📋 Content
- 📋 Content
- 📄 Description
- 📣 Current announcements
- ❗ Course requirements
- 📒 Syllabus
- 📝 Theoretical basics
- ☝️ References
📄 Description
This directory contains a few basic notebooks to learn wo work with databases and how to manage and analyse these.
By the end of these notebooks, you should feel more comfortable with:
- feel more confident in dealing with Pandas
- have a basic understanding of data processing and editing
- process medical data sets and extract important information
📣 Current announcements
In this skill track, the notebooks build on each other. Therefore, complete them in the order given!
❗ Course requirements
This workshop is intended for learners who have a basic understanding of working with Python like:
- Variables, data types, functions
- Loops, comditionals
Please note:
- you should have understood the basic concepts of Python, otherwise have another look at the Introductory notebooks
- in this notebook we use data from open-source databases (the references are at the bottom of the page); in Google Colab the data is loaded automatically at the beginning of the notebook
- have a look at the theoretical basics before you start with the notebooks
📒 Syllabus
- Basic concepts of data management
- Basic concepts of loading file formats
- Data Analysis - Lung Deseases
- Data Analysis - Sleep
📝 Theoretical basics
For some information on the topic, take a look at some Basics.
☝️ References
In this skill track, you’ll work with different Open-Source datasets:
[1] Wang, Xiaosong, et al. (2017), Chestx-ray8: Hospital-scale chest x-ray database and benchmarks on weakly-supervised classification and localization of common thorax diseases, Proceedings of the IEEE conference on computer vision and pattern recognition.
[2] Kemp, B., et al. (2000), Analysis of a sleep-dependent neuronal feedback loop: the slow-wave microcontinuity of the EEG, IEEE Transactions on Biomedical Engineering.