Schedule

Course dates

The 4-day version of this course is scheduled twice a year. The 1-day version of this course is scheduled an additional two times a year

Week	Day	Date	Time	Description
17	Monday	2026-04-20	9:00 (sharp) to 16:00	Day 1: Log in and use basic Python in a cluster environment
17	Wednesday	2026-04-22	9:00 (sharp) to 16:00	Day 2: Packages, environments and using compute nodes
17	Thursday	2026-04-23	9:00 (sharp) to 16:00	Day 3: Basic analysis, Big Data and Batch jobs
17	Friday	2026-04-24	9:00 (sharp) to 16:00	Day 4: Parallelism, GPUs, and machine learning

Week	Day	Date	Time	Description
?42	?	2026-?-?	9:00 (sharp) to 16:00	Day 1: Log in and use basic Python in a cluster environment

Week	Day	Date	Time	Description
?48	?	2026-?-?	9:00 (sharp) to 16:00	Day 1: Log in and use basic Python in a cluster environment
?48	?	2026-?-?	9:00 (sharp) to 16:00	Day 2: Packages, environments and using compute nodes
?48	?	2026-?-?	9:00 (sharp) to 16:00	Day 3: Basic analysis, Big Data and Batch jobs
?48	?	2026-?-?	9:00 (sharp) to 16:00	Day 4: Parallelism, GPUs, and machine learning

Day 1: Log in and use basic Python in a cluster environment

Course starts at 9:00 sharp and ends at 16:00

Course starts at 9:00 sharp and ends at 16:00

See schedule at NAISS ‘Intro to Python for HPC’.

Day 2: Packages, environments and using compute nodes

Time	Topic	Teacher
09:00-9:50	Introduction	Richèl Bilderbeek
	Using packages	Richèl Bilderbeek
9:50-10:05	Break	.
10:05-10:55	Install packages	Björn
	Use isolated environments	Björn
10:55-11:10	Break	.
11:10-11:30	Use isolated environments	Björn
11:30-12:00	Basic batch/Slurm	Birgitte
12:00-13:00	Break	.
13:00-13:20	Interactive (terminal/onDemand)	Birgitte
13:20-13:50	Starting IDEs from command line	Bjorn
13:50-14:05	Break	.
14:05-14:40	Starting IDEs from onDemand	Rebecca
14:40-14:55	Using IDEs	Jayant
14:55-15:10	Break	.
15:10-15:45	Using IDEs	Jayant
15:45-16:00	Evaluation	Björn

Day 3: Basic analysis, Big Data and Batch jobs

Course starts at 9:00 sharp and ends at 16:00

Course starts at 9:00 sharp and ends at 16:00

Time	Topic	Teacher
09:00-10:00	Pandas	Richèl Bilderbeek
10:00-10:15	Break	.
10:15-11:00	Matplotlib	Richèl Bilderbeek
11:00-11:15	Break	.
11:15-12:00	Matplotlib, Seaborn	Richèl Bilderbeek
12:00-13:00	Break	.
13:00-13:50	Big data with Python	BC
13:50-14:05	Break	.
14:05-14:55	Big data with Python, batch	BC, BB
14:55-15:10	Break	.
15:10-15:45	batch	BB
15:45-16:00	Evaluation	.

Day 4: Parallelism, GPUs, and machine learning

Course starts at 9:00 sharp and ends at 16:00

Course starts at 9:00 sharp and ends at 16:00

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	GPUs	Birgitte
12:00-13:00	Break	.
13:00-14:00	ML/DL	Jayant
14:00-14:15	Break	.
14:15-14:45	ML/DL	Jayant
14:45-15:00	Break	.
15:00-15:45	ML/DL	Anders Hast
15:45-16:00	Evaluation	.