QAC 220
Spring 2026
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01
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An introduction to the mathematics of matrices and their application in traditional and modern methods of data analysis and scientific computing. The course promotes an interdisciplinary approach, and topics may include: - Coordinate transformations in data visualization, iterated patterns in mosaics and art - Use of least squares approach with linear solvers for regression, as well as image alignment - PCA-decomposition of computer images (the "eigenfaces" example) - Matrix decomposition methods: Singular Value Decomposition and Non-negative Matrix Factorization - Dimensionality reduction and data compression - Matrix operations in deep learning. - ChatGPT and word vector embeddings Students will use R for most of the computational tasks, and Mathematica for symbolic math and deep learning. |
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| Credit: 1 |
Gen Ed Area Dept:
SBS QAC |
| Course Format: Lecture / Discussion | Grading Mode: Graded |
| Level: UGRD |
Prerequisites: MATH121 |
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Fulfills a Requirement for: (Applied Data Science Certificate)(Data Analysis Minor)(Psychology) |
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Past Enrollment Probability: 50% - 74% |
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