MA2501 Numerical Methods - Spring 2023


Date Message
26.08.2023 Exam 2 grading document + solutions
16.06.2023 Exam 1 grading document + solutions
20.04.2023 Dear students! The Faculty of Information Technology and Electrical Engineering (IE) is sending out a questionnaire-based student evaluation for courses taught at IE. Please help us to improve our teaching by answering this survey in the course MA2501 Numerical Methods
31.03.2023 The survey closes on May 5. (You answer anonymously, but need to log in with Feide for safety reasons.)
17.03.2023 Exercise set 3
12.03.2023 The exam will take place on Friday, May 26, 9:00-13:00.
03.03.2023 The second part of project has been made available in ovsys. The deadline is March 24, at 22:00. Your solutions should be uploaded to ovsys. The supervision sessions are on March 8 and March 15.
19.02.2023 Exercise set 2
03.02.2023 The first part of project has been made available in ovsys. The deadline for this project is Friday, February 24, 22:00. Your solutions should be uploaded to ovsys. You are allowed to work in groups. However, each student needs to submit solutions individually. The supervision sessions are on Wednesday, February 8, and on Wednesday, February 15.
20.01.2023 Exercise set 1
11.12.2022 First lecture: Wednesday, January 11, room EL4, 08:15 - 10:00.

General information

Official course description

Wednesdays, 8:15 - 10:00, room EL4 (Elektro B)
Thursdays, 12:15 - 14:00, room EL4

Exercise and project sessions:
Wednesday 14:15 - 16:00, room EL4


Textbook, other teaching material and old exams



Note on Newton methods for systems.

Note on ODEs

Note on BVPs

Note on Linear algebra part 1 and part 2.

Old exams

Curriculum and Lecture plan


An important part of MA2501 Numerical Methods is the implementation of numerical methods as computer programs. For that we will use Python, a multi-purpose programming language which offers an extensive computing environment designed for numerical computations. For more information see Introduction to Python.

Learning outcome

A student successfully meeting all the learning objectives of this course

  1. will have developed knowledge and general competence in numerical methods, in particular will have familiarity with selected algorithms, knowledge of how these algorithms are developed and analysed; will have familiarity with central concepts such as error sources, convergence and stability.
  2. will be able to choose a suitable numerical algorithm for a given mathematical problem, to implement this method, and to critically evaluate the result; will acquire the ability of developing (further) simple numerical algorithms and to analyse these.

The exam and the compulsory assignments are designed to test the achievement of the learning outcome.


Evaluation system and marking in this course
  • The project counts for 30 % of the final mark. The final exam counts for 70 %. The official description of the course will be updated accordingly in the next few days.
2023-08-27, Vasileios Tsiolakis