此课程适用人群: 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.


制作方:   密歇根大学

  • Krishna Garikipati, Ph.D.

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

LevelIntermediate
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.
Language
English
How To PassPass all graded assignments to complete the course.
User Ratings
4.6 stars
Average User Rating 4.6See what learners said
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常见问题解答
运作方式
课程作业
课程作业

每门课程都像是一本互动的教科书,具有预先录制的视频、测验和项目。

来自同学的帮助
来自同学的帮助

与其他成千上万的学生相联系,对想法进行辩论,讨论课程材料,并寻求帮助来掌握概念。

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制作方
密歇根大学
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评分和审阅
已评分 4.6,总共 5 个 36 评分

This is a good intro course which introduce the Finite Element Method step by step, which suited me perfectly since I hardly coded in c++ nor did FEM before.

Nevertheless, as a graduate student, the pace is very slow, and the outline and motivation unclear, which would likely have discouraged me if I did not review video in x2, and stuck to second week lectures and onward.

I would advise to introduce more outline and motivation at the beginning of the week lecture to keep students motivated.

Apart from that, I recommand the course !

It is very well structured and Dr Krishna Garikipati helps me understand the course in very simple manner. I would like to thank coursera community for making this course available.

A rigorous and organized introduction to the subject with the additional benefit of learning through implementation.

This was a great course, I can only recommend. The tutor really explains basically all that there is to linear PDEs. What I miss, maybe as a different course is the case of nonlinear equations.