Basic information
Code: SCI3076
Extent: 20–25 cr
Language: English
Professor in charge: Lasse Leskelä
Administrative contact: Johanna Bovellán
Target group: All MSc students with sufficient prerequisite knowledge
Application procedure: Open to all students of Aalto University
Quotas and restrictions: No quotas
Prerequisites: BSc minor in Mathematics or equivalent knowledge. Please check the course prerequisites before signing up.
Objectives
This minor is designed for students willing to develop their general mathematical thinking and problem solving skills, and to learn mathematical and statistical methods that can be applied in science, technology, arts, and business.
Structure
Select 20–25 credits including 15–25 credits of MS-E***** courses and 0–5 credits of MS-C**** courses. Other courses can be included with the consent of the professor in charge. Suitable courses are listed below.
| General mathematics | |||
| Code | Name | Credits | Period |
Crystal flowers in halls of mirrors: Mathematics meets art and architecture | 5–15 | III–IV | |
Algebra and discrete mathematics | |||
| MS-C1081 | Abstract algebra | 5 | III |
| MS-E1050 | Graph theory | 5 | I |
| MS-E1051 | Combinatorial network analysis | 5 | II (2021-2022) |
| MS-E1110 | Number theory | 5 | II |
| MS-E1111 | Galois theory | 5 | IV (2020-2021) |
| MS-E1142 | Computational algebraic geometry | 5 | III (2020-2021), V (2021-2022) |
| MS-E1200 | Lie groups and Lie algebras | 5 | IV (2021-2022) |
| Analysis | |||
| MS-C1350 | Partial differential equations | 5 | I–II |
| MS-E1280 | Measure and integral | 5 | II |
| MS-E1281 | Real analysis | 5 | IV (2021-2022) |
| MS-E1461 | Hilbert spaces | 5 | I |
| MS-E1462 | Banach spaces | 5 | II (2020-2021) |
| MS-E1531 | Differential geometry | 5 | III (2021-2022) |
| Computational mathematics | |||
| MS-C1342 | Linear algebra | 5 | V |
| MS-E1142 | Computational algebraic geometry | 5 | III (2020-2021), V (2021-2022) |
| MS-E1150 | Matrix theory | 5 | II (2020-2021) |
| MS-E1651 | Numerical matrix computations | 5 | I |
| MS-E1652 | Computational methods for differential equations | 5 | II |
| MS-E1653 | Finite element method | 5 | III–IV |
| MS-E1654 | Computational inverse problems | 5 | IV |
| Optimization | |||
| MS-E2121 | Linear optimization | 5 | III-IV |
| MS-E2122 | Nonlinear optimization | 5 | I–II |
| Probability and statistics | |||
| MS-C2111 | Stochastic processes | 5 | II |
| MS-E1600 | Probability theory | 5 | III |
| MS-E1603 | Random graphs and network statistics | 5 | I |
| MS-E1621 | Algebraic statistics | 5 | I–II (2020-2021) |
| MS-E2112 | Multivariate statistical analysis | 5 | III–IV |