Go to homepage
Find educational resourcesKnowledge & expertiseCommunities
NL|EN
Privacy policyParticipating institutions
Creative CommonsCreative Commons AttributionSURFFunded by the European Union

Filter

Search results (153)

…

HBO/WO

MBO

February 3, 2021

A short introduction to Python

Python tutorial.

University, UASDocument

Aniel Bhulai

August 25, 2025

Python handbook for engineering students

This book offers a concise and practical introduction to Python programming, specifically tailored for Electrical Engineering students. It begins with the fundamentals to help readers get started, covering essential concepts such as variables, operations, control structures, and plotting. As the material progresses, students are introduced to core topics in numerical computation and the basics of signal processing using powerful Python libraries such as NumPy and SciPy. To support learning, the book provides numerous clear examples and an optional step-by-step guide designed to help readers work through the material at their own pace. This structured approach makes it easy for beginners to build confidence and develop practical coding skills. Designed as a fast and accessible entry point, the book equips students with the programming foundation needed to support and enhance their learning in other engineering courses.

Open (Access) Text Book

Bahareh Abdi

May 24, 2024

Workshop material Power of Python for GIS

This workshop introduces a set of tools for geospatial data handling and vizualization using Python. The workshop targets beginning python programmers or people with no Python experience that want to learn about all the possibilities of Python. The workshop will mostly be a demonstration of the power of Python for various tasks such as accessing and handling satellite data, processing raster/vector data and visualization. You will also be provide with python code to perform the same steps on your own laptop. The workshop is given by the Geo Data team from faculty of Geosciences and UU Research Engineering, both from Utrecht University. The material contains a Github repository with workflows, playbooks, data and notebooks, a Zenodo publication with presentation slides and sample data and a Github repository with a template for Jupyter workshops

Website

Garrett Speed, Aristotelis Kandylas, Jelle Treep

2023

Lecture Notes chapter 2: Introduction to Python Programming

This "Maker Lab" course uses Jupyter Notebook files and the Python programming language for data analysis and visualization and uncertainty analysis. Chapter 2 of the lecture notes introduces the Python programming language. It consists of four sub-chapters, each published as separate files. Note: If you do not (yet) have Jupyter Notebook, you cannot fully utilize these .ipynb files. But the attached PDFs will give an idea of their content and functionality. Note also: In order to interact with and fully utilize the Jupyter Notebook documents (including their hyperlinks and pointers to data and image files), it is helpful to save the entire collection locally in a way that preserves the original directory structure. This is easiest to accomplish by downloading all files at once via the JupyterPython-materials zip file and unpacking it (extracting the files) to your preferred local directory. This zip file of all Jupyter Notebook materials is located here: https://search.edusources.nl/materialen/d144774e-9705-489a-b3cd-28e3618f7324

Document

Forrest Bradbury

July 2, 2025

Intro to python programming

Learning Outcomes for Python Programming Modules 1. Develop and Document Python Code in Jupyter Notebooks Learners will create, document, and execute Python code using Jupyter Notebooks, effectively utilizing Markdown for readable and well-structured analysis. 2. Understand and Apply Python Data Types and Operations Learners will identify and manipulate core Python data types, perform data operations, and utilize comprehensions for efficient data processing. 3. Implement Program Logic and Functions Learners will control program flow using conditionals and loops, encapsulate logic within functions, and handle errors using Python’s exception mechanism. 4. Read, Write, and Process Data Files Learners will read from and write to files, apply regular expressions for text processing, and leverage core library functions for common data tasks. 5. Apply Object-Oriented Programming and Prepare for Data Analysis Learners will design and use classes, including data classes, and set up a Python environment with (Ana)conda, preparing to work with data analysis libraries such as pandas. Consists of 18 lessons (5EC).

Website

Michiel Noback

September 11, 2019

The Medieval Podcast | Monty Python and the Holy Grail

It may be the most famous medieval movie of all time. This week, Daniele talks with Peter Konieczny about Monty Python and the Holy Grail, its legacy, and some of their favourite moments. This podcast is made possible by the generous support of listeners like you! To find out how to help spread the joy of medieval history, please visit patreon.com/themedievalpodcast

Audio

Danièle Cybulskie, Peter Konieczny

September 5, 2020

1.2. Python for beginners

This publication contains two videos about Python for beginners created by Aniel Bhulai, senior lecturer Computer Sciences at the Vrije Universiteit Amsterdam. In this video, a short introduction to Python is given. Especially for those who don’t know anything about Python, this is a quick start. The video consists of two parts. In this part, you will learn what Python is, how to use Python, what operators, strings, and variables are. In this second part of the quick start of Python for beginners, you will learn what data types are, you will also learn what conditions, loops, and functions are.

Video

Aniel Bhulai

December 5, 2021

Python package for building isosurfaces from 3D scalar fields

Python package for building isosurfaces from 3D scalar fields Python package for evaluating integrals of Gaussian type orbitals in electronic structure calculations

Website

Ivo Filot

2023

Maker Lab Assignment: Programming and Data Analysis: Python Exercises

Before the Maker Lab students begin the open inquiry phases, they first learn and practice some important skills, supported by small assignments. In this assignment they are tasked with using a worksheet in Jupyter Notebook and the Python programming language for data analysis and visualization and uncertainty analysis of a provided data set. The analyzed data set is generated quickly via an online survey completed by all students. Note: If you do not (yet) have Jupyter Notebook, you cannot fully utilize the .ipynb file. But the attached PDF will give an idea of its content and functionality. Contents: student worksheet in Jupyter Notebook: Programming-and-DataAnalysis_Python-Exercises.ipynb (and .pdf) instructor link to Google Forms survey for data collection: https://docs.google.com/forms/d/e/1FAIpQLSfWsdadhq-v3ubt1p3EIkzxAVyAyQ-1hBYst_RodV7PEp9E7A/viewform?usp=sharing example of data file: example_Data_Collection_For_Python_Exercises.csv

Document

Forrest Bradbury

February 22, 2021

Python package for calculating one- and two-electron integrals

PyQInt is a Python package for calculating one- and two-electron integrals as encountered in electronic structure calculations. Since integral evaluation can be quite computationally intensive, they are programmed in C++ and connected to Python using Cython.

Website

Ivo Filot