Summer School and Workshop on Numerical Linear Algebra
As event of SaC3 we organize a summer school and conference at the Universidad Nacional Agraria La Molina and the Universidad de San Marcos in Lima, Peru. School and workshop will take place from August 18-22, 2025.
Date and location
Universidad Nacional Agraria La Molina and Universidad de San Marcos, Lima, Peru
August, 2025.
Auditorio de la Facultad de Zootecnia - UNALM
Registration and call for papers
Registration is closed as we already got a very large number of applicants.
Due to the very large number of applications, a selection of participants will take place.
Preliminary program
Monday
Organizers
Coordination
Local organizers from the Universidad Nacional Agraria La Molina
- Dr. Dandy Rueda Castillo
- Mg. Alessandri Canchoa Quispe
- Mg. Rocío Consuelo Delgado Aguilar
- Mg. Aldo Mendoza Uribe
- Mg. Jorge Condeña Cahuana
- Dra. Raquel Serna Díaz
- Mg. Edgar Santisteban León
- Mg. Alfredo Velasquez Flores
- Dr. Renato Benazic Tomé
- Mg. Emma Cambillo Moyano
- Dra. Roxana López Cruz
Responsible Lecturers for the Summer School from the Otto von Guericke University Magdeburg
- Celine Reddig
- Jochewed Schmeck
- Jonathan Irmscher
- Joris Edelmann
- Medard Govoeyi
- Saskia Kahl
Python classes
The Python exercises will be carried on using its powerful ecosystem of scientific computing libraries, including:
- NumPy: For numerical computations and array operations.
- SciPy: For scientific computations, including ODE solvers.
- Matplotlib: For visualisation.
- Scikit-learn: For statistical learning.
Using JupyterLab for Programming
Throughout this course, we will use JupyterLab as a programming tool. JupyterLab provides an interactive environment for writing and running Python code. We highly recommend installing it in your Python environment. Please, follow the installation instructions of the official JupyterLab website. Google Colab provides an alternative. If you choose to work with Google Colab, be aware: It needs a stable internet connection.
Our experiences
We have good experiences using virtual environments in Visual Studio Code. The following instructions were tested on MacOS and Ubuntu (24.04).Step-by-step guide using virtual environments
This guide assumes that a bare python installation exists on your system, and will set up a venv for the workshop.
- Install VSCode or VSCodium
- Open the project and install the recommended extensions (Jupyter, Jupyter Notebook, Python)
- Installing dependencies (here, using Pythons virtual environments functionality)
Create a virtual environment:
python3 -m venv path/to/venv
source path/to/venv/bin/activate
python3 -m pip install ipykernel # Required for interactive compilation
ipython kernel install --user --name=workshop
- Restart VSCode, open this notebook, and choose the new Jupyter environment as compiler in the top-right
- Install the other required packages
Enter the virtual environment again:
source path/to/venv/bin/activate
python3 -m pip install numpy scipy matplotlib scikit-learn
To test your setup, you'll find a script in the matrials folder.
Materials
All materials are published here .Contact
Thomas Richer at Otto von Guericke University Magdeburg thomas.richter@ovgu.de.