- material: https://uppmax.github.io/HPC-python/index.html
- source: https://github.com/UPPMAX/HPC-python/tree/main/docs
None decided at the time of writing
Course dates:
- 2026-04-20
- 2026-04-22
- 2026-04-23
- 2026-04-24
Present:
- Birgitte
- Björn
- Jayant
- Pedro
- Richel
- Talk about evaluations
- Next iteration
General: large spread in confidence: - Always some that have high confidence and at least 1 that jave no idea even though attending - Discuss Goal: Have more "High" or less "low" or do we have to have "both"? - RB: I think a teacher may aim for 'high', but as far as I have searched the literature, I could not find a relation between this value and course quality, hence I ignore this value completely. I've only informally observed it to correlate to the day of the course (it decreases per day). The only value I see in self-assessed confidence is that there is less literature against it: course satisfaction has been more strongly proven to be useless to assess couse quality.
- Maybe, if our learners are new to Python, only follow Day 1?
- We are discussing different topics during the day. Without knowing everything, can they finish the course? I think that will be challenging
- Maybe we should make it clear what the level is of the different parts?
- Let us clarify what the level is of the different topics!
- Day 2 summary
- Day 2 full evaluation
- Least confidence: virtual envs, IDEs, interactive, install
- RB: as far as I've read about evaluations by learners, there is no use to compare the results (i.e. confidences) between sessions or teachers: only a teacher teaching the same session multiple times may think it is useful to see this number change
- Least confidence: virtual envs, IDEs, interactive, install
- Most problems with Dardel users
- The afternoon was split up differently this time
- Day 3 summary
- Day 3 full evaluation
- Least confidence: Formats Big data, Seaborn, Work inside Pandas
- Most problems with Dardel users
- We can point more to the NBIS courses on analysing big data
- We can point more to other courses in general
- Day 4 summary
- Day 4 full evaluation
- Least confidence: parallelization, GPU, Tensorflow
- Maybe some learners will only join on Day 4, hence they may not have installed an ML virtual environment as done on Day 3. We adapt by the Day 4 courses by starting with a 'do this' (i.e. create the virtual env), then talk, then use the virtual env
- Should we add an Intermediate or Advanced Python Day? It is a lot of work and we expect to few learners to make it worth it. We seem to be leaning to a no. Instead, we could point more to other advanced courses
- We consider to make more connected exercises here
- We will make it more clear that they can get a course certificate for the days they attended
-
Keep day 1 outside or keep as refresher?
- Refresher/prerequisite
-
Should we extend the course by 1 more day? It is often mentioned in the evaluations. Some of us think we definitely should do so. - [DECIDED] Yes: BB, PO, JY - Neutral: BC - No: RB
-
If we extend the course, we can schedule these days over more weeks
- One week: RB, BB
- [DECIDED] Two weeks: BC (), BB, JY, RB, PO
- Three weeks:
-
There are many problems with Dardel. Can we use Arrhenius and if yes, should we focus om it?
- Arrhenius will be main course project
- Tetralith: will be decomissioned
- Alvis: decomissioned or local (the hardware will be reused someplace or sold: we don't know :-)
- Dardel up until Dec (at least)
- Arrhenius will be main course project
-
Point more to other courses
-
, prereqs etc
-
Follow up in August/September,
-
Should we give this course in autumn yes/no?
- Yes: BC, RB, BB
- Neutral:
- No:
-
How often should we give this course? Maybe once a year, yet, due to the new HPC cluster Arrhenius, we should have an extra course to help these new Arrhenius uses
-
Should we transition to:
- NAISS GitLab
- Yes: BC
- Yes, but I would not do so if I would be boss: RB
- Neutral
- No
- Zensical
- Yes: BC, RB
- Neutral:
- No:
- NAISS GitLab
-
When should the next course be appoximately?
- November (after Matplotlib): BC, RB, BB, JY
- It has been put into the shared NAISS training planning 👍
Present:
- Birgitte
- Björn
- Jayant
- Pedro
- Richel
- Sahar
- Rebecca? Otherwise Sahar / Richel
- Get on track
- Go through evaluation
- Identify needed changes (if time)
- Available teachers
- Advertise and registrations
- Teachers available (a list can be found below)
- Evaluations
- Changes
- Sphinx --> Zensical
- GitHub --> Gitlab?
- Can learners make issues?
- Would it work if the repo is private for us?
- No! We need it for, e.g. downloading tarballs, allowing learners to submit a PR, etc.
