CSPB 2820 – Linear Algebra with Computer Science Applications

*Note: This course discription is only applicable to the Computer Science Post-Baccalaureate program. Additionally, students must always refer to course syllabus for the most up to date information. ​

  • Credit Hours: 3.0
  • Prerequisites: CSPB or CSCI 2824 Discrete Structures with a minimum passing grade of C-
  • Minimum Passing Grade: C-
  • Textbooks: Introduction to Applied Linear Algebra, Boyd & Vandenberghe

[video:https://www.youtube.com/watch?v=lnfBTT8Nv0E]

Brief Description of Course Content

Introduces the fundamentals of linear algebra in the context of computer science applications. Includes vector spaces, matrices, linear systems, and eigenvalues. Includes the basics of floating point computation and numerical linear algebra.

Specific Goals

By the end of this course, students should be well positioned to apply linear algebra skills in a computer science context.

 
  • Use and reason about vectors, theoretically and in computer science applications
  • Use and reason about matrices, theoretically and in computer science applications
  • Understand and apply linear functions, and the relation between linear functions and matrices
  • Solve systems of linear equations, and reason about the computational complexity of them

● Vectors

● Linear functions

● Norm and distance

● Writing linear algebra code

● Clustering

● Linear independence

● Matrices

● Matrix examples

● Linear equations

● Linear dynamical systems

● Matrix multiplication

● Matrix inverses

● Least squares

● eigenvalues, eigenvectors, and singular values

● Least squares data fitting

● Least squares classification

Algebra, including solving equations, proofs, real numbers, inequalities, and functions, linear algebra, as described above

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