University of Maryland Launches Science Academy with Professional STEM Programs

Enrollment open for data science and machine learning professional master’s and graduate certificate programs

The University of Maryland’s College of Computer, Mathematical, and Natural Sciences (CMNS) has launched the Science Academy to provide graduate education programs for working professionals who want to advance their knowledge and skills in key areas like data science and machine learning.

With courses taught by UMD faculty members who are leading experts in their fields, the Science Academy is designed to meet a regional demand for a modern workforce with expertise in specialized areas of science and mathematics.

“Working professionals in nearly every field need data-related skills to stay current and advance in their careers,” said CMNS Dean Amitabh Varshney. “Science Academy programs cater to a workforce that recognizes the need for the knowledge and expertise that are required to compete in the 21st-century global economy.”

The Science Academy will be led by Director Amy Chester, who joins UMD next month from Georgetown University’s School of Continuing Studies where she is senior assistant dean.

“We are excited to welcome Amy back to the University of Maryland, where she earned both undergraduate and graduate degrees,” Varshney said. “Amy brings with her a wealth of experience and knowledge in higher education and professional training. In her new role, Amy will be instrumental in growing our portfolio of Science Academy programs to meet the needs of working professionals and lifelong learners.”

Science Academy programs currently include: 

• Data Science - Master of Professional Studies (30 credits) or Graduate Certificate (12 credits): Students learn to design, conduct, interpret, and communicate data analysis tasks and studies using methods and tools of statistics, machine learning, computer science, and communications.

• Machine Learning - Master of Professional Studies (30 credits): Students master the methods and techniques of creating models and algorithms that learn from and make decisions or predictions based on data. They also explore advanced topics such as deep learning, optimization, big data analysis, and signal/image understanding.

All courses take place in the evenings on UMD’s campus in College Park, a regional hub for innovation and technology. With the university’s computer science, mathematics and engineering programs consistently ranked in the Top 25 by U.S. News & World Report, Science Academy courses are taught by high-quality faculty who are committed to teaching excellence.

Courses are taught on a 12-week term schedule, which means students can complete a Master of Professional Studies degree in as little as 15 months or a Graduate Certificate in six months, while also working.

Domestic students can apply immediately to enroll in any of the Science Academy programs and should apply by October 1, 2019, for best consideration. Courses will begin in late November. International students should apply by March 13, 2020 to begin taking courses in August 2020.

Science Academy programs are led by faculty members in CMNS and the A. James Clark School of Engineering. 

Michael Cummings, UMD professor of biology with a joint appointment in the University of Maryland Institute for Advanced Computer Studies (UMIACS), serves as director of the Data Science and Analytics Master of Professional Studies Program. Cummings, whose research focuses on molecular evolutionary genetics, also serves as director of the Center for Bioinformatics and Computational Biology in UMIACS.

Hector Corrada Bravo, UMD associate professor of computer science with a joint appointment in UMIACS, and Amol Deshpande, UMD professor of computer science with a joint appointment in UMIACS, serve as co-directors of the Data Science Graduate Certificate Program. In addition to teaching, Corrada Bravo and Deshpande conduct cutting-edge research in computational biology and database systems, respectively.

David Jacobs, UMD professor of computer science with a joint appointment in UMIACS, and Sennur Ulukus, Anthony Ephremides Professor in Information Sciences and Systems in the Department of Electrical and Computer Engineering at UMD, serve as co-directors of the Machine Learning Master of Professional Studies Program. Ulukus’ research focuses on information theory and wireless communications. Jacobs, an expert in computer vision, also serves as director of the Center for Machine Learning in UMIACS. 

“This is just the beginning for the Science Academy,” Varshney added. “Our long-term goal is to broadly expand access to the University of Maryland’s knowledge and expertise in the sciences. These programs in data science and machine learning are the perfect way for us to begin addressing the learning needs of the workforce in the federal government and in industries that span from medicine and weather to telecommunications and cybersecurity.”