Undergraduate Course: Numerical Linear Algebra (MATH10098)
Course Outline
School  School of Mathematics 
College  College of Science and Engineering 
Credit level (Normal year taken)  SCQF Level 10 (Year 3 Undergraduate) 
Availability  Available to all students 
SCQF Credits  10 
ECTS Credits  5 
Summary  Driven by the needs of applications, this course studies reliable and computationally efficient numerical techniques for practical linear algebra problems. As well as traditional theoretical assessment
of the algorithms studied, an advanced programming language is used to perform practical experiments to complement students insight into the subject. 
Course description 
Linear Algebra is one of the most widely used topics in the mathematical sciences. At level 8 or 9 students are taught standard techniques for basic linear algebra tasks including the solution of linear systems, finding eigenvalues/eigenvectors and orthogonalisation of bases. However, these techniques are usually computationally too intensive to be used for the large matrices encountered in practical applications. This course will introduce students to these practical issues, and will present, analyse, and apply algorithms for these tasks which are reliable and computationally efficient. The course includes significant lab work using an advanced programming language. The course studies three main topics: the solution of linear systems of equations, the solution of least squares problems and finding the eigenvectors and/or eigenvalues of a matrix.

Information for Visiting Students
Prerequisites  Visiting students are advised to check that they have studied the material covered in the syllabus of any prerequisite course listed above before enrolling. 
High Demand Course? 
Yes 
Course Delivery Information

Academic year 2022/23, Available to all students (SV1)

Quota: None 
Course Start 
Semester 1 
Timetable 
Timetable 
Learning and Teaching activities (Further Info) 
Total Hours:
100
(
Lecture Hours 18,
Seminar/Tutorial Hours 5,
Supervised Practical/Workshop/Studio Hours 12,
Summative Assessment Hours 1.5,
Programme Level Learning and Teaching Hours 2,
Directed Learning and Independent Learning Hours
61 )

Assessment (Further Info) 
Written Exam
50 %,
Coursework
50 %,
Practical Exam
0 %

Additional Information (Assessment) 
Coursework 50%, Examination 50% 
Feedback 
Not entered 
Exam Information 
Exam Diet 
Paper Name 
Hours & Minutes 

Main Exam Diet S1 (December)   2:00  
Learning Outcomes
On completion of this course, the student will be able to:
 Use the algorithms presented in the course to solve linear systems of equations, solve least squares problems and find eigenvalues and eigenvectors of a matrix, and choose an appropriate method for a given problem.
 Develop methods to solve numerical linear algebra problems using the tools presented in the course.
 Analyse the computational cost of an algorithm and discuss its computational efficiency.
 Discuss the accuracy of computed solutions in reference to matrix conditioning, floating point arithmetic and convergence of iterative methods.
 Perform scientific investigation of an algorithm by implementing it and performing experiments in Python.

Reading List
Numerical Linear Algebra and Applications, Second Edition", by B. N. Datta, SIAM, ISBN: 9780898716856
Numerical Linear Algebra by Lloyd "Nick" Trefethen and David Bau III, SIAM, ISBN: 9780898713619
Applied numerical linear algebra by James "Jim" Demmel, SIAM, ISBN: 9780898713893 
Additional Information
Graduate Attributes and Skills 
Not entered 
Keywords  NLA 
Contacts
Course organiser  Dr Aretha Teckentrup
Tel: (0131 6)50 5776
Email: A.Teckentrup@ed.ac.uk 
Course secretary  Miss Greta Mazelyte
Tel:
Email: greta.mazelyte@ed.ac.uk 

