Accelerated 3+2 Mathematics Minor with MS in Data Science

Program (3+2) for B.S./B.A. students with Mathematics Minor and M.S. in Data Science. The accelerated curriculum can be completed in five years to obtain the M.S. in Data Science degree within one additional year after completing the B.S./B.A. and the Mathematics Minor programs. The M.S. in Data science graduate courses are offered online only. The students take one graduate course during the summer preceding the senior year and two additional graduate courses during the senior year. Subsequently, the students complete the requirements for the M.S. in Data Science within one year. The accelerated program applies 9-12 graduate credits for undergraduate courses.

Requirements for Program Admission and Continuation:

• Submit an application for the M.S. in Data Science program during the Spring semester of Junior Year,
• Meet the M.S. in Data Science admission requirements, except having completed the undergraduate degree program, with undergraduate GPA of at least 2.75,
• Have Senior status (earned at least 90 credits) before taking graduate courses,
• Have at least a 3.0 GPA in the undergraduate Mathematics Minor program before taking graduate courses from the Data Science curriculum,
• Before taking graduate courses during the fifth year, fulfill all the requirements for admission to the M.S. in Data Science, including having earned the undergraduate degree.

Accelerated Curriculum

By the end of Spring of Junior Year:

• Take MATH 2711 Intro Probability - Statistics as the first elective course of the Mathematics Minor.
• Complete the courses of the Mathematics Minor, except the second elective course.

Summer between the Junior and Senior Years:

• Take the graduate course MATH 6611 Operations Research that shall count as the second required elective courses for the Mathematics Minor.

Senior Year:

• Take  DASC 6010 Data Mining and DASC 7111 Text Mining. DASC 6010 Data Mining and DASC 7111 Text Mining replace the undergraduate courses DASC 3010 Data Mining and DASC 3111 Text Mining. Optionally, students may additionally take DASC 7000 Data Visualization which replaces the undergraduate course DASC 3000 Data Visualization.

Graduate Year:

• Fall Semester: Take MATH 6811 Statistics for Data Science and DASC 7000 Data Visualization (if not yet taken).
• Spring Semester: Take DASC 6911 Big Data Analytics and two elective graduate courses from the M.S. in Data Science curriculum.
• Summer Session: Take DASC 9311 Data Science Project and one elective graduate course from the M.S. in Data Science curriculum.