This virtual course will show how public bioimaging data resources, centred around the BioImage Archive, enable and enhance machine learning based image analysis. The content will explore a variety of data types including electron and light microscopy and miscellaneous or multi-modal imaging data at the cell and tissue scale. Participants will cover contemporary biological image analysis with an emphasis on machine learning methods, as well as how to access and use images from databases. Further instruction will be offered using applications such as ZeroCostDL4Mic, ilastik, the BioImage Model Zoo, and CellProfiler.

Virtual course

This course will be a virtual event delivered via a mixture of live-streamed sessions, pre-recorded lectures, and tutorials with live support. We will be using Zoom to run the live sessions (all fully password protected with automated English closed captioning and transcription) with support and both scientific and social networking opportunities provided by Slack and other methods, taking different time zones into account.

In order to make the most out of the course, you should make sure to have a stable internet connection throughout the week and are available between 08:00 – 18:00 BST each day. In the week before the course there will be a brief induction session. Computational practicals will run on EMBL-EBI's virtual training infrastructure, meaning participants will not require access to a powerful computer or install complex software on their own machines.

Selected participants may be sent materials prior to the course. These might include pre-recorded talks and required reading or online training that will be essential to fully engage with the course.