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ABOUT THE COURSE:
This course develops linear algebra with a clear focus on computation and applications in computer science. We build from vector spaces, inner products, and orthogonality to projections, least-squares problems, eigenvalues, spectral decompositions, and singular value decomposition (SVD). Using these tools, we study data matrices, covariance, principal component analysis (PCA), linear regression, and Markov chains with applications such as PageRank. In the final module, we introduce complex vector spaces, quantum states, basic quantum gates, and simple quantum circuits to show how linear algebra underlies both modern machine learning and quantum computing. The course emphasizes conceptual understanding through worked examples and applications, providing a solid foundation for further study in ML, data science, and quantum information.
INTENDED AUDIENCE: B.Tech / M.Tech / M.Sc in CS
PREREQUISITES: Educational level: At least 1st year UG (or above) in CSE/IT/ECE/EE/Math.
Mathematical background: Basic calculus, high-school algebra.
INDUSTRY SUPPORT: Microsoft Research, Google, Meta, LinkedIn and start-ups working in data analytics and machine learning.
This course develops linear algebra with a clear focus on computation and applications in computer science. We build from vector spaces, inner products, and orthogonality to projections, least-squares problems, eigenvalues, spectral decompositions, and singular value decomposition (SVD). Using these tools, we study data matrices, covariance, principal component analysis (PCA), linear regression, and Markov chains with applications such as PageRank. In the final module, we introduce complex vector spaces, quantum states, basic quantum gates, and simple quantum circuits to show how linear algebra underlies both modern machine learning and quantum computing. The course emphasizes conceptual understanding through worked examples and applications, providing a solid foundation for further study in ML, data science, and quantum information.
INTENDED AUDIENCE: B.Tech / M.Tech / M.Sc in CS
PREREQUISITES: Educational level: At least 1st year UG (or above) in CSE/IT/ECE/EE/Math.
Mathematical background: Basic calculus, high-school algebra.
INDUSTRY SUPPORT: Microsoft Research, Google, Meta, LinkedIn and start-ups working in data analytics and machine learning.
