 hours) to complete the focus area in Data Science within the BSDS degree program.  

INFO 5307 - Knowledge Management Tools and Technologies

INFO 5503 - Knowledge Management Processes and Practices

INFO 5707 - Data Modeling for Information Professionals

INFO 5709 - Data Visualization and Communication

INFO 5731 - Computational Methods for Information Systems

INFO 5735 - Usability and User Experience Metrics

INFO 5737 - Information and Cyber-Security

INFO 5810 - Data Analysis and Knowledge Discovery

All remaining courses required for the Data Science, BS  must also be completed.