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This course is intended for anyone with an interest in linear algebra. No prerequisites are needed.

The goal of the present course is you to get some intuition about it.

All along we’ll discuss linear equations, matrices, vectors, matrix elimination, linear dependence, determinants, bases, linear transformations, eigenvectors and eigenvalues and diagonalization.

Linear algebra has numerous applications in practical areas including chemistry, quantum physics, video games, finance, architecture, meteorology, image processing, animation movies, operational research, search engine, algorithmics, machine learning, etc.

Albert Einstein on blackboard

Figure 0.1 : A. Einstein using linear algebra (tensor) (© credits: Bettmann / CORBIS)