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MECH 203 Mathematical and Computational Tools for Mechanical Engineers II Units: 3.50
This course will introduce numerical and statistical methods for the solution of engineering problems, to complement those discussed in MECH 202. The topics of the course will be presented through problems, models and applications relevant to the Mechanical Engineering Program. On completion of the course students will be able to: solve linear systems of equations; analyze random processes; perform local optimization and hypothesis testing; interpolate and fit discrete data sequences. Students will solve problems analytically and computationally in an active learning, tutorial environment. The course will include a design project.
K3.5(Lec: Yes, Lab: No, Tut: Yes)
K3.5(Lec: Yes, Lab: No, Tut: Yes)
Offering Term: W
CEAB Units:
Mathematics 31
Natural Sciences 0
Complementary Studies 0
Engineering Science 0
Engineering Design 11
Offering Faculty: Smith Engineering
Course Learning Outcomes:
- Solve systems of linear equation analytically and numerically with Python.
- Explain random processes, including Gaussian, Poisson and binomial.
- Analyze random processes, including Gaussian, Poisson and binomial.
- Apply various interpolation and fitting methods using Python and discuss numerical errors.
- Explain local optimization algorithms.
- Apply local optimization methods, coding in Python.
- Perform a one-independent-variable hypothesis test.