The requirements for the proposed M.S. in Data Science are structured so that undergraduate student would be able to pursue a five-year Bachelor’s/Master’s program, in which the Bachelor’s degree is awarded in any major offered at WPI and the Master’s degree is awarded in Data Science. Students enrolled in the B.S./M.S. program must satisfy all the program requirements of their respective B.S. degree and all the program requirements of the M.S. degree in Data Science. For students who will earn the Data Science B.S. degree at WPI, the “Integrative Data Science” core area requirement is waived. Instead, the students can earn the corresponding 3 credits by taking any of the data science courses listed in the graduate catalog, including DS 501.
WPI allows the double counting of up to 12 credits for students pursuing a 5-year Bachelor’s/Master’s program. This overlap can be achieved through the following mechanisms. Students may double-count courses towards both their undergraduate and graduate degrees whose credit hours total no more than 40 percent of the 30 credit hours required for the M.S. degree in Data Science, and that meet all other requirements for each degree. These courses can include graduate courses as well as certain undergraduate 4000-level course as long as the undergraduate course is acceptable in place of a corresponding graduate course that satisfies a Data Science M.S. requirement.
In consultation with the academic advisor, the student prepares a Plan of Study outlining the selections chosen to satisfy the B.S./M.S. degree requirements, including the courses that will be double-counted. This Plan of Study must then be approved by the Data Science Program.
As a university wide rule, the B.S./M.S. double counting credits can be applied for only while the student is an undergraduate student.
Double Counting Credits From 4000-Level Courses
For the following 4000-Level courses, two graduate credits will be earned towards the B.S./M.S. degree if the student achieves grade B or higher, or otherwise with the instructor’s approval. In addition, faculty may offer, at their discretion, an additional 1/6 undergraduate unit, or equivalently a 1 graduate credit, for completing additional work in the course. To obtain this additional credit, the student must register for 1/6 undergraduate unit of independent study at the 4000-level or a 1 graduate credit independent study at the 500-level, with permission from the instructor.
Courses from Computer Science |
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CS 4120 Analysis of Algorithms |
CS 4341 Introduction to Artificial Intelligence |
CS 4342 Machine Learning |
CS 4432 Database Systems II |
CS 4445 Data Mining and Knowledge Discovery in Databases |
CS 4518 Mobile and Ubiquitous Computing |
CS 4802 BioVisualization |
CS 4803 Biological and Biomedical Database Mining |
Courses from Mathematical Sciences |
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MA 4235 Mathematical Optimization |
MA 4603 Statistical Methods in Genetics and Bioinformatics |
MA 4631 Probability and Mathematical Statistics I |
MA 4632 Probability and Mathematical Statistics II |
DS 4635/MA 4635 Data Analytics and Statistical Learning |
Other 4000-level courses not listed above, including 4000-level independent study courses, require a petition and approval from the Data Science Graduate Committee before they can double-count for the B.S./M.S. degree.
Restricted Undergraduate and Graduate Course Pairs
Some undergraduate and graduate courses have significant overlap in their content. The following table lists these courses.
A student can receive credit towards their M.S. degree for at most one of the two courses in any row of this table.
Courses from Computer Science
Undergraduate Course | Graduate Course |
CS 4341 Introduction to Artificial Intelligence | CS 534 Artificial Intelligence |
CS 4342 Machine Learning | CS 539 Machine Learning |
CS 4432 Database Systems II | CS 542 Database Management Systems |
CS 4445 Data Mining and Knowledge Discovery | CS 548 Knowledge Discovery and Data Mining |
CS 4518 Mobile and Ubiquitous Computing | CS 528 Mobile and Ubiquitous Computing |
CS 4802 Biovisualization | CS 592 Biovisualization |
CS 4803 Biological and Biomedical Database Mining | CS 583 Biological and Biomedical Database Mining |
Courses from Mathematical Sciences
Undergraduate Course | Graduate Course |
MA 4631 Probability and Mathematical Statistics I | MA 540 Probability and Mathematical Statistics I |
MA 4632 Probability and Mathematical Statistics II | MA 541 Probability and Mathematical Statistics II |
DS 4635/MA 4635 Data Analytics and Statistical Learning | MA 543/DS 502 Statistical Methods for Data Science |
Satisfying Data Science Core Areas
B.S./M.S. students can use the B.S./M.S. credits to satisfy a core area requirement if any of the following conditions is met: (1) The undergraduate course under consideration, either used to earn 2 or 3 graduate credits, must appear in one of the tables above, and the corresponding graduate course must satisfy the core area requirement. (2) The undergraduate course or independent study/project work is not in the tables listed above but it is deemed to satisfy the core area. This requires submitting a petition along with a detailed course description and syllabus to the Data Science Program for final decision.