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 Course module: 202200239
 202200239Modelling and Programming 2
 Course info
Course module202200239
Credits (ECTS)5
Course typeStudy Unit
Language of instructionEnglish
Contact persondr.ir. G. Meinsma
E-mailg.meinsma@utwente.nl
Lecturer(s)
 Previous 1-5 of 106-10 of 10 Next 5
 Examiner dr. T.S. Craig Lecturer dr. T.S. Craig Examiner dr.ir. R.P. Hoeksma Lecturer dr.ir. G. Meinsma Contactperson for the course dr.ir. G. Meinsma
Starting block
 2A
RemarksPart of module 3 B-AM.
Minor students: please register for the minor!
Application procedureYou apply via OSIRIS Student
Registration using OSIRISYes
 Aims
 body { font-size: 9pt; font-family: Arial } table { font-size: 9pt; font-family: Arial } Afterwards the student is able to: Interpret a real-life problem, and extract from it a sensible mathematical research question, Devise an action plan for the modelling project with the above research question, Execute the modelling assignment, with emphasis on the mathematical analysis, in particular relating to the other courses in this module,  Present written and verbally the results of the modelling project, Cooperate in a team and give constructive feedback, Present the results of a project both in written and verbal form, Analyse the correctness of algorithms implemented in Python, Describe, explain and modify larger programs in Python.
 Content
 body { font-size: 9pt; font-family: Arial } table { font-size: 9pt; font-family: Arial } The prime objective (80% of the course) is to predict water levels using lots of measurements that have been collected in the past. This is directly related to signals and transforms but if you want to characterise the quality of your prediction you also need to model and quantify the uncertainty, which is connected to probability theory. In the project the students work in a group.  Students should report their results in a written report, as well as an oral presentation. A second component is a programming course (20% of the course) focusing on the use of Python. The focus is on the following topics: Recursion Formal reasoning on the correctness of algorithms Implementing elementary algorithms from a textual description Using Python for data and time series analysis. Assessment Modelling assignment (100%) Programming assignment (pass/fail) Collaboration (pass/fail)
Assumed previous knowledge
 AM modelling assignments. Basic programming skills.
 Module
 Module 3
 Participating study
 Bachelor Applied Mathematics
Required materials
Handouts
 Pdf on Canvas.
Recommended materials
-
Instructional modes
Practical
 Presence duty Yes

Presentation(s)
 Presence duty Yes

Workshop
 Presence duty Yes

Tests
 Modelling assignment Programming assignment Collaboration
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