Checking date: 10/09/2025 21:33:16


Course: 2025/2026

Linear Algebra
(20123)
Bachelor in Applied Mathematics (Plan: 554 - Estudio: 507)


Coordinating teacher: MOLERA MOLERA, JUAN MANUEL

Department assigned to the subject: Mathematics Department

Type: Basic Core
ECTS Credits: 6.0 ECTS

Course:
Semester:




Objectives
The student is expected to know and understand the fundamental concepts of: - Systems of linear equations - Matrix and vector algebra - Vector spaces - Linear maps - Eigenvalues and eigenvectors - Jordan canonical form The student is expected to acquire and develop the ability to: - Discuss the existence and uniqueness of solutions of a system of linear equations - Solve a consistent system of linear equations - Carry out basic operations with vectors and matrices - Compute the LU factorization of a matrix - Determine whether a square matrix is invertible or not, and compute the inverse matrix if it exists - Determine whether a subset of a vector space is a subspace or not - Find bases of a vector subspace, and compute change-of-basis matrices - Compute eigenvalues and eigenvectors of a square matrix - Determine whether a square matrix is diagonalizable or not - Diagonalize a matrix - Compute the Jordan form of a matrix
Learning Outcomes
K1: To know the main techniques of mathematical proof, as well as to understand the importance and necessity of hypotheses in mathematical results. K2: Know the fundamental definitions and results of algebra, geometry and discrete mathematics, including both the statements and their proofs. S1: Learn and adapt mathematical techniques and methods from one branch to another (such as algebra, calculus or probability) and apply them to different scientific or industrial problems. S4: Use logical and abstract reasoning to state, demonstrate and verify the validity of mathematical results, as well as to analyze models and design solution strategies. C3: Use numerical or symbolic calculation, statistical analysis, or optimization software to approximate the solution of mathematical problems arising in a professional context and know how to analyze and predict behaviors in different contexts, implementing efficient solutions to complex problems.
Description of contents: programme
. Matrices and vectors . Systems of linear equations . LU factorization . Vector spaces . Linear maps . Eigenvalues and eigenvectors . Jordan canonical form
Learning activities and methodology
The teaching methodology will include: - Theoretical lectures in large groups, where knowledge that students should acquire will be presented. The course weekly schedule will be available to students and they are expected to prepare the classes in advance. - Resolution of exercises by the student, which will serve them as a self-assessment and to acquire the necessary skills - Problem classes, during which problems are discussed and solved - Tutorships
Assessment System
  • % end-of-term-examination/test 60
  • % of continuous assessment (assigments, laboratory, practicals...) 40

Calendar of Continuous assessment


Extraordinary call: regulations
Basic Bibliography
  • Stephan Ramon Garcia and Roger A. Horn. A Second Course in Linear Algebra. Cambridge. 2017
  • David C. Lay,. Linear Algebra and its Applications,. Addison Wesley.
  • Sergei Treil . Linear Algebra Done Wrong . Sergei Treil, https://www.math.brown.edu/streil/papers/LADW/LADW.html. 2017
  • Sheldon Jay Axler. Linear Algebra Done Right, Third Edition. Springer. 2015
  • W. Keith Nicholson. Linear Algebra with Applications. McGraw Hill. 2009 (6th edition)
Recursos electrónicosElectronic Resources *
Additional Bibliography
  • B. Noble and J. W. Daniel. Applied Linear Algebra. Prentice Hall.
Recursos electrónicosElectronic Resources *
(*) Access to some electronic resources may be restricted to members of the university community and require validation through Campus Global. If you try to connect from outside of the University you will need to set up a VPN


The course syllabus may change due academic events or other reasons.