Admissions Requirements

Degree Requirements

  • Ten courses must be completed within five years.
  • The curriculum consists of seven required courses, one Applied and Computational Mathematics ( elective, one Computer Science elective (, and one elective course from the Data Science program ( or from the list of Additional Selections below. Two of the elective courses must be at the 700-level.
  • Courses applied toward undergraduate or graduate degrees at other institutions (non-JHU) are not eligible for transfer or double counting to a Data Science master’s degree or post-master’s certificate. Up to two graduate courses taken outside of JHU after an undergraduate degree was conferred and not applied toward a graduate or other degree may be considered toward the Data Science master’s degree subject to advisor approval.
  • Graduate students who are not pursuing a master’s degree in Data Science should consult with their advisor to determine which courses must be successfully completed before 600- or 700-level Data Science courses may be taken.
  • Only one C-range grade (C+, C, or C−) can count toward the master’s degree.
  • Course selections outside of the Data Science foundational, required, and elective courses are subject to advisor approval.

Course Planning and Search

Wondering what course to take when or which courses are required? Use these helpful course planning and course search tools to help map out your path to degree completion.

Academic Calendar

Find out when registration opens, classes start, transcript deadlines and more. Applications are accepted year-round, so you can apply any time.

Certificate in Data Science

If you are not quite ready to commit to another master’s degree, take a look at pursuing our post-master’s certificate option. You can earn this certificate in 5 courses.

Looking to Study Full-Time?

Whether your goal is to become a data scientist with a focus on understanding consumer and market trends or provide insights and statistics about diseases in medicine, you will be prepared to tackle any data-driven problem with skill.