Does UNT require GRE for data science?

Question

Rohan Dharamchand · Accepted Answer

It sounds interesting! Pursuing your Data Science degree from the UNT will open a new door to explore a new world to technology indeed. 
As a study abroad guide, I've assisted many students in their journey towards studying data science abroad. 
When it comes to the university of north texas ms in ds program, the requirement for GRE scores can vary over time. While GRE scores may have been required in the past, the university might have updated its admissions criteria since then. 
I always advise students to visit UNT's official website or reach out to the admissions office for the most accurate and up-to-date information. If GRE scores are still required, I recommend thorough preparation to ensure you meet the university's expectations and enhance your chances of acceptance.
If you have any other queries regarding pursuing your education abroad , we are here to help you!

Abhiyudaya Chauhan · Answer

For the Master of Science in Data Science program at the University of North Texas (UNT), the Graduate Record Examination (GRE) is not a mandatory requirement. The admission process has been designed to focus more on the applicants' academic background and professional experience in relevant fields rather than standardized test scores. This decision aligns with a broader trend in graduate education to make advanced studies more accessible and to evaluate candidates on a holistic basis. 
The UNT program emphasizes the practical and technical skills necessary for data science and analytics, with coursework that includes statistical analysis, natural language processing, and data mining, among other topics. The program can be completed online or on campus, offering flexibility for working professionals or those who prefer traditional classroom learning. 
Choosing not to require the GRE allows UNT to attract a diverse range of applicants who may not perform well on standardized tests but who have strong academic or professional credentials in relevant areas. This approach can help expand access to education and support the training of skilled professionals in the growing field of data science​