BIOS 437: Data Best Practices: Computation

Biosciences Interdisciplinary Stanford University 1.0 credits

Course Description

Building on Data Best Practices: Basics, this one-week Mini-Course covers advanced topics in reproducible, portable, and scalable scientific computing. Students will containerize software and environments with Podman/Docker; parallelize analyses locally with GNU Parallel and orchestrate cloud-based, asynchronous parallelization with Google Cloud Pub/Sub; and implement CI/CD in Stanford GitLab, using runners to automate scientific data preprocessing and analysis pipelines. It is recommended that students take Data Best Practices: Basics prior to enrolling in this course. Students will equivalent experience may also enroll.

Reviews

Sign in to Review Login to Review

No reviews yet. Be the first to share your experience!

Sign in with Google Login to Review