Linear Algebra with Computer Science Applications | BS in Applied Computer Science

Course Details

*Note: This course description is only applicable to the Computer Science Post-Baccalaureate program. Additionally, students must always refer to the 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

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.

Specific Outcomes of Instruction

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

Brief List of Topics to be Covered

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

Mathematical Concepts Used

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

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CSPB 2820 – Linear Algebra with Computer Science Applications

Course Details

Brief Description of Course Content

Specific Goals