Preliminary schedule
Time |
Topic |
Content |
Teacher(s) |
|---|---|---|---|
9:00 |
Introduction to the course, log in, load/run Python, find packages |
Getting started with practical things |
All |
9:55 |
Coffee |
||
10:10 |
Install packages and isolated environments |
Install, create and handle |
Björn |
11.00 |
Short leg stretch 10m |
||
10:40 |
Reaching compute nodes with Slurm (70) |
Batch jobs vs interactive work in IDEs |
Birgitte |
~~11:50~~ |
Catch-up time and Q/A (no recording) |
||
12:00 |
LUNCH |
||
13:00-14:45 |
Analysis with Python (90m) |
Matplotlib, IDEs and plots from scripts |
Rebecca |
13.55 |
Short leg stretch 15m |
||
14.45 |
Coffee 15 min |
||
15.00 |
Using GPUs for Python (30m) |
Birgitte |
|
15:30 |
Summary + Q/A Evaluation |
||
~15.50 |
Use cases and Q/A |
Bring your own problems |
All |
Time |
Topic |
Content |
Teacher |
|---|---|---|---|
9:00 |
Analysis with Python part I (50) |
Pandas |
Rebecca |
9:50 |
Coffee |
||
10:05 |
Analysis with Python part II (50) |
Pandas & Seaborn |
Rebecca |
10.55 |
Short leg stretch |
||
11:10 |
Parallelism part I: MPI, Processes, Dask |
Processes, MPI |
Pedro |
12:00 |
LUNCH |
||
13:00 |
Big Data with Python (35) |
File formats and packages, Chunking |
Björn |
13:50 |
Short leg stretch |
||
14:05 |
Machine and Deep Learning part I (50) |
Pytorch, Tensorflow, ScikitLearn |
Jayant |
14.55 |
Coffee |
||
15:10 |
Machine and Deep Learning part II (40) |
Pytorch, Tensorflow, ScikitLearn |
Jayant |
15.50 |
Short leg stretch |
||
16.00 |
Summar and Q&A and avaluation |
||
16.20 |
Use cases and Q&A |
Bring your own problems |
All |
16.45 |