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.

If you are interested in a re-run of our past courses or if you want to suggest a new course, please take this survey.

Future courses Fall-Winter 2022 courses - We are always adding interesting courses. Please check this page once in a while. If you are interested in a re-run of our past courses or if you want to suggest a new course, please take this survey.

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

Other interesting courses

Data management, Reproducibility, open science

Other relevant courses by Aalto Open Science team: https://www.aalto.fi/en/services/training-in-research-data-management-and-open-science

Other courses on scientific computing and data management

Please check https://mycourses.aalto.fi/ for other courses at Aalto and https://www.csc.fi/en/training for training courses and events at CSC. Some coming courses:

MOOC on scientific computing:

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.

Level dependencies

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.

Our courses

You can browse the material we have developed for our courses by following the links below.