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I am new to data science, taken a sabbatical and want to spend next few months in learning the basics of statistics, algebra and programming. While looking up the resources i came across Linear algebra and computations linear algebra which got me confused. Can someone please tell me being an amateur should i take up a course in linear algebra or computational algebra

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    @Raghav: Asking for personal advice ("should i take up a course in linear algebra or computational algebra?") is explicit grounds for closure on this site. On the other hand, the title question ("What is the difference between computational linear algebra and linear algebra?") is both on-topic and worthwhile. Please consider rewording your question, even something as simple as replacing the final sentence with, "I'm trying to decide whether to take up a course in linear algebra or computational algebra. Can someone please explain the differences between these fields?" Thank you. – 2017-01-10

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Computational linear algebra is concerned with numerical algorithms for solving linear algebra problems (large systems of linear equations, calculating matrix eigenvalues, eigenvectors, ...) on computers. While this is obviously useful in data science, I would not attempt a course in computational linear algebra before a linear algebra course; the latter constitutes a prerequisite for the former. You can not, after all, discuss efficient algorithms for calculation of singular value decomposition of a matrix if you don't know what it is, or some of it's properties.