Programplaner og emneplaner - Student
MEK2000 Mathematics 2000 Course description
- Course name in Norwegian
- Matematikk 2000
- Study programme
-
Bachelor’s Programme in Electrical EngineeringBachelor's Degree Programme in Biotechnology and Applied ChemistryBachelor's Degree Programme in Mechanical Engineering
- Weight
- 10.0 ECTS
- Year of study
- 2025/2026
- Curriculum
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FALL 2025
- Schedule
- Programme description
- Course history
-
Introduction
This course, together with Mathematics 1000, will give the students an understanding of mathematical concepts, problems and solution methods with the focus on application, particularly in engineering subjects.
Recommended preliminary courses
The course builds on ELFE/MAFE/KJFE1000 Mathematics 1000 or MEK1000.
Required preliminary courses
There are no requirements beyond the admission requirements.
Learning outcomes
After completing the course, the student is expected to have achieved the following learning outcomes defined in terms of knowledge, skills and general competence:
Knowledge
The student is capable of:
- explaining how functions can be approximated by Taylor polynomials and truncated Fourier series,
- explain what it means that a series converges, with emphasis on power and Fourier series,
- differentiating and integrating power series term by term,
- explaining what a frequency spectrum is,
- describing and explaining how a sequence of numbers can originate by sampling, by using formulae or as the solution of a difference equation,
- explaining how to interpolate sampled data,
- explain linear regression based on sampled data,
- explaining partial differentiation and using using relevant tools visualize functions of two variables,
- calculating eigenvalues and eigenvectors.
Skills
The student is capable of:
- discussing the connection between Fourier series and the Fourier transform,
- discussing pros and cons using interpolating polynomials, and splines to interpolate sampled data,
- explaining how the method of least square may be applied to fit data to a linear function and implement such methods numerically on for larger data sets,
- discussing error bounds when using Taylor polynomials to approximate functions,
- using simple tests for convergence of series,
- giving a geometrical interpretation of gradient and directional derivative and using linear approximations of multi variable functions,
- using partial differentiation optimize functions of two variables - both analytically and by implementing the method of gradient ascent/descent,
- using eigenvalues and eigenvectors to solve coupled linear systems of differential equations with constant coefficients.
General competence
The student is capable of:
- identifying connections between mathematics and their own field of engineering,
- translating practical problems, preferably from their own field, into mathematical form so that it can be solved analytically or numerically,
- assessing her or his own results from analytical and numerical calculations,
- formulating precise explanations, providing justifications for the choices of methods and demonstrating correct use of mathematical notation,
- using relevant analytical and numerical methods and tools,
- use mathematics to communicate problems and solutions within engineering sciences.
Teaching and learning methods
The course is taught through joint lectures and exercises. In the exercise sessions, the students work on assignments, both individually and in groups, under the supervision of a lecturer. These sessions will also involve assessing the assignments - both own ones and assignments carried out by fellow students.
Also in between teaching sessions, the students are expected to work with exercises. The proposed exercises are directly linked to learning outcomes for the course. Assessing their own and others' solutions will provide the students with insight as to which extent these goals are achieved.
The students will also have the option of handing in certain exercise sets and have these assessed.
Course requirements
None.
Assessment
Individual written exam under supervision, 3 hours.
The exam result can be appealed.
Permitted exam materials and equipment
All printed and written aids.
Calculator.
Grading scale
Grade scale A-F.
Examiners
One internal examiner. External examiners are used regularly.
Overlapping courses
The course has an overlap of 10 credits with MAPE2000, KJPE2000, EMPE2000 and BYPE2000. This course overlaps 5 credits with DAPE2000 and ELTS2000. Under the rule that students have three attempts to take an exam, attempts in equivalent courses also count.