The online master’s degree in data science prepares you to succeed in specialized jobs involving everything from the data pipeline and storage to statistical analysis and eliciting the story the data tells. Learn from senior-level engineers and data scientists who will incorporate realistic scenarios in your studies that you have or will encounter as a professional.
Admission Requirements
- You must meet the general admission requirements that pertain to all graduate certificate candidates.
- Your prior education must include the following prerequisites: (1) Three semesters or five quarters of calculus, which includes multivariate calculus; (2) One semester/term of advanced math (discrete mathematics is strongly preferred but linear algebra and differential equations will be accepted); (3) One semester/term of Java or Python (C++ will be accepted but the student must be at least also somewhat knowledgeable in Java or Python).
- If your prior education does not include the prerequisites listed above, you may still be admitted under provisional status, followed by full admission once you have completed the missing prerequisites. Missing prerequisites may be completed with Johns Hopkins Engineering (all prerequisites are available) or at another regionally accredited institution.
- If you decide to pursue the full master’s degree, all courses will apply to the master’s degree provided they meet program requirements and fall within a five-year time limit. You must declare your intention prior to completing the certificate.
- If you are an international student, you may have additional admission requirements.
Certificate Requirements
- Complete the two foundational courses and two electives offered from the course list below. These must be completed within five years.
- One or more required courses can be waived by your advisor if you have received a grade of a B− or above in equivalent graduate courses. In this case, you may replace the waived required courses with the same number of other graduate Data Science courses and may take these courses after all remaining course requirements have been satisfied.
- Only one C-range grade (C+, C, or C−) can count toward the graduate certificate.
- All course selections outside the four required foundational courses are subject to advisor approval.
Required Courses
Course Number & Name | Course Format |
---|---|
Course Number & Name: 625.603 - Statistical Methods and Data Analysis | Course Format: Asynchronous Online, Hybrid In-person and Synchronous Online |
Course Number & Name: 685.621 - Algorithms for Data Science | Course Format: Asynchronous Online |
Elective Courses
Two courses must be chosen
Course Number & Name | Course Format |
---|---|
Course Number & Name: 605.641 - Principles of Database Systems | Course Format: Asynchronous Online |
Course Number & Name: 605.649 - Principles and Methods in Machine Learning | Course Format: Asynchronous Online, Synchronous Online |
Course Number & Name: 625.615 - Introduction to Optimization | Course Format: Asynchronous Online |
Course Number & Name: 625.664 - Computational Statistics | Course Format: Asynchronous Online |
Course Number & Name: 605.662 - Data Visualization | Course Format: Asynchronous Online |
Course Number & Name: 625.661 - Statistical Models and Regression | Course Format: Asynchronous Online |
Course Number & Name: 685.648 - Data Science | Course Format: Asynchronous Online |
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.
Master's in Data Science
Explore a part-time, online master's degree, and take carefully constructed, modern courses designed for the way you live and work today—all while having invaluable mentorship from professors you can conveniently access.