To earn a master’s degree at Washington University, a student must complete all courses required by their department; maintain satisfactory academic progress; pass certain examinations; fulfill all academic and residence requirements; and apply for program completion (graduation) via Workday Student.
For the details of master’s degree general requirements in Arts & Sciences, including an explanation of Satisfactory Academic Progress, students should review the Master’s Degree Academic Information page of the Arts & Sciences Bulletin.
Program Requirements
- Total Units Required: 30 units
- Degree Length: Two additional semesters
- Note: Students must be enrolled in at least 9 graduate credits each semester to retain full-time status. As students complete their coursework, if enrolled in fewer than 9 graduate credits, they must enroll in a specific Arts & Sciences graduate course that will show 0 units but does count as full-time status. Students should connect with their department to ensure proper enrollment prior to the Add/Drop date.
Statistics and Data Science, Accelerated BA/MA
The Office of Graduate Studies, Arts & Sciences, has an accelerated BA/MA program in which highly qualified WashU undergraduate majors can earn both the BA and MA degrees with two additional semesters of work (usually a total of five years).
This program is only for Washington University undergraduates who, if they participate, must do so in the academic year immediately following graduation of their BA degree (no deferments). Eligibility requires having completed the BA degree from Arts & Sciences or a BA, BS, or BSBA degree from another school or college at Washington University that includes sufficient coursework from the Department of Statistics and Data Science.
For students in the accelerated BA/MA pathway, a minimum of 9 units and a maximum of 12 units at the 4000 or 5000 level with mixed enrollment taken during undergraduate study may be applied to the MA degree, subject to approval. BA/MA students may enroll in the 4000-level version of a 4000/5000 paired course while they are undergraduates, and these units may be applied to the accelerated MA. Once the students become graduate students, in their fifth year, they must take only 5000-level or above graduate courses. Accelerated BA/MA students must complete all BA requirements prior to matriculating into the MA program; they are expected to have completed at least 9 graduate-applicable units prior to their fifth year (the +1 master's year).
The application deadline (subject to change by the Office of Graduate Studies, Arts & Sciences) is the March 15 before beginning the MA program in the fall semester following the completion of the Washington University BA degree. Note that the application is made through the department, which forwards it to the Office of Graduate Studies, Arts & Sciences. Applicants must specify in their application that they are applying to the accelerated program.
The program offers two concentrations: Statistics and Applied Data Science. The Statistics concentration is intended for students seeking deeper training in statistical theory, mathematical statistics, and advanced statistical methodology, including those preparing for PhD study or technically intensive statistical work. The Applied Data Science concentration is designed for students who want rigorous training in statistical modeling, computation, and data science, with greater flexibility to connect these tools to domain-specific applications in areas such as biology, economics, political science, psychology, and other data-driven fields. Students in both concentrations must satisfy the general requirements (listed below).
The degree requires 30 units of coursework. Students may also choose an optional thesis pathway, which requires 6 additional units of thesis research, bringing the total requirement to 36 units. The minimum residence requirement is one full academic year of graduate study. A GPA of B (3.0) or better must be maintained in graduate courses. To be eligible for the thesis option, a student must maintain a cumulative GPA of 3.5 or higher in the first 18 units of courses satisfying the program requirements.
Required Courses
Students must take the following required courses or their equivalents. The required courses differ slightly based on the student's concentration.
Required Courses for the Applied Data Science Concentration
| Code | Title | Units |
|---|---|---|
| SDS 5005 | Essentials of Probability Models and Statistical Inference | 3 |
| SDS 5130 | Linear Statistical Models | 3 |
| SDS 5210 | Statistical Computation | 3 |
| SDS 5215 | Python for Data Science | 3 |
| SDS 5910 | Practical Training in Statistics | 0 |
| Total Units | 12 | |
SDS 5005 Essentials of Probability Models and Statistical Inference may be replaced with the sequence of both SDS 5010 Probability and SDS 5020 Mathematical Statistics. In that case, the student will earn a total of 6 units, with the additional 3 units counted toward electives.
If an equivalent course has been taken and proficiency in the course material has been demonstrated, other 5000-level and above electives may be chosen by the student in consultation with their advisor to make up the 30 units. Typically, at most three electives will be chosen from outside the Department of Statistics and Data Science.
