Degree Requirements
The following requirements apply to the SM degrees in Data Science. Note that the term "course" refers to a typical Harvard semester-length course, i.e., a 4-credit FAS course or its equivalent. 2-credit courses such as AC 298r count as "half of a course" in the context of these requirements.
Degree Program Options
|
Master of Science (SM) in 3 semesters |
Master of Science (SM) in 4 semesters |
Master of Science (SM) in 4 semesters with thesis |
|
|
Credit requirements |
48 |
48-64 |
56 |
|
Typical course load |
12 classes |
12-16 classes |
9-11 classes plus 12-20 credits of research |
General Requirements
- Unless completing a thesis, twelve letter-graded courses are required for the degree. As many of these as possible should be SEAS 200/2000-level courses. To account for the time spent on thesis research, students choosing the thesis option are able to substitute three required courses (the Capstone and two "free" elective courses (as defined in the course requirement section ) with AC 302.
- No 300/3000-level courses may be included among the twelve required, letter-graded courses.
- Up to six of the twelve courses may be 100/1000-level SEAS/FAS courses or U-level MIT courses. Courses lower than the 100/1000-level, including all General Education courses, may not be counted towards the degree.
- Students may include no more than one semester of the reading and research course (AC 299r) and two semesters/four credits of the seminar/project course (AC 298r) among the twelve courses.
- Harvard Extension School courses and transfer credit are not accepted toward the degree. Waivers for course requirements may be approved on a case-by-case basis, but will not reduce the total number of credits required for the degree.
Grade requirements: In order to be eligible to count for the SM degree, a class grade must be a C (2.0) or higher, and the average grade of all courses counting towards the SM degree must be B (3.0) or higher.
Course Requirements for students matriculating in Fall 2024
|
Required for SM in 3 or 4 semesters? |
Required for SM in 4 semesters with a thesis? |
|
| Data Science/Machine Learning | ||
|
AC 209a (Data Science 1: Introduction to Data Science) * AC 209b (Data Science 2: Advanced Topics in Data Science) * CS 1810 (Machine Learning) 1 of the following Statistics courses:
|
✅ ✅ ✅ Choose 3 of 4
|
✅ ✅ ✅ Choose 3 of 4
|
| Computing | ||
|
AC 215 (Advanced Practical Data Science) AM 215 (Mathematical Modeling for Computational Science) CS 2050 (Computing Foundations for Computational Science) STAT 221 (Computational Tools for Statistical Learning) |
✅ Choose 1 of 4 |
✅ Choose 1 of 4 |
| Ethics | ||
|
AC 221 (Critical Thinking in Data Science) |
✅ |
✅ |
| Department Electives Courses often chosen as electives are listed on the Data Science courses page. | ||
|
Computer Science elective Statistics elective |
✅ ✅ |
✅ ✅ |
| “Free” Data Science Electives may be from SEAS, other FAS departments, other schools at Harvard, or MIT. Up to four credits (two semesters) of the AC 298r seminar course and up to one semester of an Independent Study (AC 299r) may also be counted as an elective. | ||
|
“Free” data science elective 1 |
✅ |
✅ |
| “Free” data science elective 2 | ✅ | ✅ |
|
“Free” data science elective 3 |
✅ (May be non-technical) |
Fulfilled by any combination of additional electives or 12-20 credits of AC 302 (Research Credit) |
|
“Free” data science elective 4 |
✅ (May be non-technical) |
|
|
Research experience |
✅ Fulfilled by AC 297r (Capstone Project) |
* Students can choose to substitute CS 1090a/b for AC 209a/b. These will count towards the maximum number of six 100/1000-level courses that can be counted toward the Data Science degree.
Course Requirements for students who matriculated in Fall 2023 and earlier
|
Required for SM in 3 or 4 semesters? |
Required for SM in 4 semesters with a thesis? |
|
|
Core Courses |
||
|
*AC 209a (Data Science 1: Introduction to Data Science) |
✅ |
✅ |
|
*AC 209b (Data Science 2: Advanced Topics in Data Science) |
✅ |
✅ |
|
AM 207 (Advanced Scientific Computing: Stochastic Methods for Data Analysis, Inference, and Optimization) |
✅ |
✅ |
|
AC 207 (Systems Development for Computational Science) |
✅ |
✅ |
|
AC 221 (Critical Thinking in Data Science) |
✅ |
✅ |
|
Department Electives Courses often chosen as electives are listed on the Data Science courses page. |
||
|
Computer Science elective |
✅ |
✅ |
|
Statistics elective |
✅ |
✅ |
|
“Free” Data Science Electives may be from SEAS, other FAS departments, other schools at Harvard, or MIT. Up to four credits (two semesters) of the AC 298r seminar course and up to one semester of an Independent Study (AC 299r) may also be counted as an elective. |
||
|
“Free” data science elective 1 |
✅ |
✅ |
|
“Free” data science elective 2 |
✅ |
✅ |
|
“Free” data science elective 3 |
✅ (May be non-technical) |
Fulfilled by any combination of additional electives or 12-20 credits of AC 302 (Research Credit) |
|
“Free” data science elective 4 |
✅ (May be non-technical) |
|
|
Research experience |
✅ Fulfilled by AC 297r (Capstone Project) |
* Students can choose to substitute CS 1090a/b for AC 209a/b. These will count towards the maximum number of 6 100/1000-level courses that can be counted toward the degree.
Thesis Option
Data Science master’s students can choose to satisfy the research experience requirement by selecting the thesis option. Students will spend the majority of their second year working on a substantial data science project that culminates in the submission and oral defense of a master’s thesis. While all thesis projects must be related to data science, students are given leeway in finding a project in a domain of study that fits with their background and interest.
All students choosing the thesis option must find a research advisor and submit a thesis proposal by mid-April of their first year of study. Thesis proposals will be evaluated by the Data Science faculty committee and only those students whose proposals are accepted will be allowed to continue with the thesis option. Follow this link for more information about Data Science SM thesis proposals.
To account for the time spent on thesis research, students choosing the thesis option are able to substitute three required courses (the Capstone and two "free" elective courses (as defined in the final bullet point in the course requirement section ) with AC 302.