Python, Matrices, and Linear Algebra for Data Science and ML

Python, Matrices, and Linear Algebra for Data Science and Machine LearningCourse DescriptionThis course introduces students to essential concepts of linear algebra and python that are necessary as a foundation for learning concepts in data science and machine learning. The emphasis has been on creating lectures in a format that provides both geometrical intuitions and computational implementation of all the important concepts in linear algebra. Additionally, all the covered concepts are implemented and discussed in the python programming context.

The following topics will be covered:1. Introduction to Python2. Vector and Matrices in Data Science and Machine Learning3.

Vector and Matrices Operations4. Computing Eigenvalues5. Computing Singular Values6.

Matrix Operations in Machine Learning Algorithm7. Python Data Science and Machine Learning LibrariesWho this course is for:Students who want to learn linear algebra and python programming conceptsStudents who want to develop foundations in linear algebra for Data Science, Machine Learning, and Deep Learning domainsAnyone who is interested in learning python and wants to have a conceptual understanding of linear algebra concepts. Data scientists and machine learning students who want to review their basics in the linear algebra domainAnyone who wants to learn Python for data science, machine learning, and AI domainThis course is taught by professor Rahul Rai who joined the Department of Automotive Engineering in 2025 as Dean's Distinguished Professor in the Clemson University International Centre for Automotive Research (CU-ICAR).