Professor in charge: Nuutti Hyvönen
Other professors: Chris Brzuska, Antti Hannukainen, Camilla Hollanti, Pauliina Ilmonen, Kaie Kubjas, Lasse Leskelä, Rolf Stenberg
Extent: 55–65 ECTS (long major) or 40–45 ECTS (compact major)
Abbreviation: AM
Code: SCI3053
Objectives
The major in Applied Mathematics is designed for students interested in mathematical sciences and their application to other disciplines. It is based on a solid mathematical core that gives the student a broad set of skills for working on diverse mathematical problems. The major also includes an elective part that provides flexibility to orientate toward a master's thesis project in a chosen application area. A high proportion of students majoring in applied mathematics will continue their studies to a doctoral degree.
The importance of mathematical techniques is increasing in science and engineering as new fields employing sophisticated mathematical models are constantly emerging. The driving forces for such development are the ever-increasing computational resources, which should be used wisely and to their full power. This requires the education of mathematicians who are able to interact and collaborate with experts in application areas. The major in Applied Mathematics responds to this need.
Content and structure
The major in Applied Mathematics can be taken either as a long major (55–65 ECTS) or a compact major (40–45 ECTS). The student's personal academic advisor provides assistance in planning the curriculum details.
Mandatory studies (15 ECTS)
CODE | NAME | CREDITS | PERIOD | YEAR |
Numerical matrix computations | 5 | II | 1 | |
Multivariate statistical analysis | 5 | III–IV | 1 | |
Nonlinear optimization | 5 | I–II | 1 |
Core studies (25–45 ECTS)
Select 25–45 credits for a long major or 25–30 credits for a compact major. In both cases, select at least one course from each of the three categories below.
Computational mathematics
CODE | NAME | CREDITS | PERIOD | YEAR |
Computational algebraic geometry | 5 | I (every other year) | 1 or 2 | |
Hilbert spaces | 5 | I | 1 or 2 | |
Computational methods for differential equations | 5 | I | 1 or 2 | |
Finite element method | 5 | III–IV | 1 or 2 | |
Computational inverse problems | 5 | IV | 1 or 2 |
Optimization
CODE | NAME | CREDITS | PERIOD | YEAR |
Linear optimization | 5 | I–II | 1 or 2 | |
Integer optimization | 5 | III–IV (every other year) | 1 or 2 | |
Decision making and problem solving | 5 | III–IV | 1 or 2 |
Statistics and probability
CODE | NAME | CREDITS | PERIOD | YEAR |
Probability theory | 5 | III | 1 or 2 | |
Large random systems | 5 | IV (every other year) | 1 or 2 | |
Random graphs and network statistics | 5 | I | 1 or 2 | |
Bayesian data analysis | 5 | I–II | 1 or 2 |
Students taking a long major select in addition sufficiently many courses in mathematics or other mathematical sciences to obtain a total of 55–65 credits. Courses not in the below list of recommended courses may also be included with the consent of the professor in charge.
Recommended courses
CODE | NAME | CREDITS | PERIOD | YEAR |
Graph theory | 5 | I (2018-2019) | 1 or 2 | |
Number theory | 5 | II (2018-2019) | 1 or 2 | |
Galois theory | 5 | IV (every other year) | 1 or 2 | |
Advanced topics in cryptography | 5 | III–IV | 1 or 2 | |
Computational mechanics 1 | 5 | I | 1 or 2 | |
Computational mechanics 2 | 5 | II | 1 or 2 | |
Principles of algorithmic techniques | 5 | I–II | 1 or 2 | |
Machine learning: Basic principles | 5 | I–II | 1 or 2 | |
Advanced course in algorithms | 5 | III–IV | 1 or 2 | |
Distributed algorithms | 5 | I–II | 1 or 2 | |
Cryptography and data security | 5 | I–II | 1 or 2 | |
Computational complexity theory | 5 | III–IV | 1 or 2 | |
Combinatorics | 5 | III–IV | 1 or 2 | |
Programming parallel computers | 5 | V | 1 or 2 | |
Complex networks | 5 | I–II | 1 or 2 | |
Mathematical methods for network science | 5 | III (every other year) | 1 or 2 | |
Computational physics | 5 | III–V | 1 or 2 | |
Dynamics of particles, fluids and solids | 5 | I-II | 1 or 2 |