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327-0314-00L 2 Credits BSC D-MATL
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Computational Thinking Lab I

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

Last Updated: 2026-02-05 16:16:27

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

- Getting used to the idea that solving problems using a programming language is a dynamic process, where one can learn from errors - Thinking in modules that perform a task and can be tested separately. Modules are then combined to interact lateron. - Organizing the distribution of work across a small group of students and ask questions, as soon as they arise. - Using existing resources if helpful to implement your ideas - Getting confronted with computational tasks as they may occur during scientific work

Content

- Develop ideas to solve well-defined problems using computational methods - Create transparent (re-usable, using functions) and ideally efficient algorithms using python - Make use of collaborative tools (vscode, github) to edit, store and execute python code in groups - Create accompanying descriptions and resulting graphs (at github, using mark-down language) - Make use of internet resources or vscode to find answers to questions that arise (python command and their syntax, existing libraries, if helpful) - Short oral presentation of algorithms, results, possible improvements at the end of the semester

Resources

Lecture Notes

There is no script for this course. Each project has its own project description at github. Information available athttps://polyphys.mat.ethz.ch/education/courses/CTL-I.htmland alternatively, athttps://ctl.polyphys.mat.ethz.ch/

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 beschrieben, und die Ergebnisse und Erfahrungen in einem Kurzvortrag dargestellt wurden.

Course Components

Type Title Time & Place Hours
lecture with exercise Computational Thinking Lab I
  • Mon 12:45-13:30 (HCP E 47.3)
1 h weekly
independent project Computational Thinking Lab I
Selbständiges Arbeiten
No time listed 1 h weekly

Offered In