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PlusOne Program with MS in Data Science

The PlusOne Accelerated Master’s Program empowers motivated students like you to start earning your master’s degree while pursuing your undergraduate education. In this program, you can complete up to four graduate-level courses and apply them to both your undergraduate and graduate data science degrees. Gain foundational data science knowledge and experience while reducing the time it takes to complete a master’s from two years to one.

Program details

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Program eligibility

Students must be enrolled in the data science major or a data science combined major to be in this pathway. Students in data science combined majors with Khoury College are eligible regardless of their home college affiliation.

Students may complete up to four graduate (master’s) courses as an undergraduate.

  •  Only one graduate course may be completed per semester.
  • The remaining required courses must be completed as a master’s student (post-bachelor’s graduation).

When can you begin?

  • Minimum 3.0 GPA required to request graduate course enrollment.
    • First-year students cannot take their first graduate-level course during the summer. Please plan to take your first graduate-level course in the fall of your second year at the earliest.
       
  • Students can request enrollment in graduate-level courses via a survey that is emailed out before each semester’s registration period.

Admission requirements

Interested students should meet with their advisor no later than their third semester to discuss how the PlusOne pathway will fit into their academic plan and when they plan to complete their first graduate-level course.

Admission requires:

  • Minimum 3.0 GPA, both cumulative and within the major
  • Successful completion of a graduate-level Khoury College course
  • Submission of the online PlusOne Application form:
    • Academic advisors will share the online application form with eligible students
    • Application form should only be submitted after the above requirements are met
    • Admission into the PlusOne program does not guarantee admission into the master’s program upon graduation at the bachelor’s level

Progression requirements

  • To continue in the PlusOne program, students must maintain a minimum 3.0 GPA and earn a cumulative 3.0 GPA in all graduate-level CS courses.
  • Students admitted into the PlusOne program maintain undergraduate standing and must continue to request admission into graduate courses each term.
  • Undergraduates are limited to one graduate course per semester, with a limit of four graduate courses (including withdrawals) total during the undergraduate degree. Placement is not guaranteed.
  • Students should confer regularly with their undergraduate academic advisor to ensure proper planning.
  • Students entering a graduate program via the PlusOne pathway are not eligible for the Double Husky Scholarship. If you have additional questions related to tuition or scholarship eligibility, please reach out to Student Financial Services.

Graduate replacements for undergraduate courses

Students must complete all four listed master’s courses while in their undergraduate program. All four will be applied to both the undergraduate and graduate degree programs. Students who have already taken the undergraduate version of any of the below courses are not eligible for the PlusOne degree in Data Science. Check the course catalog for course descriptions.

Undergraduate Course RequirementGraduate Replacement
CS 3000 Algorithms and DataCS 5800 Algorithms
DS 3000 Foundations of Data ScienceDS 5110 Introduction to Data Management and Processing
DS 4400 Machine Learning and Data Mining 1DS 5220 Supervised Machine Learning and Learning Theory
DS 4420 Machine Learning and Data Mining 2DS 5230 Unsupervised Machine Learning and Learning Theory

Campus location

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    Boston

    Located in the heart of Boston, Northeastern’s oldest campus is home to a vibrant community of students, researchers, and faculty working across disciplines to build a better world through CS.

Meet our faculty

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