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Zoekresultaten (17)

HBO/WO

MBO

2023

Lecture Notes chapter 1: Introduction to Jupyter Notebook and Markdown

This "Maker Lab" course uses Jupyter Notebook files (and the Python programming language) for data analysis and visualization and uncertainty analysis. Chapter 1 of the lecture notes introduces the Jupyter Notebook platform. 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. 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

29 maart 2022

Interactive worksheets as a resource for teaching building performance and energy systems simulation

Jupyter Notebooks that are used as interactive worksheets for the course 7LY3M0 - Building performance and energy systems simulation.

Document

Roel Loonen

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

2023

Lecture Notes chapter 3: Uncertainty Analysis

This "Maker Lab" course uses Jupyter Notebook files and the Python programming language for data analysis and visualization and uncertainty analysis. Chapter 3 of the lecture notes introduces Uncertainty Analysis using Python. 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. 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

2023

Lecture Notes chapter 5: Fourier Transform

This "Maker Lab" course uses Jupyter Notebook files and the Python programming language for data analysis and visualization and uncertainty analysis. Chapter 5 of the lecture notes introduces the discrete Fourier Transform using Python. This lecture notes document is presented in the Maker Lab course as optional reading, but sometimes relevant to students with projects involving (for example) signal analyses in the temporal frequency domain. 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. 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

2023

Lecture Notes chapter 4: Curve Fitting

This "Maker Lab" course uses Jupyter Notebook files and the Python programming language for data analysis and visualization and uncertainty analysis. Chapter 4 of the lecture notes introduces Curve Fitting using Python. In fact, one of these documents covers Curve Fitting using two different Python libraries (lmfit and scipy), however, the lmfit library is the recommended one for the Maker Lab course, as it's more user-friendly and covers most uses needed by the student projects. Thus, the other document cuts out the scipy library explanations, keeping the document shorter and easier to follow. 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. 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

2023

Maker Lab complete set of JupyterPython-materials zip file

This a zip file of all the course's Jupyter Notebook documents, bundled together here for the convenience of anyone wanting to use them within Jupyter Notebook*. The Maker Lab course uses Jupyter Notebook documents in several ways: for Readings for Students (specifically the "lecture notes") and for Assignments (both descriptions and templates). These individual files are found in the relevant pages here on Edusources - and also shared in PDF form so that they can be viewed without using Jupyter Notebooks. However, in order to interact with and fully utilize the Jupyter Notebook documents (including their hyperlinks and pointers to data and image files), it is best 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 this JupyterPython-materials zip file and unpacking it (extracting the files) to your preferred local directory. *Note: there is a text file within this zip file with instructions for installing Python and Jupyter Notebook.

Document

Forrest Bradbury

24 mei 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

Maker Lab Lecture Notes

This collection of the Maker Lab's Lecture Notes (alongside the Lecture Sldies and several Assignments files) detail some of the learning material and activities that prepare students for the open inquiry phases. Specifically, students learn to use Python for data analysis & visualization and uncertainty analysis, and are given an overview into the processes of empirical research in the natural sciences. Note: These Lecture Notes files are written as Jupyter Notebooks, often containing interactive features (though static PDFs are also provided for the benefit of non-users of Jupyter Notebooks). It is possible and convenient to download all of the Maker Lab's Jupyter Notebook files at once via the JupyterPython-materials zip file - 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

Forrest Bradbury

23 augustus 2023

Practical: Platforms

To be able to use jupyter notebooks To be able to use basics of Python (variables, lists, strings, tuple) To be able to use basics of pandas (data loading from csv, data lookup)

Website

HCAIM Consortium