Application and registration process:

• Declared Applied Arts and Sciences (AA&S) 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 AA&S degree as pursuing the Data Analytics focus area,

• 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 1710 
  • MATH 1720 
  • CSCE 2100
  • IPAC 4130 
  • IPAC 4240 
  • IPAC 4250 
• Students submit the Toulouse Graduate School’s Conditional Admission and Advisor Course Approval Form to the graduate coordinator for the Advanced Data Analytics pathway list above. A signed copy of that form must be submitted to the Applied Arts and Sciences Advisor for official records.
• Students may not take a graduate class until 90 credit hours have been completed, and must complete their B.A.A.S. degree within one year of taking their first graduate course within the track in order to have the courses transferred to their graduate plan.
• Students apply for admission to the Advanced Data Analytics MS program through the Toulouse Graduate School prior to the first semester of their final undergraduate year at UNT.

Admission process and standards:

To be admitted to the program, students submit the following items to the Applied Arts and Sciences Program Director.

• written statement of purpose (500-700 words)
• resume or CV

The student’s current transcript will also be pulled by the advisor to verify GPA and prerequisites.  Grad Track program admission decisions will be made holistically and in collaboration with the graduate program coordinators.  Students will be notified of whether they were selected to be admitted to the grad track program through a letter co-signed by the Applied Arts and Science Program Director and the Advanced Data Analytics graduate coordinator.

Communication and monitoring:

Students are given a copy of this process form by their AA&S advisor to

• clarify all application and admissions requirements,
• notify students that they remain undergraduates until all undergraduate degree requirements and their B.A.A.S. 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 AA&S program director and the Advanced Data Analytics 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.

Required courses, 25 hours

Six undergraduate pre-requisite courses and two graduate courses.

• CSCE 2100 - Foundations of Computing
• IPAC 4130 - Data Analytics and Computational Statistics 1
• IPAC 4240 - Principles of Data Structures, Harvesting and Wrangling
• IPAC 4250 - Principles of Data Visualization for Large Data
• MATH 1710 - Calculus I
• MATH 1720 - Calculus II
• ADTA 5230 - Data Analytics II
• ADTA 5340 - Discovery and Learning with Big Data