PRAIRIE VIEW, Texas (Aug. 28, 2026) – Prairie View A&M University is the first Historically Black College or University (HBCU) in Texas to offer a Master of Science in Data Science and Engineering (MSDSE), launching its inaugural cohort this fall.
Housed in the Roy G. Perry College of Engineering’s Department of Electrical & Computer Engineering, the new program is bringing artificial intelligence (AI) and data science literacy to a broader audience, with a focus on students in science, technology, engineering, and mathematics (STEM) fields.
The flexible 30-credit-hour program will prepare graduates and working professionals in valuable AI, machine learning, data analytics, and data engineering skills that today’s employers are actively seeking.
“The launch of the Master of Science in Data Science and Engineering reflects where engineering education must go next,” said Dr. Pamela H. Obiomon, dean of the Roy G. Perry College of Engineering. “AI, data science, and engineering are connected across every major industry. This program gives our students and working professionals the technical skills, research experiences, and practical preparation needed to lead in an AI driven, data centered economy.”
The new program marks the culmination of years of work by Dr. Lijun Qian, AT&T endowed professor of electrical and computer engineering, and founding director of the University’s Center of Excellence in Research and Education for Big Military Data Intelligence (CREDIT Center), under the leadership of Dr. Obiomon, and with support from Academic Affairs.
Lijun Qian, Ph.D.
For Dr. Qian, the timing is no accident.
“The convergence of increased computing power, big data analytics, and breakthroughs in AI will transform our lives in the future,” he said.
Multiple recent surveys, along with steady feedback from alumni and industry partners, point to strong demand in the U.S. job market for data scientists and data engineers, Qian said.
“It is well recognized that all science and engineering students should have some core competence in data science to be successful in the future AI-enabled, data-centric economy, and skills in analyzing and interpreting data can give young people access to new career opportunities,” he said.
Qian also cited McKinsey & Company data indicating that an estimated 78% to 88% of organizations report regular use of AI for data analysis in at least one business function, underscoring the growing role of AI and data science across industries.
What distinguishes PVAMU’s MSDSE is its focus on AI-enabled data analysis, building on the University’s research capabilities in AI and data science, with work sponsored by multiple government agencies and industrial partners, according to Dr. Qian.
Students will receive face-to-face instruction paired with hands-on projects tailored to their individual backgrounds and career goals. They will also have various opportunities to perform research and develop practical skills, such as developing an intelligent monitoring, analysis, and visualization platform for electrical power systems, and implementing an agentic AI system for robot control. Additional opportunities for research, internships, and industry partnerships are also part of the program’s design.
Admission requirements include a bachelor’s degree in engineering, computer science, mathematics, or a related field with a minimum GPA of 2.75.
Graduates will be prepared to pursue a range of modern industries, Dr. Qian said, as organizations increasingly adopt AI tools for data analysis and decision-making.
Obiomon said the program also builds on the expertise and research already underway within the College.
“I am proud that Prairie View A&M University is expanding access to this growing field while building on the outstanding AI and data science research strength already present in our College of Engineering,” she said.
As the inaugural cohort begins classes this fall, the MSDSE program positions PVAMU to expand access to advanced education in a rapidly evolving field while preparing its productive Panthers to contribute to an increasingly data-driven economy.
By Christine Won
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