Introduction to Computational Science and Engineering (edX)

CSE.0002x will teach you how to use to solve problems in engineering and science including simulation of time-dependent phenomena; optimization of systems; and quantification of uncertainty. This course is primarily for learners with some prior programming experience in Python and an introductory knowledge of calculus and mechanics (typical of a first-year college course in these topics). You will spend a considerable amount of time writing programs to implement the concepts covered in the course. For example, you will write programs that will: simulate the descent of a lander in the Martian atmosphere; optimize the placement of cellular towers on the MIT campus; and quantify the likelihood of significant climate temperature rise under different scenarios.

Topics covered include:

- Advanced programming in Python 3 and NumPy

- Plotting with Matplotlib

- Initial value problems

- Discretization with explicit and implicit methods

- Solution of linear and nonlinear systems of equations

- Unconstrained optimization and gradient descent

- Probability, distributions

- Monte Carlo simulations

What you'll learn

- Python 3, NumPy, and Matplotlib

- Numerical methods to solve initial value problems

- Solution of linear and nonlinear systems of equations

- Unconstrained optimization and gradient descent

- Monte Carlo simulations

Prerequisites:

- 6.00.1x- Introduction to Computer Science and Programming Using Python Introduction to computer science or equivalent

- Some prior programming experience in Python

- Introductory knowledge of calculus and mechanics (typical of a first-year college course in these topics)