The Munich Center for Machine Learning (MCML) is organizing a 5-day workshop on computational reproducibility and scientific computing for R and Python users.

The in-person workshop is designed to provide a balanced mix of theoretical background and practical skills with lecture-style morning sessions and hands-on tutorials in the afternoon.

Topics covered include writing reproducible manuscripts for small-scale data analysis projects, high performance computing (HPC) for large-scale projects, and packaging and software development.

Details of the workshop

Who:                   Primary target group are PhD students, but the workshop is open to all researchers and students meeting the prerequisites (listed on the homepage linked below)

When:                 We-Fr, 25.09. - 27.09. & Mo-Tu, 30.09. - 01.10.
If it is organizationally feasible, we will try to enable participation on individual days. 

Where:               Munich, in-person, Location/Room TBD
What:                  Topics include computational reproducibility, HPC, Packaging, CI/CD; both for R and Python users
How:                   Lecture-style morning sessions, hands-on tutorials in the afternoons

You can find a detailed program and more information on the workshop, the prerequisites and the registration process on the workshop website: https://sites.google.com/view/mcml-ws-repro-compute/home

To attend, please register by 6 September 2024, 23:59 CEST: https://forms.gle/w6E9jNgzHCjH9bXAA.

Seats will be given on a first-register, first-serve basis. (We reserve the right to reject applicants who do not meet our minimum coding experience requirements.) 

Best wishes

Martin Binder, MCML Open Source and Open Data Transfer Coordinator
Moritz Herrmann, MCML Reproducibility and Open Science Transfer Coordinator

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Dr. Malika Ihle (she/her) (pronounciation)

LMU Open Science Center Coordinator

Website: https://www.osc.lmu.de

Mailing list: https://lists.lrz.de/mailman/listinfo/lmu-osc

Computing skill self-paced tutorials: https://github.com/lmu-osc

Workshops material: https://osf.io/zjrhu/

Bluesky: https://bsky.app/profile/lmu-osc.bsky.social

LinkedIn: https://www.linkedin.com/company/lmu-open-science-center

Mastodon: https://scicomm.xyz/@lmu_osc

Twitter: https://twitter.com/lmu_osc

Summer School: https://osip.mpdl.mpg.de/lmu-mpg-open-science-summer-school-2024/