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327-0514-00L 3 Credits BSC D-MATL
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Computational Thinking Lab II

Lecturers & Examiners: Prof. Dr. Martin Kröger
VVZ CR n/a

Last Updated: 2026-02-05 16:02:13

Abstract

You are going to address, in groups, problems that are arising or may arise in the context of remaining courses of your studies, that cannot be solved analytically or manually within reasonable amounts of time, but solved computationally with the help of a programming language and computers. Knowledge of a computing language is required.

Objective

Participants get used to one or more collaborative tools, work actively in groups. They invent, set up, structure, plan, and attempt solving a problem that requires developing algorithms. They make use of existing, or invent novel, computational methods. Aspects that should be taken into account when developing algorithms or codes are: speed of execution, ease of use, small amount of adjustable parameters.

Content

Development of a project plan, including modules to be created, milestones to be reached, required input data and its aquisition, tests to be performed, work sharing. The project needs to be documented, and codes saved using a collaborative environment (github, vscode share). Ideally, several groups attack a similar problem so that their results can be directly compared (concerning speed of execution, algorithms, etc.)

Resources

Lecture Notes

Information available athttps://polyphys.mat.ethz.ch/education/courses/CTL-II.html

Literature

A. Shiflet, G.W. Shiflet, Introduction to Computational Science: Modeling and Simulation for the Sciences, Princeton University Press; 2nd edition (March 30, 2014) ISBN-13: 978-0691160719 M.P. Allen, D.J. Tildesley, Computer Simulation of Liquids (Oxford Science Publications, Oxford, United Kingdom) ISBN-10 9780198556459 D. Frenkel, Understanding Molecular Simulation: From Algorithms to Applications, Computational Science Series, Vol. 1 ISBN-10 0122673514

Learning Materials (Links)

General Information

Language
English
Levels
BSC
Frequency
Yearly recurring

Examination

Type
ungraded semester performance
Der Kurs gilt als bestanden, wenn die Programmieraufgaben in der Gruppe bearbeitet, der Algorithmus auf overleaf beschrieben, und die Ergebnisse und Erfahrungen in einem Kurzvortrag dargestellt wurden.

Course Components

Type Title Time & Place Hours
lecture with exercise Computational Thinking Lab II
  • Mon 11:45-12:30 (HCP E 47.3)
1 h weekly
independent project Computational Thinking Lab II
Selbständiges Arbeiten
No time listed 2 h weekly

Offered In