autumn 2018

SMN6190 Linear Algebra 2 - 5 stp

Sist endret: 08.02.2019

The course is administrated by

Faculty of Engineering Science and Technology

Studiested

Narvik | Nettbasert | Annet |

Application deadline

Applicants from Nordic countries:1 June for the autumn semester and 1 December for the spring semester. Exchange students and Fulbright students: 1 October for the spring semester and 15 April for the autumn semester.

Type of course

The course may be taken as a singular subject.

Admission requirements

A relevant undergraduate bachelor Engineering programme with minimum 30 credits mathematics/statistics topics

Application code: 9371

Course contents

  • Particular and general vector spaces
  • Basis and subspaces
  • Inner product spaces
  • The Gram-Schmidt process
  • Least-squares problems
  • Extension of the theory of eigenvalues and eigenvectors
  • Diagonalization with generalizations
  • Singular value decompositions
  • Linear transformations with matrix representation

Recommended prerequisites

IGR1600 Mathematics 1, IGR1601 Mathematics 2, IGR1613 Mathematics 3 / Physics 2

Objective of the course

Knowledge (K):

After completing the linear algebra course the candidate:

  • Has advanced knowledge of concepts within linear algebra.
  • Has thorough knowledge of central theories and methodologies within the listed concepts in linear algebra and know how to apply these in mathematical problems.
  • Can analyse formulated linear algebra problems and identify methods to solve these.

Skills (S):

After completing the linear algebra course the candidate:

  • Can recognize and identify linear problems and formulate them in terms of linear systems.
  • Can analyse and deal critically with theories in linear algebra and use these to structure and formulate scholarly arguments.
  • Can utilise existing interpretations and relevant methods within the field to accomplish a task.
  • Can use relevant methods within the field.

General competence (GC):

After completing the linear algebra course the candidate:

  • Can analyse relevant linear problems.
  • Can apply the knowledge and skills within linear algebra to carry out assignments.
  • Can communicate about different aspects in linear algebra, particularly explaining in mathematical terms how to deal with mathematical tasks.
  • Can use the knowledge for concepts, theories and methods in linear algebra in other engineering areas.

Teaching and Learning Methods: The course is taught intensively during two non-consecutive weeks, in which a combination of lectures followed by task solving sessions and flipped classroom arrangements are used. All lectures are streamed and recorded. Videos provided in flipped classroom arrangements are made available to all students attending the course.

Workload: Two distributed assignments are to be completed. An obligatory questionnaire must be completed, in which students are encouraged to reflect on their learning goals in the course. Form of assessment: A final summative exam. Selected solutions from the exam will be graded externally.

Language of instruction

English

Teaching methods

Lectures and task solution sessions. Video lectures.

Two distributed assignments to be completed.

Final, summative exam.

Assessment

A final exam which is a 4 hours written exam. Scale of grades: A-F in which F means fail A re-sit exam will be arranged for this course

Date for examination

Written examination 12.10.2018

The date for the exam can be changed. The final date will be announced in the StudentWeb early in May and early in November.

Schedule

Recommended reading/syllabus

David Lay: Linear Algebra and Its Applications, latest edition. Selected additional literature from textbooks: - G. Strang: Linear algebra and its applications - H. Anton: Elementary linear algebra Compendia: 'Linear systems, matrices and determinants', 'Real eigenvalues and eigenvectors Lecture notes, recorded lectures, provided videos and task solutions

Additional literature

G. Strang: Linear algebra and its applications

H. Anton: Elementary linear algebra

E. Kreyszig: Advanced engineering mathematics.