Docker for Data Scientists Course
This course introduces students to preconfigured Docker stacks for data scientists. These stacks include specialized stacks for RNAseq, single-cell, high content screening, and genomics. Each stack comes with a preconfigured JupyterLab and RStudio server instance.
Students will learn to use these stacks and how to expand on them for their own projects using pre-existing toolchains to build and save their docker images.
To view existing images see the BioHub Docker Images GitHub repo.
Skillset Outcomes
By the end of the course students will be able to:
Intended Audience
Bioinformaticians who have day to day practical experience in solving problems with R or Python. Some familiarity with the command line is necessary.
Course Length
4 days
Course Delivery
This course can be delivered in person or remotely in real-time with Zoom and Slack.
Requirements
Computer
All students require a computer with an internet connection and at least 8 GBs of ram.
IDE
I recommend PyCharm professional, but Visual Studio code can also be used.
Other requirements
All students need Slack for communicating with code blocks, and optionally Zoom if the course will be delivered remotely.
Development Environment
Students can use Docker Desktop on their own laptops, or you can request a development environment for your students, which I build on AWS. Please note that I need 1 week of notice to deploy the development environment, and there is a charge.
