Please note! Course description is confirmed for two academic years (1.8.2018-31.7.2020), which means that in general, e.g. Learning outcomes, assessment methods and key content stays unchanged. However, via course syllabus, it is possible to specify or change the course execution in each realization of the course, such as how the contact sessions are organized, assessment methods weighted or materials used.
Students learn to analyze and solve problems in linear algebra that occur often in scientific computing, data fitting and optimization. The main focus is on solution of linear systems, least squares problems and eigenvalue problems. After the course, the students can choose the best solution method for each problem and have a good understanding on issues related to numerical stability of the applied algorithms.
Schedule: 08.09.2020 - 21.10.2020
Teacher in charge (valid 01.08.2020-31.07.2022): Antti Hannukainen
Teacher in charge (applies in this implementation): Antti Hannukainen
Contact information for the course (applies in this implementation):
CEFR level (applies in this implementation):
Language of instruction and studies (valid 01.08.2020-31.07.2022):
Teaching language: English
Languages of study attainment: English
CONTENT, ASSESSMENT AND WORKLOAD
Matrix decompositions and their numerical computation, eigenvalue iterations, sparse matrices, iterative solution of linear systems.
Assessment Methods and Criteria
Teaching methods: lectures, exercises and exam
Assessment methods: exercises and an exam
contact hours 36h (no compulsory attendance)
self-study ca 100h
All essential material is included in the lecture notes that are available at the course's homepage.
Substitutes for Courses
MS-A00XX, MS-A01XX, MS-A02XX, MS-C134X. The courses MS-A03XX and MS-C1540 may also be useful.