QAC 220
Spring 2024
| Section:
01
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| 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. |
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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: (CADS)(DATA-MN)(PSYC) |
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Past Enrollment Probability: 50% - 74% |
| SECTION 01 | | Special Attributes: CQC |
| Instructor(s): Oleinikov,Pavel V Times: .M.W... 10:50AM-12:10PM; Location: OLIN014; |
| Total Enrollment Limit: 18 | | SR major: 0 | JR major: 0 | | |
| Seats Available: -13 | GRAD: X | SR non-major: 6 | JR non-major: 6 | SO: 6 | FR: X |
| Drop/Add Enrollment Requests | | | | | |
| Total Submitted Requests: 1 | 1st Ranked: 0 | 2nd Ranked: 0 | 3rd Ranked: 0 | 4th Ranked: 0 | Unranked: 1 |
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