This course is delivered entirely as an online course. Participants are expected to connect using their own computers and to follow along with hands-on exercises during the sessions. A stable internet connection, webcam, and microphone are recommended for interaction and support.

We will be working on the JupyterLab environment provided by the Gauss Centre for Supercomputing (GCS) Portal: https://portal.gauss-centre.eu/

Python has become the programming language of choice in scientific computing, AI, and data-driven research. This refresher course is aimed at users who have a basic working knowledge of Python and want to strengthen their skills before moving on to more advanced training in areas such as machine learning, workflow automation, and accelerated computing.

Over five interactive online sessions, participants will revisit core Python concepts, explore practical tools for modern development, and gain exposure to the scientific Python ecosystem. The course will conclude with an introduction to parallel computing using Python tools that are compatible with HPC environments.

The course is designed to be hands-on and interactive, with each session combining short presentations, coding demonstrations, and practical exercises.

The five sessions cover the following topics:

1. Core Python: Fundamentals

Python syntax and data types
Variables, control flow, and functions
Lists, dictionaries, sets, and tuples
File I/O and scripting basics

2. Core Python: Advanced

Comprehensions and lambda functions
Exception handling
Object-oriented programming concepts
Decorators & Generators and type hints

3. Python Tooling

Conda environments
Packages and modules
Writing clean, testable code
Profiling and timing

4. Scientific Python

Array operations with NumPy
Data wrangling using pandas
Plotting with matplotlib and seaborn
Introduction to scikit-learn

5. Parallel Computing and Accelerated Python

CPU-bound vs I/O-bound Tasks
Using multiprocessing for parallel tasks
Just-in-time compilation with Numba
Acceleration with Cython

This course prepares participants for more specialised topics, such as those covered in the LRZ AI Training Series, and helps build confidence in using Python effectively for research and development workflows.

Prerequisites

A basic understanding of Python is expected, including familiarity with running scripts, working with data structures, and using simple functions and control flow.

Hands-On

Each session includes live coding demos and guided hands-on exercises to help reinforce learning outcomes and prepare participants for real-world tasks at LRZ or in their own institutions. Hands-on sessions will be provided through the Gauss Centre for Supercomputing (GCS) portal: https://portal.gauss-centre.eu/

Content Level

The content level of the course is broken down as:

Beginner's content:	0,30h	8%
Intermediate content:	1,30h	24%
Advanced content:	2,30h	40%
Community-targeted content:	1,45h	28%

Language

English

Lecturers

Dr. Birkan Emrem (LRZ)

Prices and Eligibility

The course is open and free of charge for people from academia and industry from the Member States of the European Union (EU) and Associated Countries to the Horizon 2020 programme.

Registration

Please register with your official e-mail address to prove your affiliation.

Withdrawal Policy

See Withdrawal

Legal Notices

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Online Course	Modern Python in Depth - From Fundamentals to Acceleration
Number	hpyt1w25
Available places	23
Date	28.01.2026 – 28.01.2026
Price	EUR 0.00
Location	ONLINE
Room
Registration deadline	21.01.2026 23:59
E-mail	[email protected]

No.	Date	Time	Trainer	Location	Room	Description
1	28.01.2026	10:00 – 18:00	Birkan Emrem	ONLINE		Lecture

Modern Python in Depth - From Fundamentals to Acceleration

Contents