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Applied Vectors and Matrices

QAC 220
Spring 2024
Section: 01  
Course Cluster and Certificates: Applied Data Science Certificate

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.
Credit: 1 Gen Ed Area Dept: SBS QAC
Course Format: Lecture / DiscussionGrading Mode: Graded
Level: UGRD Prerequisites: MATH121
Fulfills a Major Requirement for: (CADS)(DATA-MN)(PSYC)
Past Enrollment Probability: 50% - 74%

Last Updated on JUN-13-2024
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