Considering a career in one of technology’s most in-demand fields? The College of Engineering’s new Master of Science in Data Engineering may be for you. According to the Dice 2020 Tech Job Report, jobs in data engineering are growing by 50% each year, making data engineering the fastest-growing job in technology.
The Master of Science program in Data Engineering allows you to focus on your analytical, programming and engineering skills to:
UNT’s degree is interdisciplinary, allowing you to leverage your existing skill set and experience by combining it with skills in data engineering. As a graduate student in our program, you will have the opportunity to focus your entire degree on data engineering or specialize in biomedical engineering.
The College of Engineering has state-of-the-art instructional facilities and laboratories containing cutting-edge research equipment. Top-ranked research labs offer exciting possibilities for study and discovery. Alongside faculty members, you’ll explore areas such as:
Our program is open to students from STEM disciplines including engineering, computer science, math and other science-related backgrounds. Your transcript will be reviewed to determine if your background is suitable for admission into the concentration of your choice and/or if leveling coursework is required.
You can expect to take:
Core courses will provide you with a solid foundation in data engineering and will dive into topics such as:
Degree concentration areas focus on data engineering and biomedical engineering.
Teaching and research assistantships are available to help you pursue your graduate degree. These assistantships provide you with a monthly stipend and may qualify you for in-state tuition rates or tuition and fee support. You also can apply for UNT scholarships, as well as departmental scholarships within the College of Engineering. The general scholarship deadline is March 1 of each year. Apply and learn more.
Mark Albert, Assistant Professor; Ph.D., Cornell University. Machine learning and biomedical engineering.
Xuan Guo, Assistant Professor; Ph.D., Georgia State University. Data mining, machine learning, big data analysis and data fusion.
Yan Huang, Professor; Ph.D., University of Minnesota. Spatio-temporal databases and mining, geo-stream data processing, smart transportation and location-based social networks.
Rodney Nielsen, Associate Professor; Ph.D., University of Colorado at Boulder. Natural language processing, machine learning and cognitive science.