Students will take a total of eight courses to satisfy the degree requirements. To ensure breadth, students are expected to take at least two courses in an engineering or natural science focus area of choice (e.g., mechanics of solids, materials science, etc.), at least two courses in applied mathematics and at least two courses in data science/high performance computing. The remaining two courses may be taken in engineering, applied mathematics, data science or other relevant disciplines.
Students should choose courses in consultation with their advisor to develop a coherent program. The proposed program of study must be approved by the academic director of data-enabled computational engineering and science master’s program in the School of Engineering.
Thesis
Students choose this option if they are interested in pursuing a Ph.D. They must complete a coherent plan of study based in data-enabled computational engineering and science consisting of eight graduate or advanced level courses and an acceptable thesis, which is normally sponsored by a member of the Engineering or APMA faculty.
Students are expected to complete the thesis option in three or four semesters. In the three-semester format, the students are expected to take three courses in the first semester, three in the second semester and two in the third semester. However, in the second and third semesters, the students may sign up for a “Special Topics: Reading Research and Design” type class (i.e., ENGN 2980 or equivalent in APMA) to satisfy the eight-course requirement.
In the four-semester model, students are expected to take three courses in the first semester, two in the second semester, two in the third semester and one in the fourth semester. In both cases, the “Special Topics: Reading Research and Design” course may be counted up to two times toward the degree.
Non-Thesis
Students choose this option if they want a degree to help achieve their personal or professional goals. They must complete a coherent plan of study based in data-enabled computational engineering and science consisting of eight graduate or advanced level courses.
Students are expected to complete the non-thesis option in three semesters, taking three courses in the first and second semesters, and two courses in the third semester (i.e., the 3-3-2 model).
One-year completion is also possible with students taking four courses in the first semester and four courses in the second (i.e., the 4-4 model). The maximum duration students may take to complete will be four semesters.
Professional
Students choose this option if they are focused on their professional goal of obtaining a position that applies data-enabled computational engineering and science in national laboratories or industries. They must complete a coherent plan of study based in data-enabled computational engineering and science consisting of eight graduate or advanced level courses. In addition to the course requirements, a paid or unpaid internship is a required component. Assistance in obtaining internships will be provided by the School of Engineering and the Center for Master’s Student Excellence.
Students are expected to complete the professional option in three semesters, taking three courses in the first and second semesters, and two courses in the third semester (i.e., the 3-3-2 model). The maximum duration students may take to complete will be four semesters (i.e., the 2-2-2-2 model).
A paid or unpaid experiential learning experience of three to six months is a required component. Experiential learning can include one of the following (but not both):
- A summer internship directly related to the program of study
- Completion of ENGN 2960 (Experiential Learning in Industry (ELI)) as an elective course that counts towards the eight-course requirement. Note: students enrolled in ENGN 2960 are considered full-time students and may be counted only one time toward the degree.