Who is this class for: This class is aimed at the beginning graduate student, or the well-prepared undergraduate in engineering, mathematics or the physical sciences. A working knowledge of linear algebra (matrix-vector manipulations) is needed. Some exposure to partial differential equations would be very helpful. Experience with programming is a must. This could be Matlab or a language such as Fortran, C or Python.

Created by:  University of Michigan

  • Krishna Garikipati, Ph.D.

    Taught by:  Krishna Garikipati, Ph.D., Professor of Mechanical Engineering, College of Engineering - Professor of Mathematics, College of Literature, Science and the Arts

CommitmentYou should expect to watch about 3 hours of video lectures a week. Apart from the lectures, expect to put in between 3 and 5 hours a week.
Hardware ReqIt would be ideal if you have your own notebook/desktop computer to install the open-access code.
How To PassPass all graded assignments to complete the course.
User Ratings
4.6 stars
Average User Rating 4.6See what learners said

How It Works

Each course is like an interactive textbook, featuring pre-recorded videos, quizzes and projects.

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University of Michigan
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Ratings and Reviews
Rated 4.6 out of 5 of 56 ratings


Need to invest a great deal of time to understand thoroughly.

A must take course if you intend to one day tackle real world finite element based Physics simulations.

There are finite element method software packages that lead us to believe that we don't need to understand the finite element method (FEM) in order to make physics simulations.

That is true if you just want to study simple academic problems. However if you want to simulate the real world you need to understand the basics of the FEM. This course will provide you with these basic tools.

Instructions (in lecture and coding assignment) are clear and easy to follow. Contents of the lectures are somewhat repetitive, but I think it's OK because it allows you to go over previous materials just by watching the lecture and taking notes. Talking about potential improvement, I think it would be nice to give some more explanations to certain details, such as how the connectivity matrix is constructed.

good for learning.