The Data Science Master’s degree at the Johns Hopkins University 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 in mathematical ones, and then solving these problems by using a diverse collection of scientific tools.
In addition to Introduction to Data Science (EN.553.636), students will take one course in each of the four core areas: Statistics, Machine Learning, Optimization, and Computing. Students will decide on an area of focus and take three courses in either Computational Medicine, Computational Machine Learning, Computer Vision, Computational Finance, Mathematics of Data Science, Language and Speech, or Statistical Theory. The final capstone project is course EN.553.806 Capstone Experience in Data Science, and include a research topic approved by the faculty advisor and the Internal Oversight Committee, and a written paper. The goal of the final course and written paper is to allow the student to apply data analysis techniques learned in the program, and possibly to extend those ideas to more general settings or to new application areas. Lastly, the paper will be summarized in a poster session organized at the end of each semester.
One course in each of the four Core Areas below. Courses chosen in this section must be distinct from the courses used to satisfy requirements 2 and 3.
Three courses from one of the following focus areas.
Capstone Experience in Data Science (EN.553.806), or another project-oriented course approved by the research supervisor, academic advisor and the Internal Oversight Committee. Students must complete a Proposal Request for the Capstone Experience in Data Science form and follow instructions to submit for approval before being permitted to enroll in EN.553.806.
|Prior to First Semester:||Orientation Program (2 days)|
|Year 1: FALL||Introduction to Data Science|
|(4 courses)||Computing (Core)|
|OPTION A||Core Area 3|
|OPTION B||Area of Focus 1|
|Year 1: Intersession||Online Data Science Ethics Course|
|Year 1: SPRING||OPTION A||Core Area 4|
|Area of Focus 2|
|Area of Focus 3|
|OPTION B||Core Area 4|
|Area of Focus 1|
|Area of Focus 2|
|Area of Focus 3 (or Elective)|
|Year 2: FALL OR SPRING||Capstone Experience|
|(2 courses)||OPTION A||Elective|
|OPTION B||Elective (or Area of Focus)|
|Arora, Raman||Computer Science/MINDS||[email protected]|
|Basu, Amitabh||Applied Mathematics/MINDS||[email protected]|
|Braverman, Vladimir||Computer Science/MINDS||[email protected]|
|Budavari, Tamas||Applied Mathematics/MINDS||[email protected]|
|Caffo, Brian||Biostatistics/MINDS||[email protected]|
|Chellappa, Rama||Electrical & Computer Eng/MINDS||[email protected]|
|Eisner, Jason||Computer Science/MINDS||[email protected]|
|Fertig, Elana||Oncology/MINDS||[email protected]|
|Naiman, Daniel||Applied Mathematics||[email protected]|
|Patel, Vishal||Electrical & Computer Eng/MINDS||[email protected]|
|Priebe, Carey||Applied Mathematics/MINDS||[email protected]|
|Shpitser, Ilya||Computer Science/MINDS||[email protected]|
|Venkataraman, Archana||Electrical & Computer Eng/MINDS||[email protected]|
|Vidal, Rene||Biomedical Engineering/MINDS||[email protected]|
|Xu, Yanxun||Applied Mathematics/MINDS||[email protected]|
|Younes, Laurent, Program Director||Applied Mathematics/MINDS||[email protected]|