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Stanford University

Advanced MATLAB for Scientific Computing

Stanford University via Stanford OpenEdx

This course may be unavailable.


The course is aimed for participants working or conducting research in scientific computing. Covered topics in scientific computing will include numerical linear algebra, numerical optimization, ODEs, and PDEs. Relevant applications areas include machine learning, electrical engineering, mechanical engineering, and aeroastro. There will be seven interactive based lectures with application based assignments to follow. Participants will be introduced to advanced MATLAB features, syntaxes, and toolboxes not traditionally found in introductory courses. Material will be reinforced with in-lecture examples, demos, and homework assignment involving topics from scientific computing. MATLAB topics will be drawn from: advanced graphics (2D/3D plotting, graphics handles, publication quality graphics, animation), MATLAB tools (debugger, profiler), code optimization (vectorization, memory management), object-oriented programming, compiled MATLAB (MEX files and MATLAB coder), interfacing with external programs, toolboxes (optimization, parallel computing, symbolic math, PDEs). Thanks to the support from MathWorks, a free MATLAB license is provided for participants taking the course.

Taught by

Danielle Maddix


5.0 rating, based on 2 Class Central reviews

Start your review of Advanced MATLAB for Scientific Computing

  • Profile image for David Chen
    David Chen
    I took the first iteration of this course on Stanford Online (laguinta/edX platform, which is no longer available). It consisted of 6 units, with the first being a refresher. The instructor was a Stanford doctoral candidate, who was incredibly knowledgeable about the subject and explained the concept very clearly. The course was very fast-paced; I found it challenging despite having taken a MATLAB-based course in graduate school in-person. However, the materials covered were thorough -- you get a deep delve into advanced application of MATLAB cell arrays, for example. I also appreciated the course covering some advanced topics on debugging that are critical to robust programming. Overall, I highly recommend this course.
  • Profile image for Selva Kumar
    Selva Kumar
    You must be fundamentally strong in Matlab to take this advanced course.

    All modules are explained clearly.

    Quiz is easy while the programming assignment is hard.

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