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Build an intermediate understanding of linear algebra while learning to represent and manipulate vectors and matrices with NumPy. You will examine their essential properties and use the numpy.linalg library to perform common computations.
Practice vector and matrix operations, including addition, subtraction, and multiplication. You will also work with systems of equations and matrix transformations to connect mathematical concepts with computational techniques.
Explore eigenvalues, eigenvectors, and matrix diagonalization through practical exercises. This path is designed for learners who want to apply linear algebra in areas such as data science and machine learning.
