Modelling and Simulation

Uitgebreide vaknaam	Modelling and Simulation
Leerdoelen	At the end of the course, the student is able to: 1. Explain and use key modelling strategies and mathematical/computational techniques 2. Understand and modify existing abstract models of complex real world systems or formulate novel models in a variety of scientific disciplines. 3. Know how to identify and formulate relevant research questions and design/modify existing models in order to investigate these systematically. 4. Present the computational investigation of a particular model system appropriately and to present and discuss results of a computer simulation study according to scientific standards.
Omschrijving	Modelling and simulation techniques play an increasingly important role in a variety of scientific disciplines. This course will cover some of the most important techniques used in the simulation of systems, which could come from physics, chemistry, biology, sociology or other fields. Examples in the course will include, among others, models of deterministic chaos, growth processes, game theory and neural networks. The emphasis, however, will be on the basic concepts and the simulation techniques, rather than on the actual applications. Numerical methods used in the course will include discrete iterations, integration of differential equations, Monte Carlo simulations, etc.
Uren per week
Onderwijsvorm	Hoorcollege (LC), Opdracht (ASM)
Toetsvorm	Schriftelijk tentamen (WE), Verslag (R) (Final grade: weighted average of the practicals (weight 2/3) and the written (digital) exam (weight 1/3). In order to pass, students must get a mark of at least 5.5 for both of these separately, and the weighted average has to be at least 5.75. Weighted averages above 4.75 and below 5.75 will result in a final grade 5.0, in all other cases the grade is rounded to the nearest half-integer value.)
Vaksoort	master
Coördinator	Dr. M.H.F. Wilkinson
Docent(en)	Prof. Dr. M. Biehl ,Dr. M.H.F. Wilkinson
Verplichte literatuur	Titel Auteur ISBN Prijs All lecture notes and additional material (original literature etc.) will be provided through Brightspace. No textbook is required. links to secondary literature, textbooks etc. are provided in Brightspace.
Entreevoorwaarden	The course unit assumes prior knowledge in the sense that students should have some basic experience with programming, either in Matlab (recommended but not obligatory) or any mainstream general purpose programming language such as C, C++, Java, Python etc.
Opmerkingen	This course has limited enrollment: - CS students can always enter the course, regardless of whether the course is mandatory for them or not. - The number of enrolments for other non-CS students is limited. These students need to meet the course prerequisite requirements as mentioned on Ocasys. Priority is given to students for which the course is an official elective (see list below). - An exception can be made for exchange students, if they have a CS background: please contact the FSE International Office. See here for more info about the enrollment procedure.
Opgenomen in	Opleiding Jaar Periode Type MSc Astronomy: Quantum Universe  (Optional Courses in Data Science (DS)) - semester I a keuze MSc Computing Science: Data Science and Systems Complexity  (Compulsory course units) 1 semester I a verplicht MSc Computing Science: Intelligent Systems and Visual Computing  (Compulsory course units) 1 semester I a verplicht MSc Computing Science: Science Business and Policy  (Elective course units) 1 semester I a keuze MSc Courses for Exchange Students: AI - Computing Science - Mathematics - semester I a