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Total Size:
7.5 MB
Info Hash:
2AF392C48E5260D676060095773BDB979E151DDD
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Added:
Sept. 11, 2025, 11:03 a.m.
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(Last updated: Sept. 11, 2025, 11:05 a.m.)
| File | Size |
|---|---|
| Ershadi A., Kappler W. Advanced Scientific Programming (Python) 2025.pdf | 7.5 MB |
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SOURCE: Ershadi A., Kappler W. Advanced Scientific Programming (Python) 2025
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Textbook in PDF format Scientists spend more and more time writing, maintaining, and debugging software. While techniques for doing this efficiently have evolved, only few scientists have been trained to use them. As a result, instead of doing their research, they spend far too much time writing deficient code and reinventing the wheel. In this course we will present a selection of advanced programming techniques and best practices which are standard in the industry, but especially tailored to the needs of a programming scientist. Lectures are interactive and allow students to acquire direct hands-on experience with the topics. Students will work in pairs throughout the school and will team up to practice the newly learned skills in a real programming project — an entertaining computer game. We use the Python programming language for the entire course. Python works as a simple programming language for beginners, but more importantly, it also works great in scientific simulations and data analysis. Python is the standard tool for the programming scientist due to clean language design, ease of extensibility, and the great wealth of open source libraries for scientific computing and data visualization. This school is targeted at PhD students, postdocs and more senior researchers from all areas of science. Competence in Python or in another language such as Java, JavaScript, C/C++, MatLAB, or R is absolutely required. Basic knowledge of Python and git or another version control system is assumed. Participants without any prior experience with Python or git should work through the proposed introductory material before the course
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