Training

Scientific computing and data science require special, practical skills in programming and computer use. However, these aren’t often learned in academic courses. This page is your portal for getting these skills. The focus is practical, hands-on courses for scientists, not theoretical academic courses.

Scientific Computing in Practice

SCIP is a lecture series at Aalto University which covers hands-on, practical scientific computing related topics. Lectures are open for the entire Aalto community as well as our partners at FGCI consortium.

Examples of topics covered at different lectures: HPC crash course, Triton kickstarts, Linux Shell, Parallel programming models: MPI and OpenMP, GPU computing, Python for scientists, Data analysis with R and/or Python, Matlab, HTCondor and many others.

Tentative plans: Fall / Winter 2020-21 courses (tentative plan): Linux Shell Basics, Python for Scientists, Data analysis with R and Python, Matlab Basics, GPU computing, Triton winter kickstart. Spring / Summer 2021: Introduction to MPI, Matlab continuation course, Linux Shell Scripting, CodeRefinery. On top of them Summer Kickstart in June.

Anyone can sign up for announcements at the SCIP announcement mailinglist.

Skills map

There is a lot to learn, and it all depends on each other. How do you get started?

Our training map Hands-on Scientific Computing sorts the skills you need by level and category, providing you a strategy to get started.

In order to do basic scientific computing, C (Linux and shell) is needed. To use a computer cluster, D (Clusters and HPC) is useful. E (scientific coding) is useful if you are writing your own software.