- big picture
- Advertise and registrations
- 2026-04-20: Day 1: Richel
- 2026-04-22: Day 2: Richel's sessions go to Björn, Björn, Birgitte, Jayant, (Sahar)
- 2026-04-23: Day 3: ?Rebecca, Sahar as backup for Rebecca's sessions, Björn, Birgitte, Sahar
- 2026-04-24: Day 4: Birgitte, Jayant, Pedro
Misc:
- Birgitte will ask Joachim for status of Rebecca at the coordination meeting
- Very few answered: 4-5
- want more about COSMOS-SENS because little documentation at LUNARC
- practical management of Conda/virtual environments on HPC: we can attempt to put it back in
- Workflow systems like NextFlow or Snakemake: this is other courses
- We can consider adding 1 (all combined) or 3 (all separate) courses on workflows
- NBIS, however, has a course 'Tools for reproducible research'
- We'll leave it out for now
- I guess that Python, pandas, matplotlib and such could be prerequisites to the course and instead only focus on big data and HPC specifics
- The order is right: Day 1 teaches Python needed for Day 2, the Day 3 morning teaches the prerequisites for its afternoon
- We keep it as it is!
- The material is good, but the teaching technique is lacking.
- Richel started off very good with a lot of interaction, breakout rooms and time for questions and doing things yourself.
- Teachers decide on how to teach, as per usual
- I liked this and that the exercises were part of the teaching, not meant to do during breaks, then you would never get breaks
- There is the intention to add more time for exercises
- Richel started off very good with a lot of interaction, breakout rooms and time for questions and doing things yourself.
- Day 1 had 3 responses (38% fill-in rate)
- Success score: 90%
- Comments:
- It's very nice to be able to through everything at your own pace, and still receive help/feedback on where you are, independent of the rest of the group.
- The instructor was so helpful and friendly and helped me a lot in learning new stuff and solving issues I had during the day
- Great teaching!
- Great work with creating engagement
- Numbers answering: 4
- Success score: 82%
- Best confidence: Find & load / Install Python packages
- Lowest: Check if in interactive session
- This session is low on time (as is also mentioned by the learners)
- There needs to be taught too much different ways
- May fix itself when we have Arrhenius in the future
- Working group decides on how to split the time up better and will schedule a meeting: BC, BB, JY, (RP)
- Comments:
- Exercises were a bit less clear today, which ones we should do and when was a little confusing.
- Because each HPC has different setup it is a bit uninteresting to walk through them all when I'm only concerned with the one I'm using
- We feel we are doing this more already
- a little bit tight
- The time allocated isolated environments and launching IDEs from the command line did not seem adequate
- I and some other seemed to be lost already at OnDemand, and interactive work.
- So maybe you should make that session more interactive. Then it would have been easier to follow the other sessions after that.
- Numbers answering: 5
- Success score: 66%
- Best confidence: Create plots in matplotlib
- Lowest: Create plots in Seaborn
- May be a leftover from incomplete discussion on IDEs
- Comments:
- when you get stuck in setting things up you then also loose on the learning
- Overall a good setup of the course! It is hard to do the exercises because environments etc. has to be set, so I will have to go back later to finish.
- Demonstrating everything with actual code and a more hands-on approach would be essential to better understand the core concepts.
- Numbers answering: 4
- Success score: 52%
- Best confidence: Multiprocessing
- Lowest: Determine which ML/DL modules are installed at centre
- BC will try to make this better
- We will have InfraViz around again next time
- Comments
- a bit too fast for me to really learn by following examples, too uncertain with setting up environments, connecting etc
- People jump in on only Day 4, where the prerequisites (e.g. connecting) are taught earlier
- Suggest: for each day, have a link to the requirements of that day
- Maybe connection session in the morning? No, we tried this and nobody showed up.
- more on basic usage with nodes, set up Jupyter, environments, loading modules
- We assume he/she did not follow the earlier days ...
- a bit too fast for me to really learn by following examples, too uncertain with setting up environments, connecting etc
-
Sphinx --> Zensical
- Let's wait until the other courses have moved on, as there is also a GitHub --> GitLab move
-
GitHub --> GitLab
- Let's wait until the other courses have moved on, as there is also a Sphinx --> Zensical move
-
Big picture changes in lessons?
- NextCloud for registrations?
- Mostly yes: everything should be there
- Not for evaluations: Cannot use for evaluations with the version (of NextCloud) NAISS has now, as there is no checkboxgrid there. In the future we will move
- Birgitte will do the registrations in NextCloud
- Will there be a Zoom organisation for NAISS?
- That would be nice: so that we can add each other. It would make things much easier
- We are told: 'Maybe'. Maybe this is not all too soon ...
- Birgitte will keep asking for this
- Next course advertisement is next week
- Birgitte will do this :-)
- Change content in Ads?
- It is perfect!