TU Delft Resources
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Six Jupyter Notebooks used in the first year physics lab course. The first three notebooks cover the basic concepts of programming. Notebooks 4 and 5 cover numpy, plotting and data-analysis. Notebook 6 covers error propagation.
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Materials used by the library to train researchers.
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This set of Notebooks is written for scientists and engineers who want to use Python programming for exploratory computing, scripting, data analysis, and visualization.
http://mbakker7.github.io/exploratory_computing_with_python/
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Materials related to the second year Computational Science course in the physics program, covering i.a. numerical differentiation and integration, Fourier analysis, and Monte Carlo simulations. Access may be requested.
https://gitlab.tudelft.nl/python-for-applied-physics/computational-science
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This package contains a set of tools that are used to support the MUDE course given at Civil Engineering, TU Delft, for first-year MSc students. It contains a set of tools and dependencies that are used in the course contents themselves. In addition, this package has several debugging tools that can be used by students and staff to check that their installation is compatible with the requirements for the course.
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More than 25 examples on transient and steady-state dynamic analysis of multiple degree-of-freedom systems using time- and frequency-domain techniques. Reduced-order modelling techniques based on modal analysis are included, with a detailed discussion on modal truncation error. A full workshop on random fatigue analysis is also included, based on the frequency-domain methods.
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These are the materials of the course Intermediate Python Programming (TI3105TU), which is taught in the Computer Science minor programme by Frank Mulder (F.Mulder@tudelft.nl). They can be tried live on WebLab: find the course TI3105TU and enrol in this year’s edition. (WebLab contains the Python assignments that students do throughout the course. The associated reading/video material is hosted on Brightspace.)
The course assumes that students already have basic Python skills. See this webpage for an overview of the prerequisite knowledge, along with materials to teach those basics.