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Data Science, Master of Science

The Data Science Master's program at the Johns Hopkins University is a fully residential program which will provide the training in applied mathematics, statistics, and computer science to serve as the basis for an understanding and appreciation of existing data science tools. Our program aims to produce the next generation of leaders in data science by emphasizing mastery of the skills needed to translate real-world data-driven problems into mathematical ones, and then solving these problems by using a diverse collection of scientific tools.

Overview

The Data Science Master's program is designed to be completed in three semesters of full-time residential (on-campus) graduate study.

Admission

Admissions Process and Materials

To ensure timely consideration of your application, please complete the items in the following checklist at your earliest convenience.

• Complete the online application, including:
  • statement of purpose
  • supplementary information section
  • non-refundable $75 application fee
  • unofficial transcripts
  • TOEFL/IELTS (for international students)
  • 3 letters of recommendation
• If English is not your native language, arrange for TOEFL or IELTS Examination scores to be sent to the department by the testing organization.
• Arrange for three letters of recommendation from persons familiar with your abilities and achievements, especially relevant to graduate study in applied mathematics, to be submitted electronically through the online application.
• Arrange for unofficial transcripts of all undergraduate and previous graduate study to be uploaded into your online application.

Admissions Criteria

Prospective students for our graduate programs must have completed a Bachelors level degree, ideally in Engineering, Mathematics, Computer Science, or in the Sciences. In addition, candidates should ideally have completed undergraduate-level courses in:

• Calculus, through multivariable calculus
• Linear algebra
• Differential equations
• Probability, preferably complemented with a course in Statistics
• Computer programming (e.g., in C++)
• At least one proof-writing course

Admissions decisions are based on four major factors: Mathematical course background, grades (GPA), Graduate Record Examination (GRE) scores, and recommendation letters.

Program Requirements

The program requirements differ based on the matriculation date.

Program Requirements for Students Who Matriculated Prior to Fall 2025

1. Orientation sessions starting 2 weeks before the first day of classes.
2. EN.553.636 Introduction to Data Science.
3. One course in each of the four Core Areas.
4. Four elective courses.
5. Data Science Capstone Experience (6 credit course), poster presentation, and final paper.
6. Complete training on the responsible and ethical conduct of research.
7. Receive a Passing grade in the mandatory Graduate Academic Ethics course, EN.500.603 (01).
8. Data Science Ethics course.
9. The communication skills requirement (Communication Skills Practicum)

Program Requirements for Students Who Matriculated Fall 2025 or Later

Students have the choice to complete a Capstone Option or a Course Only Option.

Capstone Option

1. Orientation sessions starting 2 weeks before the first day of classes.
2. EN.553.636 Introduction to Data Science -OR- EN.601.675 Machine Learning. Must be taken the first semester.
3. One course in each of the four Core Areas.
4. Three elective courses.
5. Data Science Capstone Experience*. Six credit course which may be taken in two semesters of 3 credits each.
6. Complete training on the responsible and ethical conduct of research.
7. Receive a Passing grade in the mandatory Graduate Academic Ethics course, EN.500.603 (01).
8. Data Science Ethics course.
9. The communication skills requirement (Communication Skills Practicum)

Course Only Option

1. Orientation sessions starting 2 weeks before the first day of classes.
2. EN.553.636 Introduction to Data Science OR EN.601.675 Machine Learning. Must be taken the first semester.
3. One course in each of the four Core Areas.
4. Five elective courses.
5. Complete training on the responsible and ethical conduct of research.
6. Receive a Passing grade in the mandatory Graduate Academic Ethics course, EN.500.603 (01).
7. Data Science Ethics course.
8. The communication skills requirement (Communication Skills Practicum)

Core Areas

Select one course in each of the four Core Areas:

• Statistics
• Machine Learning
• Optimization
• Computing

Elective Courses

The following additional courses may be taken to fulfill the elective requirement. Courses listed in the core areas may be taken for the elective requirement, however, they may not be double-counted.

Capstone Experience

The Capstone Experience in Data Science (EN.553.806 or EN.553.506 for undergraduates) is a research-oriented project which must be approved by the research supervisor, academic advisor, and the Internal Oversight Committee. The Capstone Experience can be taken in multiple semesters, but the total number of credits required for successful completion is six (6).

Additional Required Courses

In addition to the above course requirements, all data science master's students will complete:

• An online Data Ethics course
• The communication skills requirement (Communication Skills Practicum)
• Online course on Responsible Conduct of Research (AS.360.624)
• University Orientation and Academic Ethics (EN.500.603) - students are automatically enrolled in their first semester

Additional Notes

• A course grade of B- or better is required to meet all course requirements. One grade of C/C+, is permitted to count towards program requirements.
• Courses cannot be double-counted for different requirements (even if they appear in several core and/or elective areas).
• All students are required to submit a program plan for review. If any deviations are made from this plan, students are required to submit an updated plan for review.