
edXLinear algebra underpins everything from machine learning to structural engineering. This course builds your toolkit from the ground up—starting with how to solve systems of equations, then progressing through the abstractions that make advanced applications possible.
You'll develop a working understanding of how matrices transform space, how eigenvalues reveal hidden structure, and how decompositions like SVD simplify complex calculations. The skills are practical: engineers use these concepts daily to optimize networks, compress data, and model real-world phenomena.
By the end, you'll recognize linear patterns everywhere—and know exactly how to manipulate them.
Analyze and solve linear systems of equations. ,Work with linear subspaces. ,Use orthogonality in the analysis of linear systems and linear subspaces and calculate projections. ,Matrix Algebra: calculate products, inverses and inverses of matrices. ,Work with linear transformations. ,Calculate eigenvalues, eigenvectors and eigenspaces of matrices. ,Find diagonalizations and singular value decompositions of matrices, and use those to simplify matrix calculations.
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