eliasgruenewald/ai_in_medicine

Programmierung in Python

This repository contains the course material for the programming tutorials in week 1 & 2. The table gives an overview on the topics covered within the tutorials.

Schedule

Datum	Zeit	Raum	Titel	Referenten
2024-07-08	10:15-13:00	CIPOM	Grundkonzepte	Sebastian Boie
2024-07-09	10:15-13:00	CIPOM	Numpy und Pandas	Sebastian Boie
2024-07-10	10:15-13:00	CIPOM	Matplotlib und Seaborn	Marija Tochadse
2024-07-11	10:15-13:00	CIPOM	Scikit-learn	Sebastian Boie
2024-07-12	10:15-13:00	CIPOM	Keras	Moritz Seiler
2024-07-16	10:15-13:00	CIPOM	Patientenversorgung	Elias Grünewald (Sebastian Boie)
2024-07-18	10:15-13:00	CIPOM	Computer Vision	Marc-Andre Schulz

How to start using this material

There are different options to access the course material. Here, we recommend to use one of the following:

Colab (Recommended)

1. Click on the linked title of the lesson you want to open.
2. Log in with your Google account of choice.
3. Save a copy in your Google Drive by clicking on Copy to Drive.
4. In the new tab, click on Connect to environment (top right). Accept potential warnings about the origin of the notebooks.
5. Follow the lesson!

Binder

The Binder Project is an open community that makes it possible to create sharable, interactive, reproducible environments. No account is required to access and execute the tutorial material.

1. Go to Binder
2. Insert to URL of this GitHub repository (https://github.com/ritterlab/ai_in_medicine) in the GitHub repository field.
3. Click on the 'launch' button to create a Docker image of the environment.
4. Select the relevant Jupyter notebook for the tutorial.

Binder allows only a memory of 2GB per container, you have to use a copy of the COVID-19 dataset for your tutorial. Moreover, Binder does not offer GPU support.

Jupyter Notebooks (local)

It is recommended to install the Anaconda Distribution which is a Python/R data science distribution and a collection of over 7,500+ open-source packages including a package and environment manager. Please follow the installation instructions for the local installation.

1. After the installation you can either clone the GitHub repository or download the repository as a zip-file by clicking on the green Code button and selecting Donwload ZIP
2. Launch the Jupyter Notebook App.
3. Access the relevant directory.
4. Open the relevant Jupyter notebook.

Optional: Challenge

tba