SaC3

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.

Puno 2022
Lago Titicaca, Puno, Peru, 2022. Eigenens Bild.

Date and location

Universidad Nacional Agraria La Molina and Universidad de San Marcos, Lima, Peru
August, 2025.

Auditorio A2 – Escuela de Posgrado, 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

08:00 – 10:00: Registration and Opening
10:00 – 11:00: Theoretical: The QR Decomposition
11:00 – 11:30: Coffee Break
11:30 – 12:30: Theoretical: The QR Decomposition for Overdetermined Systems
12:30 – 14:00: Lunch Break
14:00 – 15:30: QR Decomposition in Python
15:30 – 16:00: Coffee Break
16:00 – 17:00: QR Decomposition in Python (cont.)
Tuesday
09:00 – 10:30: Theoretical: Conjugate Gradient Method
10:30 – 11:00: Coffee Break
11:00 – 12:00: Theoretical: Conjugate Gradient Method (cont.)
12:00 – 14:00: Lunch Break
14:00 – 15:30: Python: Conjugate Gradient Method
15:30 – 16:00: Coffee Break
16:00 – 17:00: Python: Conjugate Gradient Method (cont.)
Wednesday
09:00 – 10:30: Theoretical: Eigenvalue Problems
10:30 – 11:00: Coffee Break
11:00 – 12:00: Theoretical: Eigenvalue Problems (cont.)
12:00 – 14:00: Lunch Break
14:00 – 15:30: Python: Eigenvalue Problems
15:30 – 16:00: Coffee Break
16:00 – 17:00: Python: Eigenvalue Problems (cont.)
Thursday
09:00 – 10:30: Theoretical: Principal Component Analysis
10:30 – 11:00: Coffee Break
11:00 – 12:00: Theoretical: Principal Component Analysis (cont.)
12:00 – 14:00: Lunch Break
14:00 – 15:30: Python: Principal Component Analysis
15:30 – 16:00: Coffee Break
16:00 – 17:00: Python: Principal Component Analysis (cont.)
Friday
10:00 – 16:00: Workshop (Details to follow)

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

Local organizers from the Universidad de San Marcos
  • 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 under here .

Contact

Thomas Richer at Otto von Guericke University Magdeburg thomas.richter@ovgu.de.

Last Modification: 2025-08-04 - Contact Person: thomas.richter@ovgu.de - Impressum
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Contact

SaC3 is a DAAD funded project between several universities from Germany and Latin America. The spokesperson of the consortium is Thomas Richter at the Otto von Guericke University Magdeburg.

You reach us best by mail thomas.richter@ovgu.de.

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