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# Scientific Computing (Master 2 EFM)
## Content
During sessions 1, 2 and 4 (9 hours), we will present an introduction on
scientific computing and programming:
- Computers to compute (CPU, memories, GPU, clusters)
- Numbers in computers
- Programming languages
- Difference open-source / close-source
- Operating systems and importance of Linux for scientific computing
- Install a good environment, example of Conda
- Versioning and Gitlab (https://gricad-gitlab.univ-grenoble-alpes.fr)
We will study some basics on Linux and Python for scientific computing.
The personal project part will be presented during session 3. Sessions 3, 5, 6
and 7 will be dedicated to practical exercices on (3) Computation of integrals,
(5) Finite Difference methods, (6) Gradient descent and (7) Machine learning.
We will work together on your personal projects during session 8.
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