Electives (18 units)
Students will select 5000-level electives primarily from SDS, with up to 9 units from other departments. Any SDS 5000+-level course can count toward the approved 18 units of electives, except for teaching seminars, research, or independent work. Approved outside elective courses are listed below:
| Code | Title | Units |
|---|---|---|
| BBS 5483 | Human Genetic Analysis | 3 |
| BIOL 5181 | Population Genetics | 3 |
| BIOL 5220 | Practical Bioinformatics | 4 |
| CSE 5100 | Deep Reinforcement Learning | 3 |
| CSE 5104 | Data Mining | 3 |
| CSE 5105 | Bayesian Methods in Machine Learning | 3 |
| CSE 5107 | Machine Learning | 3 |
| CSE 5109 | Advanced Machine Learning | 3 |
| CSE 5270 | Natural Language Processing | 3 |
| CSE 5610 | Large Language Models | 3 |
| DAT 5550 | Machine Learning Tools for Prediction of Business Outcomes | 3 |
| DAT 5561 | Introduction to Python and Data Science | 3 |
| ECON 6110 | Econometrics | 3 |
| ECON 6140 | Machine Learning and Data Science in Economics | 3 |
| ECON 6840 | Introduction to STATA | 1.5 |
| ECON 6850 | A First Python Course for Economists | 1.5 |
| ECON 8111 | Quantitative Methods in Economics II | 3 |
| ECON 8130 | Structural Microeconometrics | 3 |
| ECON 8135 | Advanced Microeconometrics | 3 |
| ESE 5450 | Stochastic Control | 3 |
| FIN 5380 | Stochastic Foundations for Finance | 1.5 |
| FIN 5390 | Mathematical Finance | 1.5 |
| INFO 5558 | Applications of Deep Neural Networks | 3 |
| MATH 5011 | Introduction to Analysis | 3 |
| MATH 5012 | Introduction to Lebesgue Integration | 3 |
| MATH 5031 | Linear Algebra | 3 |
| MATH 5051 | Numerical Applied Mathematics | 3 |
| MATH 5056 | Topics in Financial Mathematics | 3 |
| MATH 5151 | Measure Theory and Functional Analysis I | 3 |
| MATH 5152 | Measure Theory and Functional Analysis II | 3 |
| POLSCI 5063 | Causal Inference | 3 |
| POLSCI 5626 | Applied Statistical Programming | 3 |
| POLSCI 5720 | Topics in Quantitative Political Methodology: Computational Social Science | 3 |
| PSYCH 8068 | Hierarchical Linear Models | 3 |
| PSYCH 8167 | Applied Bayesian Statistics for Psychologists | 3 |
Students may petition for the eligibility of courses outside this list after consultation with their advisor. A list of eligible electives is also available on the Master's Degree Program page on the Department of Statistics and Data Science website. The department's list may be more up to date as additional electives can be added after the update of the Bulletin.
Thesis
A student in the proposed concentration may choose a thesis option to gain data science research experience. To complete this option, each student needs to complete 6 additional units through independent work and research with a faculty advisor, typically during the final two semesters of the program, bringing the total degree requirement to 36 units. To be eligible for the thesis option, a student must maintain a cumulative grade point average of 3.5 or higher in the first 18 units of coursework satisfying the program requirements. It is the student's responsibility to find a thesis advisor who is willing to guide their research. During the student's last semester of studies, the student is required to defend their thesis through a presentation accompanied by a question-and-answer period.
Applying to the Program
Interested majors should consult with the SDS Director of Master's Programs by the beginning of the fall semester of their senior year, before the add/drop deadline, to ensure that all necessary courses will be completed during the senior year. Students are strongly recommended to contact the program director early. If accepted, students must begin the program in the fall semester immediately after graduation; no deferred admissions are allowed by the Office of Graduate Studies, Arts & Sciences.
International Students
For students in the United States on a visa as undergraduates, staying on to complete an MA creates a change in visa status, which will involve reapplication paperwork. Interested students should check on the details with an international student advisor at the Office for International Students and Scholars.