New master’s program: applied statistics and data science – Nieuwscentrum

Friday, May 05, 2023 Jeff Carlton :
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The Mathematics Department at the University of Texas at Arlington is offering a new master’s degree in applied statistics and data science that will equip students for careers in a fast-growing field.

The Master of Science in Applied Statistics and Data Science (MS in ASDS) program starts in fall 2023 and can be completed in three semesters (18 months). It is designed for students from a wide variety of backgrounds, including degrees in STEM and non-technical fields such as business.

“This new degree program will be a great asset to students seeking to enter the fast-growing field of data science, and it will give them additional versatility by providing them with a solid foundation in applied statistics,” said College of Science dean Morteza Khaledi. . “Just as we did with our data science bachelor’s degree, we help lead the way in educating the next generation workforce, who will need a high percentage of data science proficiency.”

Numerous studies show that the number of jobs requiring data science skills is increasing at a much faster rate than in almost any other field. This is due to the huge amounts of data generated by companies and organizations and the need for skilled workers to analyze and interpret it. The U.S. Bureau of Labor Statistics predicts that jobs for statisticians and data scientists will grow 36% by 2031.

“The ability to receive advanced training in statistics helps differentiate the MS in ASDS program from other data science master’s degrees,” said Shan Sun-Mitchell, a statistics professor. “Our program will train students in statistical methodologies, data science, big data analytics, and machine learning to prepare job-ready students for statistics and data science positions across multiple disciplines and industries. The program is project-based and is designed to help students learn how to interpret and analyze data, with a minimum requirement of mathematical and statistical knowledge and programming languages.

The MS in ASDS curriculum is designed to provide hands-on experience through classroom learning and a summer internship or capstone research project. Students increase their knowledge of statistical research, machine learning and big data analysis and master different programming languages ​​at an appropriate level for data analysis.

“Integrating data science and statistics gives students a broader range of skills, giving them a competitive advantage over graduates from programs that focus exclusively on one or the other,” said Li Wang, associate professor of mathematics and computer science and engineering. .

The idea for the program was conceived by Minerva Cordero, UTA interim vice-provost for faculty affairs and professor of mathematics, and Sun-Mitchell, professor of statistics in the Department of Mathematics. They were joined in their efforts by Keaton Hamm, Pedro Maia, Suvra Pal, Wang, and Dengdeng Yu, all faculty members of the Mathematics Department. Their collaboration led to the development and approval of the degree proposal by the Texas Higher Education Coordinating Board in the summer of 2022. The program will be launched under the joint leadership of Sun-Mitchell, program director, and Sherry Wang, director of the Center for Data Science Research and Education.

The training consists of a total of 30 hours, including six compulsory courses, three electives and one research project as the capstone or a summer internship. It is presented in a cohort style to ensure the most interactions and community building between students and teachers.

“As we approach a new era of big data, graduates with expertise in applied statistics and data science are hotly pursued by the high-tech industry, banks, national defense, marketing and healthcare organizations,” said Jianzhong Su, professor and chair of the Department of Mathematics at the UTA. “This unique program creates an excellent career path for students to achieve a level of competency in applied statistics and data science and lead the next generation of STEM workers.”

Program entry requirements include the following: • Undergraduate preparation equivalent to a baccalaureate degree in natural, natural or social sciences; technology; engineering; math; company; or related fields. • Completion of a linear algebra course. Applicants can gain provisional admission into the program without this, but must complete the course in the summer before the program begins. • At least a 3.0 undergraduate GPA on a 4.0 scale. • Two favorable letters of recommendation from people familiar with the applicant’s academic and/or professional work. • GRE scores are suggested but not required.

The first cohort of MS in ASDS students will take three core courses during the fall semester of 2023: ASDS 5301 – Statistical Theory and Applications, ASDS 5302 – Principles of Data Science, and ASDS 5303 – Statistical and Scientific Computing I.

For more information on the MS in ASDS training, visit https://blog.uta.edu/sun-mitchell/ms-asds/.

– Written by Greg Pederson, College of Science