Syllabus

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: 06.09.2022 - 19.10.2022

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

Substitutes for Courses

• valid for whole curriculum period:

  Substitutes for Courses

Prerequisites

• valid for whole curriculum period:

  Prerequisites

FURTHER INFORMATION

Further Information

• valid for whole curriculum period:

  Teaching Language : English

  Teaching Period : 2022-2023 Autumn I
  2023-2024 Autumn I

  Enrollment :

  Sisu (sisu.aalto.fi)

Description