The goal of this course is to introduce students to the basics of image data science using Napari and Python. The students will learn how to setup Conda environments, install Python libraries and setup Jupyter notebooks for scientific image and data analysis. We will start with a crash-course in Python basics. Afterwards, core concepts of image analysis such as image filtering, segmentation and feature extraction will be taught with the interactive image analysis software Napari. The students will then learn how to reproduce interactively assembled image analysis workflows using Python and Jupyter lab. Finally, we will introduce the students to supervised and unsupervised machine learning techniques for object classification and clustering. Using these techniques the students will be enabled to differentiate objects such as cells with different phenotypes using object-based measurements and state-of-the-art data science methods.