# Applied Linear Algebra

Universitat Politècnica de València

## Course Description

• ### Course Name

Applied Linear Algebra

• ### Host University

Universitat Politècnica de València

• ### Location

Valencia, Spain

Mathematics

• ### Language Level

Taught In English

### Hours & Credits

• Credits

3
• Recommended U.S. Semester Credits
0
• Recommended U.S. Quarter Units
0
• ### Overview

Linear Algebra

3 Credits | 300 Level | 38 Contact hours

REQUIRED TEXTBOOKS AND COURSE MATERIALS

This course will cover chapters 1-6 (omitting some sections) of the course text Linear Algebra and its Applications by Gilbert Strang, 4th edition (Publisher: Brooks/Cole Cengage Learning).
Acquisition of a physical copy of the text is highly recommended since we will follow it closely.

DESCRIPTION

It is an introductory course emphasizing techniques of linear algebra with applications to engineering; topics include matrix operations, determinants, linear equations, vector spaces, linear transformations, eigenvalues, and eigenvectors, inner products, norms and orthogonality.

Linear Algebra might be consider as a mathematical toolkit for analyzing data and geometry. In virtually every area of human endeavor, data and geometry are or can be used to further understanding and to assist in making predictions. Indeed, Linear Algebra is behind
the majority of technical and scientific discoveries.

LEARNING GOALS

• Demonstrate an understanding of matrices and gaussian elimination, vector spaces, orthogonality, determinants, eigenvalues and eigenvectors, and positive definite matrices.
• Apply numerical, computational, and estimation techniques.
• Use matrices to model and analyze physical phenomena.
• Explain and use the tools to formulate and solve problems in mathematical situations and connect concepts covered to other disciplines.
• Communicate ideas through descriptive language, as well as through mathematical symbols.

OUTLINE

Chapter 1: Matrices and Gaussian Elimination.
Chapter 2: Vector Spaces.
Chapter 3: Orthogonality.
Chapter 4: Determinants.
Chapter 5: Eigenvalues and Eigenvectors.
Chapter 6: Positive Definite Matrices.

PoliformaT homework: 20 %
Quizzes: 5%
Classwork: 10 %
Midterm Exam 1: 25 %
Final Examination: 40 %

### Course Disclaimer

Courses and course hours of instruction are subject to change.

Eligibility for courses may be subject to a placement exam and/or pre-requisites.

Credits earned vary according to the policies of the students' home institutions. According to ISA policy and possible visa requirements, students must maintain full-time enrollment status, as determined by their home institutions, for the duration of the program.

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