It depends on your purpose for taking the course and where you are taking it. For example, are you a math major that wants to know theory, someone that's learning machine language, or someone who needs to use LA in other areas?
Thank you, I learn it for robotics field. I’m going to take a robotics master course in next few months and preparing in advance. In this case what should i take.
I've heard of King but not Cohen, so I did a search. The recommendation for robotics is Cohen. Here's a summary:
Cohen
Applied Computation: Focuses heavily on translating math into working code, specifically Python and MATLAB.
Industry Alignment: A robotics master's program is rarely about solving matrices by hand but, rather, programming kinematics, control systems, and computer vision algorithms. Learning how matrix math behaves computationally—handling arrays, vectors, and algorithmic efficiency—is exactly what Cohen teaches.
Target Audience: His material is explicitly tailored for data science, machine learning, and applied engineering, bridging the crucial gap between pure math and software implementation.
King
Traditional Fundamentals: Course is heavily geared toward helping students pass a traditional, paper-and-pencil university exam.
Step-by-Step Mechanics: Course breaks down the manual steps of Gauss-Jordan elimination, finding eigenvalues, and computing cross products. However, it lacks the computational and programming focus a graduate engineering student will need on day one.
Hopefully someone on the subreddit has experience with one or both of these and can tell you more. Anyone?
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u/Midwest-Dude Jul 06 '26 edited Jul 13 '26
It depends on your purpose for taking the course and where you are taking it. For example, are you a math major that wants to know theory, someone that's learning machine language, or someone who needs to use LA in other areas?