Course - Mathematics for engineering 3 A - IMAA3011
Mathematics for engineering 3 A
About
About the course
Course content
General numerics
Representations of floating point numbers in the computer, calculations with floating point numbers and various sources of error. Error magnification and condition.
Numerical linear algebra
Orthogonality in vector spaces and orthogonal bases. Gram-Schmidt orthogonalization. QR factorization. Singular value decomposition (SVD). Cholesky factorization and conjugate gradients.
Optimization
Linear programming. Method of least squares. Lagrange multipliers.
Learning outcome
Knowledge
The candidate has good knowledge of:
- Common sources of error in numerical calculations.
- Vector spaces and orthogonal bases and is familiar with orthogonalization algorithms.
- Various matrix factorizations and their applications.
- The main concepts and methods from optimization, such as iterative methods, constraints, Lagrange multipliers, objective function, dual problem.
- Digital tools for analyzing mathematical problems.
Skills
The candidate:
- Can solve linear systems numerically and estimate errors related to numerical calculations.
- Can apply eigenvalues, eigenvectors, and singular value decomposition (SVD) to solve engineering problems using digital tools.
- Can use computers to solve unconstrained optimization problems and interpret the results.
- Can solve some simple constrained optimization problems using Lagrange multipliers.
- Can formulate some applied problems such as tasks in linear programming, solve them using computers, and interpret the results.
- Should be capable of using digital tools to analyze mathematical problems.
General Competence
The candidate:
- Is well-versed in and can apply a mathematical symbol and formula apparatus relevant to communicating in the engineering field.
- Has experience applying mathematical methods and digital tools to problems from their own and adjacent fields.
- Is capable of connecting mathematical concepts and techniques to models encountered both within and outside of their studies.
Learning methods and activities
Lectures, exercises, compulsory tasks.
Compulsory tasks include both analytical and numerical solution methods, and includes problems that are solved using digital tools.
Compulsory assignments
- Compulsary tasks
Further on evaluation
4 hour individual exam, graded using the scale A-F.
In order to take the exam, compulsory assignments must be passed. Some assignments can be passed orally. Re-sit Exam: May/June. Re-sit exam can be changed to an oral exam.
Python will be available during the exam.
Specific conditions
Admission to a programme of study is required:
Aquaculture - Engineering (BIHAV)
Automation and Intelligent Systems - Engineering (BIAIS) - some programmes
Civil Engineering - Engineering (BIBYGG)
Computer Science - Engineering (BIDATA) - some programmes
Electrical Engineering (BIELEKTRO)
Electrification and Digitalisation - Engineering (BIELDIG)
Electronic Systems Engineer - Engineering (BIELSYS)
Logistics - Engineering (FTHINGLOG)
Mechanical Engineering (BIMASKIN)
Mechatronics and Product Design - Engineering (BIMEPRO)
Naval Architecture - Engineering (699SD)
Renewable Energy - Engineering (BIFOREN)
Recommended previous knowledge
IMAA/G/T 1002 - Mathematics for Engineers 1
and one of
IMAA/G/T 2012/2022/2024 - Mathematics for Engineers 2 A/B/D.
Course materials
Lecture notes, videos and other materials will be made available on the learning platform.
Credit reductions
| Course code | Reduction | From |
|---|---|---|
| IMAT3011 | 7.5 sp | Autumn 2025 |
| IMAG3011 | 7.5 sp | Autumn 2025 |
| TMA4110 | 2.5 sp | Autumn 2025 |
| IMAG2150 | 5 sp | Autumn 2025 |
| IMAT2150 | 5 sp | Autumn 2025 |
| IMAA2150 | 5 sp | Autumn 2025 |
| IMAA2023 | 3 sp | Autumn 2026 |
| TMA4420 | 3 sp | Autumn 2026 |
| IMAG2023 | 3 sp | Autumn 2026 |
| IMAT2023 | 3 sp | Autumn 2026 |
| VB6041 | 3 sp | Autumn 2026 |
| IMAG3011F | 7.5 sp | Autumn 2026 |
| IMAG2023F | 3 sp | Autumn 2026 |
Subject areas
- Mathematics