Master’s in Data-Enabled Computational Engineering and Science

Program and Schedule

A modern computational engineering scientist must be educated in applied mathematics, understand the foundations of data science, be comfortable with programming and carrying out parallel computations, and have deep expertise in one or more engineering areas.

Program and Schedule

Program of study

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 engineering, at least two courses in applied mathematics, and at least two courses in data science/high performance computing. This leaves two more courses to be taken to satisfy the program requirements, and, to ensure depth, these may be taken in engineering, applied mathematics, data science, or other relevant disciplines.

Master of Science – Non-Thesis Option

Students are expected to complete the Master of Science – Non-Thesis program 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.

Master of Science – Thesis Option

Students are expected to complete the Master of Science – Thesis program 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 “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 “Reading Research and Design” course may be counted up to two times toward the degree.

Sample Course Plans

Courses could be scheduled according to the following sample plans.

The following example schedule, which will have the student graduate in three semesters, applies to incoming students with sufficient preparation in applied mathematics:

	Fall	Spring
Year 1	ENGN2210 - Continuum Mechanics ENGN2340 - Computational Methods in Structural Mechanics APMA2550 - Numerical Solution of PDEs I	ENGN2220 - Mechanics of Solids APMA2560 - Numerical Solution of PDEs II APMA2822B - Introduction to Parallel Computing on Heterogeneous (CPU+GPU) Systems
Year 2	ENGN2520 - Pattern Recognition and Machine Learning APMA2630 - Theory of Probability I

The following example schedule, which will have the student graduate in three semesters, applies to incoming students with sufficient preparation in applied mathematics:

	Fall	Spring
Year 1	ENGN2210 - Continuum Mechanics, ENGN2810 - Fluid Mechanics I APMA2550 - Numerical Solution of PDEs I	ENGN2020 - Math Methods in Engineering and Physics II ENGN2820 - Fluid Mechanics II APMA2560- Numerical Solution of PDEs II
Year 2	ENGN2520 - Pattern Recognition and Machine Learning APMA2580A/C - Computational Fluid Dynamics/Optimization

The following example schedule, which will have the student graduate in three semesters, applies to incoming students with sufficient preparation in applied mathematics:

	Fall	Spring
Year 1	ENGN2210 - Continuum Mechanics ENGN2410 - Thermodynamics of Materials APMA2550 - Numerical Solution of PDEs I	ENGN2020 - Math Methods in Engineering and Physics II ENGN2930 - Atomistic Modeling of Materials APMA2560 - Numerical Solution of PDEs II
Year 2	ENGN2520 - Pattern Recognition and Machine Learning APMA2630 - Theory of Probability I

If a student feels more preparation might be needed before moving into the advanced courses, especially in the areas of Applied and Computational Mathematics, a recommended schedule of courses to complete the DECES degree in three semesters may look like:

	Fall	Spring
Year 1	ENGN1750 - Advanced Mechanics of Solids APMA1690 - Computational Probability and Statistics ENGN2210 - Continuum Mechanics	ENGN2020 - Math Methods in Engineering and Physics II ENGN2220 - Mechanics of Solids APMA2822B - Introduction to Parallel Computing on Heterogeneous (CPU+GPU) Systems
Year 2	ENGN2520 - Pattern Recognition and Machine Learning APMA2550 - Numerical Solution of PDEs I