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 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 Autumn 2023 courses - Linux Shell, CodeRefinery, Python for Scientific Computing, … and more! 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.
Our most important courses
These are the most important courses we recommend to new users:
These are other quite important courses we have developed:
Linux shell <https://aaltoscicomp.github.io/linux-shell/> Python for Scientific Computing <https://aaltoscicomp.github.io/python-for-scicomp/> Data analysis workflows in Python and R <https://aaltoscicomp.github.io/data-analysis-workflows-course/>
Other interesting courses
Data management, Reproducibility, open science
Other relevant courses by Aalto Open Science team will be listed at: https://www.aalto.fi/en/services/training-in-research-data-management-and-open-science
Other courses on scientific computing and data management
MOOC on scientific computing:
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.