Important links:
You will be able to access the class published in Google Colab here
Scientific Computing in Python : Online class, July 14 - 16 and 21 - 22, 2022 (in Spanish)
4 Events in the Peruvian spring
- We organize an online Python course from July 14 - 16 and July 21 - 22.
- We offer an online course on finite elements from August 4-6 and 11-13, 2022.
- From September 26 - September 30 the Spring School on Scientific Computing takes place in Cusco, Peru.
- In the week following the spring school, the Universidad Nacional de San Antonio Abad del Cusco will host the Peruvian conference on Scientific Computing, October 3 to October 6.
Content of the course
Prior to the Peruvian-German Spring School and Conference on Scientific Computing, this introductory course on scientific computing implemented in the Python programming language will be offered. During the course attendees will learn about the Python programming language and the many tools it provides to assist scientists in their research. Python is currently one of the most popular languages for being high-level, easy to use, interpreted and its flexibility of interaction with other high-performance languages such as C++ among other aspects. First an introduction to the syntax, data structures, control structures and method creation in Python language will be given. Afterwards, the module Numpy will be presented. This library brings tools for vector and matrix operations and other numerical procedures. At the same time the module scipy will be shown. The focus will be on linear algebra and ordinary differential equations solvers, numerical integration and optimization methods and other numerical methods which are implemented in these two libraries. Finally, Matplotlib module for rendering scientific figures and graphs will be presented. The dynamic of the course is based on "learning by doing". Each class is prepared to have small talks, demonstrative Python implementations and coding challenges for the attendees. One small task will be assigned to each of you that must be carried out by yourselfs and uploaded to the website. Each task aims to consolidate the knowledge obtained during the course. Then you will have the suggestions and corrections from the teacher on how to improve it. The demonstrations and your implementations in Python will be mainly carried out in the platform Google Colab. It allows you to write and execute Python in your own browser with no additional configuration required, access to computational resources free of charge and easy sharing.
Registration
Registration is closed!
Online Access
The classes will be held online using the platform Zoom. The link to the platform are already available for all registered participants in the events listed in the calendar.
The access code to the virtual room will be send to each participant soon.
Program
Dates for each class can be found in the following calendar:
You could also download the calendar in this link.
Course materials
Lecture #1: - Introduction to Python programming
Lecture #2, #3: - Handling vectors and matrices in Python: Numpy Module
Lecture #4: - Linear Algebra
Lecture #5: - Ordinary differential equations
Projects
You will be able to evaluate yourself by solving one of the two problems presented in the following projects:- Project A: Heat equation. Download documentation (pdf).
- Project B: Lorenz equation system. Download documentation (pdf).
Deadline for projects
The deadline for submission of projects is July 31, 2022 at 11:59pm Peru time.
IMPORTANT: The delivery of the projects is NOT by e-mail. For this purpose another form will be enabled for you to upload your files or indicate the address of the Google Colab spreadsheet where you developed the solutions.
Upload projects
You will be able to upload your project solution through the link upload form.
There will be two ways to send it. The first one will be to compress all the files that make up your solution in a single .zip file. In the second variant you will be able to implement your solution in Google Colab and share it directly through the url of the link. In the form header you will find you will find more indications on how to perform both processes.
Examples of project solutions
Below you will find examples of solutions for both projects:
- Project A: Heat equation: Solution by Mr. Gerardo Rivera Tello, UNMSM Perú (Google Colab sheet).
- Project B: Lorenz system of equations. Solution by Mr. Paolo Flores Cóngora, UNMSM Perú (Google Colab sheet).
Lecturer
The course was taught by M.Sc. Dayron Chang Dominguez, researcher of the Institute for Analysis and Numerics from Otto-von-Guericke University, Germany.Contact
For all questions regarding this Python course do not hesitate to contact Dayron Chang Dominguez.
