Preliminary schedule
Course dates:
Week |
Date |
Description |
|---|---|---|
17 |
Wednesday 2025-04-23 |
(optional) On-boarding |
17 |
Thursday 2025-04-24 |
Day 1: NAISS ‘Intro to Python’) |
17 |
Friday 2025-04-25 |
Day 2 |
18 |
Monday 2025-04-28 |
Day 3 |
18 |
Tuesday 2025-04-29 |
Day 4 |
Day 1: Log in and use Basic Python in a cluster environment
See schedule at NAISS ‘Intro to Python’).
!!! tip “Course starts at 9:00 sharp and ends at 16:00”
Day 2: Use and install packages with pip and conda in virtual environments and doing basic analysis interactively
!!! tip “Course starts at 9:00 sharp and ends at 16:00”
Time |
Topic |
Teacher |
|---|---|---|
09:00-10:00 |
Packages |
Björn+Richel (co-teaching) |
10:00-10:15 |
Break |
. |
10:15-11:00 |
Isolated environments conda/pip |
Björn+Richel (co-teaching) |
11:00-11:15 |
Break |
. |
11:15-12:00 |
Basic Slurm and interactive, ?OnDemand,?parallel session |
Birgitte |
12:00-13:00 |
Break |
. |
13:00-14:00 |
IDEs: Jupyter/vscode/Spyder [1] |
Jayant |
14:00-14:15 |
Break |
. |
14:15-15:00 |
matplotlib 1/2 |
?Rebecca, else Björn |
15:00-15:15 |
Break |
. |
15:15-15:45 |
matplotlib 2/2 |
?Rebecca, else Björn |
15:45-16:00 |
Evaluation |
. |
[1] Spyder only works on LUNARC, for an old version. Using virtual environments may get this to work on other session. Björn will investigate this :+1:
Day 3: Deeper analysis with pandas and seaborn, HPC usage with big data, parallelisms and Machine Learning with and without GPUs.
!!! tip “Course starts at 9:00 sharp and ends at 16:00”
Time |
Topic |
Teacher |
|---|---|---|
09:00-10:00 |
Pandas |
?Rebecca |
10:00-10:15 |
Break |
. |
10:15-11:00 |
Pandas (enough time?) |
?Rebecca |
11:00-11:15 |
Break |
. |
11:15-12:00 |
Seaborn (enough time)? |
?Rebecca ?Björn |
12:00-13:00 |
Break |
. |
13:00-14:00 |
Slurm and batch jobs |
Birgitte |
14:00-14:15 |
Break |
. |
14:15-15:00 |
Formats and Big data |
Björn (more time than earlier) |
15:00-15:15 |
Break |
. |
15:15-15:45 |
Formats and Big Data |
Björn |
15:45-16:00 |
Evaluation |
. |
Day 4: Deeper analysis with pandas and seaborn, HPC usage with big data, parallelisms and Machine Learning with and without GPUs.
Time |
Topic |
Teacher |
|---|---|---|
09:00-10:00 |
Parallelism |
Pedro |
10:00-10:15 |
Break |
. |
10:15-11:00 |
Parallelism |
Pedro |
11:00-11:15 |
Break |
. |
11:15-12:00 |
GPU, batch jobs |
Birgitte |
12:00-13:00 |
Break |
. |
13:00-14:00 |
ML/DL |
Jayant |
14:00-14:15 |
Break |
. |
14:15-15:00 |
ML/DL |
Jayant |
15:00-15:15 |
Break |
. |
15:15-15:45 |
ML/DL |
Jayant + Anders Hast |
15:45-16:00 |
Evaluation |
. |