Outstanding undergraduate students can earn a bachelor’s degree and master’s degree concurrently, and in less time than would typically be required to earn each degree separately by allowing up to 12 graduate credits to be counted towards both degree requirements. Undergraduate students can pursue a 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 as the master’s AI degree. Students enrolled in this joint Bachelor's/Master's program must satisfy all the program requirements of their respective bachelor's degree and all the program requirements of the master's AI degree.
In consultation with their academic advisor, the student prepares a Plan of Study outlining the selections chosen to satisfy the Bachelor's/Master's program degree requirements, including the courses that will be double-counted. This Plan of Study must then be approved by the AI program.
Admissions Requirements
Any WPI undergraduate student may apply to the Bachelor's/Master's program in Artificial Intelligence. Students are encouraged to apply by their junior year so they can plan their 4000level courses strategically and take advantage of the option to double-count credits toward both the bachelor's and master's degrees.
Applicants should have a quantitative and computational background including some coursework in programming, linear algebra and statistics, with a grade of B or better. Students in Artificial Intelligence, Computer Science, Data Science, Mathematics, Statistics, Electrical Engineering, Robotics Engineering, Information Technology, Business Analytics, Quantitative Sciences or other related fields are adequately prepared. Students from other backgrounds are welcome to apply if they can demonstrate their readiness through other means, such as coursework, or relevant project experience. Non-matriculated students may enroll in up to two courses prior to applying for admission to Bachelor's/Master's program in Artificial Intelligence.
Double Counting Rules
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 (equivalent of 12 graduate credits) required for the master’s AI degree, and that meet all other requirements for each degree. These courses can include graduate courses as well as undergraduate 4000-level courses as long as (1) the undergraduate course covers similar material as a graduate course, (2) this corresponding graduate course satisfies the master’s AI degree program, and (3) the academic unit offering the graduate course also allows this corresponding undergraduate course to be used for BS/MS credit to satisfy this graduate course.
4000-Level Courses and Projects that can be Double-Counted
For the relevant 4000-level courses (listed below), two graduate credits will be earned towards the joint Bachelor's/Master'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 21 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 and Data Science |
|---|
| CS 4341 Introduction to Artificial Intelligence |
| CS 4342 Machine Learning |
| CS 4343 / DS 4343 Deep Learning |
| CS 4344 / DS 4344 Natural Language Processing: From Foundations to Large Language Models |
| CS 4345 / DS 4345 Multi-Agent Systems |
| CS 4432 Database Systems II |
| CS 4433/DS 4433 Big Data Management and Analytics |
| CS 4445 Data Mining and Knowledge Discovery in Databases |
| Courses from Robotics Engineering |
|---|
| RBE 4601 Human Factors and Human-Robot Interface |
| RBE 4701 Artificial Intelligence for Robotics |
| Courses from Mathematical Sciences and Data Science |
|---|
| DS 4635/MA 4635 Data Analytics and Statistical Learning |
Other 4000-level courses not listed above and 4000-level independent study courses may be approved for double-counting for the Bachelor's/Master's AI degree only through a petition and approval from the AI Program Committee.
Graduate Courses that can be Double-Counted
A student in the Bachelor's/Master’s Program in AI can double-count any of the graduate courses listed as electives (including AI specialization electives) in the AI Master's Degree description in the WPI Graduate Catalog if the course also satisfies a requirement of the student's Bachelor'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 master’s degree for at most one of the two courses in any row of the tables.
| Courses from Computer Science and Data Science | |
|---|---|
| Undergraduate Courses | Graduate Courses |
| 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 4433/DS 4433 Big Data Management and Analytics | CS 585 / DS503 Big Data Management |
| CS 4445 Data Mining and Knowledge Discovery in Databases | CS 548 Knowledge Discovery and Data Mining |
| CS 4343 / DS 4343 Deep Learning | CS 541 / DS 541 Deep Learning |
| CS 4344 / DS 4344 Natural Language Processing: From Foundations to Large Language Models | CS 554 / DS 554 Natural Language Processing |
| Courses from Robotics Engineering | |
|---|---|
| Undergraduate Courses | Graduate Courses |
| RBE 4601 Human Factors and Human-Robot Interface | RBE 526 Human-Robot Interaction |
| RBE 4701 Artificial Intelligence for Robotics | CS 534 Introduction to Artifical Intelligence |
| Courses from Mathematical Sciences and Data Science | |
|---|---|
| Undergraduate Courses | Graduate Courses |
| DS 4635/MA 4635 Data Analytics and Statistical Learning | MA 543/DS502 Statistical Methods for Data Science |
Satisfying Master’s AI Bin Requirements in the Bachelor's/Master's Program
A Bachelor's/Master's student may use up to 1/3 unit of undergraduate credit taken for Bachelor's/Master's credit to satisfy a bin requirement in the master’s AI program, if the following conditions hold: (1) the undergraduate course covers material similar to that of a graduate course, (2) this corresponding graduate course falls into one of the five core bins of the master’s AI program, and (3) the academic unit offering the graduate course allows this corresponding undergraduate course to be used for BS/MS credit to satisfy this graduate course