Computational lab course that spans research data processing workflow starting just after the point of acquisition through to computation and visualization.

Topics Include

  • Stanford specific best practices for data storage
  • Code management
  • File formats
  • Data curation
  • Toolchain creation
  • Interactive and batch computing
  • Dynamic visualization
  • Distributed computing

Students will work with a dataset of their choosing when working through topics