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Introduction to Matrix Methods | Stanford University

Stanford University

Explore the fundamentals of vectors, matrices, and their practical applications in fields like engineering, data science, and finance with this comprehensive course from Stanford University.

University CoursesJuliaMachine Learning

Introduction

ENGR108 covers the basics of vectors and matrices, solving linear equations, least-squares methods, and many applications. The focus will be on using matrix methods in applications such as tomography, image processing, data fitting, time series prediction, finance, and many others. Students will use the language Julia to do computations with vectors and matrices.

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Highlights

  • Covers the mathematics of matrices and vectors, with a focus on practical applications
  • Uses the programming language Julia for computations with vectors and matrices
  • Suitable for undergraduates with basic programming and math background

Recommendation

This course is recommended for any undergraduate interested in learning about matrix methods and their applications in fields like engineering, data science, and finance. No prior experience with linear algebra is required, as the course will develop the necessary concepts from scratch.

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