How to Apply: Accelerated BS/MPS in Data Science

Application Deadline(s)

Fall 2024: August 1, 2024
Spring 2025: December 1 , 2024

UMBC undergraduate students have the option of applying to the accelerated Data Science Bachelor’s/MPS program in their junior or senior year and may take up to nine graduate credits that can be applied to both their undergraduate and graduate degrees. Students benefit by shortening the time to degree completion, experience the cost savings of taking graduate courses at undergraduate tuition rates, experience flexible learning options (some courses taught in evening or in hybrid format) and gain practical knowledge and skills.

At a Glance

Locations Offered

  • UMBC Campus (Catonsville)
  • Shady Grove (Rockville)


Admissions Requirements for CMSC students

  • Minimum undergraduate GPA of 3.0
  • Maintain good academic standing throughout the duration of undergraduate degree
  • Students are required to complete CMSC 331, CMSC 341, and STAT 355.*

*Note that the three courses mentioned above have certain prerequisites. Students are suggested to take MATH 151, MATH 152, MATH 221, CMSC 201, CMSC 202, and CMSC 203 in their first and second years if they are interested in this accelerated Bachelor/MPS degree focusing on Data Science.

Admissions Requirements for non-CMSC students

  • Minimum undergraduate GPA of 3.0
  • Maintain good academic standing throughout the duration of undergraduate degree
  • Students are required to complete the following courses before applying:
    • Statistics (STAT 351 or STAT 355 or equivalent)
    • Linear Algebra (MATH 221 or equivalent)
    • Programming (CMSC 201 or IS 147 or equivalent)

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Application Process

Part 1

  • Student completes the Graduate School Accelerated Bachelor’s/Master’s Application DocuSign Form attaching a brief statement of why they are interested in participating in this accelerated bachelor’s/master’s program with a copy of their undergraduate transcripts.
  • If the Undergraduate Advisor approves, the DocuSign application will be forwarded to the Data Science Graduate Program Director. (Reference letters are not required.)
  • Once approved, student completes the Approval for Undergraduates to take Courses for Graduate Credit and starts taking data science courses in the Fall semester of their fourth year.   

Part Two

  • One semester prior to completion of your bachelor’s degree, student submits an application for the MPS: Data Science program to the Graduate School. This process is perfunctory but mandatory. Student does not pay the application fee.
  • Once admitted to the MPS Data Science program, student completes Transfer of Credits Form to Graduate School for nine credits.

How it Works

  • Students are required to take 10 courses (30 credits) in order to get their MPS degree. Nine of these 30 credits will be double-counted towards their undergraduate degree.
  • Students are advised to spread these 10 courses into four more semesters. For example
Fall of 4th yearSpring of 4th yearFall of 5th yearSpring of 5th year
DATA 601
+
BS/BA courses
DATA 602
DATA 607
+
BS/BA courses
DATA 603
DATA 604
DATA 605
Pathway Course-1
DATA 606
Pathway Course-2
Pathway Course-3

Accelerated Bachelor/MPS Program Regulations and Procedures

Once admitted to the combined program, the student must maintain a 3.0 or higher grade point average. No more than two “C” grades may be received in all courses taken after admission. If the GPA falls below 3.0 or if more than two “C” grades are received, the student will be removed from the combined program. This does not affect the student’s eligibility for the bachelor degree under normal University undergraduate requirements. Any one “D” or “F” also results in removal from the combined program.

Students in the combined program must formally apply for admission to the Graduate School before the application deadline during the semester in which the course work for the bachelor degree is completed. No more than 9 credits of graduate courses may be taken while the student is paying undergraduate tuition.

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