LEARNING OUTCOMES
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 sparse linear systems. 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.
Credits: 5
Schedule: 03.09.2024 - 16.10.2024
Teacher in charge (valid for whole curriculum period):
Teacher in charge (applies in this implementation): Antti Hannukainen
Contact information for the course (applies in this implementation):
CEFR level (valid for whole curriculum period):
Language of instruction and studies (applies in this implementation):
Teaching language: English. Languages of study attainment: English
CONTENT, ASSESSMENT AND WORKLOAD
Content
valid for whole curriculum period:
Matrix decompositions of sparse matrices and their numerical computation, eigenvalue iterations, iterative solution of linear systems.
Assessment Methods and Criteria
valid for whole curriculum period:
Teaching methods: lectures, exercises and exam
Assessment methods: exercises and an exam
Workload
valid for whole curriculum period:
contact hours 36h (no compulsory attendance)
self-study ca 100h
DETAILS
Study Material
valid for whole curriculum period:
All essential material is included in the lecture notes that are available at the course's homepage.
Substitutes for Courses
valid for whole curriculum period:
Prerequisites
valid for whole curriculum period:
FURTHER INFORMATION
Further Information
valid for whole curriculum period:
Teaching Language: English
Teaching Period: 2024-2025 Autumn I
2025-2026 Autumn I