Prerequisite/Recommended prerequisite for participation in the module

The students completing the module will have gained knowledge about a number of topics from mathematical modelling. The list may include, but is not limited to, the following topics:

Content, progress and pedagogy of the module

Learning objectives

Knowledge

• first and second order linear differential equations and their classification
• boundary value and intial value problems
• solution methods for linear differential equations
• solution representation and regularity of solutions
• expectation-maximisation (EM) algorithm and missing data
• Bayesian networks
• graphical models
• queueing theory
• hidden Markov models

Skills

• can apply the relevant methodologies in one or more scenarios and interpret the results

• can state the underlying assumptions and argue about limitations and extendibility of the methodology in one or more specific settings

• can assess goodness-of-fit for the models where appropriate

Competences

• can acquire supplementary knowledge about the relevant methodologies

• can combine appropriate topics from the course to analyse a specific problem

• can in writing describe the methodologies, results and outcome from an analysis of a specific problem

Type of instruction

Lectures with exercises.

Extent and expected workload

This is a 5 ECTS course module and the work load is expected to be 137,5 hours for the student.
 

Exam

Exams

Name of exam	Matematisk modellering
Type of exam	Written or oral exam
ECTS	5
Assessment	7-point grading scale
Type of grading	Internal examination
Criteria of assessment	The criteria of assessment are stated in the Examination Policies and Procedures

Additional information

Please contact Study Board of Mathematical Sciences - studyboard@math.aau.dk