In this repository you will find the lab assignments for the Data Science & AI course. The idea is that you make a copy of this repository (using the Github Classroom link you get during the first classes) and keep your own solutions in that repository.
BEWARE that your personal repository will be deleted after the end of this academic year, so be sure to always keep a local clone!
The repository is divided according to the different modules in the course. In each directory
you will find a README.md containing the assignments. The directory data/ contains all the
datasets you need (and don't have to download from the Internet).
In order to make the lab exercises, you can use the online Google Colab environment. The easiest way to get started with this is probably to download this repo as a ZIP file, unpack the contents on your local machine and upload them all to your Google Drive (under the directory Colab Notebooks). If your Google Drive doesn't have this directory yet, first create an empty Notebook on Colab (that you can later use to experiment or to keep scratch notes). Remark that files may be added or changed later! Be sure to check the commit history and reopen or redownload the newer versions of the files.
Alternatively, you can work locally on your own machine. In that case, you need to install the following software:
- Python
- Visual Studio Code, with extensions:
- Python, Pylance (Microsoft)
- Jupyter, Jupyter Keymap, Jupyter Notebook Rendering (Microsoft)
- Optionally: GitLens (GitKraken), Markdown All in One (Yu Zhang)
- Git & a Github-account
Create a local clone of this repository (or download as a ZIP) and open the directory in VS Code. VS Code will suggest to install any necessary extensions as soon as you open or create a Python or Jupyter Notebook file.
In the lab assignments, there are occasional references to sources. You can find a reference list here:
Akin, Ö. (2016) Performantie van persistentiemogelijkheden in Android. Bachelorproef. Hogeschol Gent.
Cochran, W.G. (1954). Some Methods for Strengthening the Common χ² Tests. Biometrics, 10(4), 417-451.
Ryan, et al. (1998) The effect of in-store music on consumer choice of wine. In: Proceedings of the Nutrition Society. 57(4), p. 169a.
Vanhaelewyn, B. & De Marez, L. (2016) Digimeter 2016. Onderzoeksrapport. Imec. Opgehaald 2017-05-03 van http://www.imec.be/digimeter
