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Previous courses

This shows a list of previous courses given by NAISS, how often they are normally given, as well as links to material and recordings (if available). Click the course link for more information and material.

Given 4/year

All are ½ day or full day

Course Next instance Recordings Comments
Connecting and transferring files to/from HPC clusters https://uppmax.github.io/naiss_file_transfer_course/videos/ Part of NAISS intro week/intro day
Introduction to using GPUs and AI/ML Part of NAISS intro week/intro day
Handling sensitive data at NAISS See course webpage Part of NAISS intro week/intro day
Linux Command Line 101 https://youtube.com/playlist?list=PL6jMHLEmPVLz7nfvCupvR-SX6MlFwboS8&si=Au9615epuiJnA0mn
Linux Command Line 201 https://uppmax.github.io/linux-command-line-201/videos/
Running jobs on clusters https://www.youtube.com/playlist?list=PL6jMHLEmPVLx2Cx1nfUggMfDLuahQEaBW Part of NAISS intro week/intro day
Selecting Software Modules https://www.youtube.com/playlist?list=PL6jMHLEmPVLyU5ELJh8zfu5VwjtR3Y-XV Part of NAISS intro week/intro day

Given twice a year

Course Next instance Recordings Comments
AWK workshop (2 days)
CodeRefinery Tools Workshop (automated testing, Jupyter, advanced Git) (9 days) March 17-19 and 24-26, 2026
Introduction to Python (1 day)
Programming Formalismshttps://uppmax.github.io/programming_formalisms/) (5 days)
Running and building Singularity and Apptainer containers (1 day)

Given once per year

Course Next instance Recordings Comments
Array computing in C++ using Eigen (1 day) 2026-03-05
DDT: Debugging of HPC applications (1 halfday)
Introduction to Git (5 halfdays) fall 2026 https://www.youtube.com/playlist?list=PL6jMHLEmPVLyYXYmJL7WXF-Bg6q0-3j6d
Introduction to Pandas for data science (2 halfdays) 2026-03-(10-11) https://www.youtube.com/watch?v=s-ascKrq4b8&t=11s
Introduction to parallel programming with MPI (4 halfdays)
Introduction to Python and Using Python in an HPC environment (4 days) https://www.youtube.com/playlist?list=PL6jMHLEmPVLwP48-tVEiMyJbPuNrnmh-o
Introduction to running R, Julia, and Matlab in HPC (4 days) https://www.youtube.com/playlist?list=PL6jMHLEmPVLyPX1imItZ_3_pTrNhxbm-i
LLM Workshop (3 days)
Matplotlib for Publications (2 days)
Python for Scientific Computing (3 halfdays)
Using ParaView for Scientific Visualisation on HPC resources (1 halfday)
VASP Best Practices (1 halfday)

Previously given & suggestions

  • An introduction to shared memory programming using OpenMP
  • Snakemake workshop
  • Build systems workshop