This program is designed to equip students with both practical and theoretical skills to pursue careers in data science, data engineering, and data analytics across various business domains. Taught by esteemed faculty at the Naveen Jindal School of Management, it covers essential tools like SAS, R, Python, Hadoop, Stata, and Tableau, and emphasizes descriptive, prescriptive, and predictive analytics. The curriculum aims to prepare students for the evolving needs of 21st-century businesses, fostering analytical skills and effective communication.
Why this course is highly recommended
The program offers flexibility through its flex, cohort, and online formats, making it suitable for working professionals and those seeking a flexible study schedule. The faculty are industry experts and researchers, and the curriculum is comprehensive, covering cutting-edge technologies and skills. The university's strategic Dallas location provides excellent access to employers and internship opportunities, enhancing career prospects.
Students can choose from a variety of tracks, including Accounting Analytics, Cybersecurity Analytics, Data Engineering, Data Science, Decisions and Operations Analytics, Financial Analytics, Healthcare Analytics, Marketing Analytics, Social Media Analytics, and Enterprise Systems Analytics, allowing for tailored expertise in specific areas of business analytics and AI.
Application fees
0.00L
1st year tuition fees
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Living cost
Applicants should hold a bachelor’s degree or its equivalent from an accredited institution, with a minimum GPA of 3.0. Knowledge of calculus is required, with an option to take relevant foundational courses if needed. International applicants must demonstrate English proficiency through approved test scores such as TOEFL or IELTS.

English language test
Want to learn more about the admission process, eligibility criteria,
and acceptance rates for international students? Visit the The University of Texas at Dallas admission page
for complete details.
Graduates can pursue diverse roles, including data scientist, data engineer, data analyst, business intelligence analyst, risk analyst, fraud analyst, pricing analyst, strategic business analyst, and market analyst, within various industries.