Computational Analysis: A Reproducible Python Course for Numerical Methods
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Zenodo
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| Natura: | Recurso digital |
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Zenodo
2025
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| _version_ | 1866901099813797888 |
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| author | Afful, James |
| author_facet | Afful, James |
| contents | <p>This repository provides a fully reproducible Python-based computational analysis course covering numerical linear algebra, optimization, ordinary and partial differential equations, and data-driven modeling.</p> <p>The materials are designed for training students and researchers in modern computational workflows, including numerical stability analysis, algorithmic verification, and reproducible scientific computing using Jupyter notebooks.</p> <p>The course is packaged as an executable Jupyter Book and is intended for use in academic instruction, research group onboarding, and independent study in computational science and engineering</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_18066313 |
| institution | Zenodo |
| language | |
| publishDate | 2025 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Computational Analysis: A Reproducible Python Course for Numerical Methods Afful, James Numerical analysis Scientific computing Python <p>This repository provides a fully reproducible Python-based computational analysis course covering numerical linear algebra, optimization, ordinary and partial differential equations, and data-driven modeling.</p> <p>The materials are designed for training students and researchers in modern computational workflows, including numerical stability analysis, algorithmic verification, and reproducible scientific computing using Jupyter notebooks.</p> <p>The course is packaged as an executable Jupyter Book and is intended for use in academic instruction, research group onboarding, and independent study in computational science and engineering</p> |
| title | Computational Analysis: A Reproducible Python Course for Numerical Methods |
| topic | Numerical analysis Scientific computing Python |
| url | https://doi.org/10.5281/zenodo.18066313 |