Students in the DSAN program must successfully complete 30 credits and maintain a cumulative GPA of no less than 3.00.
Data Science and Analytics Coursework
There are five three-credit core courses that are designed to provide students with a solid foundation in data science. We also give a zero-credit programming bootcamp course in the summer prior to matriculation. The additional five three-credit elective courses allow students to learn tailored skills, helping them apply data analysis to fields of interest. Coursework may be taken in any order that is allowed by the prerequisites.
Courses will be offered during the fall semester (late August through early December) and the spring semester (early January through early May). In addition, summer courses may be offered. Courses will typically meet once per week in the late afternoon or early evening.
Students may enroll on a full-time or part-time basis, usually starting in the fall semester of each academic year. Full-time students will be able to complete the degree in 16 calendar months by taking three courses per semester for three semesters, plus a summer course. Students may, however, take up to three years to complete the program, e.g. by taking one or two courses per semester plus summer courses.
The Georgetown DSAN program gives an online course in programming preparation that covers R, Python, and command line use in the summer prior to matriculation. The course is equivalent to three credits, is designed for matriculating MS Data Science & Analytics students, and is offered free of charge. It is required for all incoming students. This course will run during the Georgetown Summer Session (June – August). Students must complete this course to matriculate in the fall.
Full-Time Course Plan
Fall Semester: Year One
| Course Name | Credits |
|---|---|
| DSAN 5000 Data Science and Analytics (Core Course) | 3 |
| DSAN 5100 Probabilistic Modeling and Statistical Computing (Core Course) | 3 |
| Elective Course | 3 |
Spring Semester:Year One
| Course Name | Credits |
|---|---|
| DSAN-5200: Analytical Data Visualization (Core Course) | 3 |
| DSAN-5300: Statistical Learning (Core Course) | 3 |
| Elective Course | 3 |
Summer Semester between Year One and Year Two-Optional
| Course | Credits |
|---|---|
| DSAN-5925: Internship | .25 |
OR
| Course | Credits |
|---|---|
| Elective(s) | 3 (each) |
Fall Semester: Year Two
| Course | Credits |
|---|---|
| DSAN-6000: Big Data and Cloud Computing (Core Course) | 3 |
| Elective Course | 3 |
| Elective Course | 3 |
Spring Semester: Year Two
| Course | Credits |
|---|---|
| Elective | 3 |
| Internship (Optional) | .25 |
Note: You can graduate sooner by taking your final elective in the fall semester.
Part-Time Course Plan
Fall Semester: Year One
| Course | Credits |
|---|---|
| DSAN-5000: Data Science and Analytics | 3 |
| DSAN-5100: Probabilistic Modeling and Statistical Computing | 3 |
Spring Semester: Year One
| Course | Credits |
|---|---|
| DSAN-5200: Analytical Data Visualization | 3 |
| DSAN-5300: Statistical Learning | 3 |
Fall Semester: Year Two
| Course | Credits |
|---|---|
| DSAN-6000: Big Data and Cloud Computing | 3 |
| Elective | 3 |
Spring Semester: Year Two
| Course | Credits |
|---|---|
| Elective | 3 |
| Elective | 3 |
Fall Semester: Year Three
| Course | Credits |
|---|---|
| Elective | 3 |
| Elective | 3 |
Note: PT DSAN students may take 1 or 2 classes per semester, provided degree requirements are completed within 3 calendar years. PT students may complete degree requirements earlier by taking 1-2 classes during the summer semesters.
BS-MS Accelerated Course Plan
Option One: One DSAN Class per Semester in Senior Year
Fall Semester: Undergraduate Senior Year
| Course | Credits |
|---|---|
| DSAN-5000: Data Science and Analytics | 3 |
Spring Semester: Undergraduate Senior Year
| Course | Credits |
|---|---|
| DSAN-5200: Analytical Data Visualization | 3 |
Fall Semester: First-Year Graduate Student
| Course | Credits |
|---|---|
| DSAN-5100: Probabilistic Modeling and Statistical Computing | 3 |
| DSAN-6000: Big Data and Cloud Computing | 3 |
| Elective | 3 |
Spring Semester: First- Year Graduate Student
| Course | Credits |
|---|---|
| DSAN-5300: Statistical Learning | 3 |
| Elective | 3 |
| Elective | 3 |
Fall Semester: Second-Year Graduate Student
| Course | Credits |
|---|---|
| Elective | 3 |
| Elective | 3 |
Option Two: Two DSAN Courses per Semester in Senior Year
Fall Semester: Undergraduate Senior Year
| Course | Credits |
|---|---|
| DSAN-5000: Data Science and Analytics | 3 |
| DSAN-5100: Probabilistic Modeling and Statistical Computing | 3* |
Spring Semester: Undergraduate Senior Year
| Course | Credits |
|---|---|
| DSAN-5200: Analytical Data Visualization | 3 |
| DSAN-5300: Statistical Learning | 3* |
Fall Semester: First-Year Masters
| Course | Credits |
|---|---|
| DSAN-6000: Big Data and Cloud Computing | 3 |
| Elective | 3 |
| Elective | 3 |
Spring Semester: First-Year Masters
| Course | Credits |
|---|---|
| Elective | 3 |
| Elective | 3 |
| Elective | 3 |
*DSAN accelerated students may double-count (i.e. apply toward both UG and grad degree requirements) only TWO DSAN classes. Any DSAN classes taken during senior year beyond the two double-counted classes are permitted only if the student has earned at least 120 undergraduate credit hours, and will apply toward the MS degree only (NOT the undergraduate degree).