Course Schedule

The Master of Science in Data Science & Analytics (DSAN) program requires 30 credits. You’ll take five core courses to establish your foundational knowledge and five elective courses to explore your interests through your selected concentration. We offer different paths to achieving the degree: full-time, part-time and an accelerated B.S (B.A.)./M.S. for current Georgetown undergraduates.

Course schedule options


Full-time course schedule

Full-time students will take three courses per semester. You can graduate sooner by taking your final elective in the Fall semester or by taking a course in the summer prior to the graduating semester.

Year 1

SemesterCreditCourse
Fall3DSAN 5000: Data Science and Analytics
(Core Course)
3DSAN 5100: Probabilistic Modeling and Statistical Computing
(Core Course)
3Elective course
Spring3DSAN 5200: Analytical Data Visualization
(Core Course)
3DSAN 5300: Statistical Learning
(Core Course)
3Elective course
Summer (Optional).25
or
3
Internship (Optional)
or
Elective course

Year 2

SemesterCreditCourse
Fall3DSAN 6000: Big Data and Cloud Computing
(Core Course)
3Elective course
3Elective course
.25Internship (Optional)
Spring3Elective course
.25Internship (Optional)

Part-time course schedule

We offer a part-time option so you can pursue your graduate degree while managing other priorities in your life. With courses offered after traditional working hours, part-time students may take one to two courses per semester. While you must complete the degree in three calendar years, you can finish earlier if you take classes during the summer.

Year 1

SemesterCreditCourse
Fall3DSAN-5000: Data Science and Analytics
3DSAN-5100: Probabilistic Modeling and Statistical Computing
Spring3DSAN-5200: Analytical Data Visualization
3DSAN-5300: Statistical Learning

Year 2

SemesterCreditCourse
Fall3DSAN-6000: Big Data and Cloud Computing
3Elective course
Spring3Elective course
3Elective course

Year 3

SemesterCreditCourse
Fall3Elective course
3Elective course

B.S./M.S. accelerated course plan 

This accelerated degree is an option to start graduate school while finishing your undergraduate degree. There are two options for the course schedule:

Option one: one Data Science & Analytics class per semester in senior year

Undergraduate senior year

SemesterCreditCourse
Fall3DSAN 5000: Data Science and Analytics
Spring3DSAN 5200: Analytical Data Visualization

Master’s year 1 

SemesterCreditCourse
Fall3DSAN 5100: Probabilistic Modeling and Statistical Computing
3DSAN 6000: Big Data and Cloud Computing
3Elective
Spring3DSAN 5300: Statistical Learning
3Elective
3Elective

Master’s year 2

SemesterCreditCourse
Fall3Elective
3Elective

Option two: two Data Science & Analytics courses per semester in senior year

Undergraduate senior year

SemesterCreditCourse
Fall3DSAN 5000: Data Science and Analytics
3*DSAN 5100: Probabilistic Modeling and Statistical Computing
Spring3DSAN 5200: Analytical Data Visualization
3*DSAN 5300: Statistical Learning

*You may double-count (i.e., apply toward both your undergraduate and graduate degree requirements) two Data Science and Analytics classes. Any data science and analytics classes taken during your senior year beyond the two double-counted courses are permitted only if you have earned at least 120 undergraduate credit hours – these additional courses will count toward the M.S. degree only.

Master’s year 1

SemesterCreditCourse
Fall3DSAN 6000: Big Data and Cloud Computing
3Elective
3Elective
Spring3Elective
3Elective
3Elective

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