Course - Mathematics for engineering 3 A - IMAG3011
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
- Exercises
- Preproject
Further on evaluation
The exam consists of two assessment components:
- a 3-hour individual digital exam where Python is available, and
- an individual oral exam based on the candidate's work with a project assignment, and academic issues related to the project assignment. The regular A-F grading scale is used for both parts.
The mandatory coursework requirements consist of exercises and a pre-project. Some exercises can be approved orally. Approved exercises give access to the digital written exam, and exercises from previous years are automatically approved by the department. An approved pre-project provides access to the individual oral exam. The pre-project is only valid in the semester it is passed, and for the re-sit exam in April/May next year.
If one sub-assessment is passed, and one is not passed, the sub-assessment that was not passed can, if necessary, be retaken when the course is offered regularly. Students who wish to improve their grade in the course can choose to retake only one of the sub-assessments.
Re-sit exam in April/May. For re-sit exams, a written exam can be converted to an oral exam. If the assessment method is changed, the entire course must be retaken.
Specific conditions
Admission to a programme of study is required:
Aquaculture - Engineering (BIHAV)
Automation and Intelligent Systems - Engineering (BIAIS) - some programmes
Building Constructions – Engineering (BIBYGGK)
Civil Engineering - Engineering (BIBYGG)
Computer Science - Engineering (BIDATA) - some programmes
Digital Infrastructure and Cyber Security (BDIGSEC)
Electrical Engineering (BIELEKTRO)
Electrification and Digitalisation - Engineering (BIELDIG)
Electronic Systems Engineer - Engineering (BIELSYS)
Logistics - Engineering (FTHINGLOG)
Mechanical Engineering (BIMASKIN)
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 |
| IMAA3011 | 7.5 sp | Autumn 2025 |
| TMA4110 | 2.5 sp | Autumn 2025 |
| IMAA2150 | 5 sp | Autumn 2025 |
| IMAT2150 | 5 sp | Autumn 2025 |
| IMAG2150 | 5 sp | Autumn 2025 |
| IMAA2023 | 3 sp | Autumn 2026 |
| IMAG2023 | 3 sp | Autumn 2026 |
| TMA4420 | 3 sp | Autumn 2026 |
| IMAG3011F | 7.5 sp | Autumn 2026 |
| IMAG2023F | 3 sp | Autumn 2026 |
| IMAT2023 | 3 sp | Autumn 2026 |
| VB6041 | 3 sp | Autumn 2026 |
Subject areas
- Mathematics