Docker Containers for Data Science and Reproducible Research

Get excited! This course is designed to jump-start using Docker Containers for Data Science and Reproducible Research by reproducing several practical examples. Course will help to setup Docker Environment on any machine equipped with Docker Engine (Mac, Windows, Linux). Course will proceed with all steps to create custom and distributed development environment [RStudio] in a container. Forget about manual update of your Development Environment! Work as usual, add or develop the research document into your Container, test it and distribute in an image! Result will be reproducible independently on the R version, perhaps after several years... Same about running R programs in the container. We will demonstrate this capability including testing the container on completely different machines (Mac, Windows, Linux) Summary of ideas we will cover in this course: Reproduce and share work on a different infrastructure Be able to repeat the work after several years Use R-Studio in an isolated environment Tips to personalize work with Docker including usage of Automated Builds What is covered by this course? This course will provide several use cases on using Docker Containers for Data Science: Preparing your computer for using Docker Working pipeline to develop docker image Building Docker image to work with R-Studio in Interactive mode Building Docker images to run R programs Using Docker network to communicate between containers Building ShinyServer in Docker container Walk-though example of developing Shiny App as an R Package and deploying in Docker Container using golem framework More relevant materials may be added to this course in the future (e.g. continous integration and deployment, docker-compose) Why to take this course and not other? Added value of this course is to provide a quick overview of functionality and to provide valuable methods and templates to build on. Focus of this course is to make a learning journey as easy as possible - simply watch these videos and reuse provided code! Just Start using Docker Containers with your Data Science tools by reproducing this course!

Requirements GitHub account Mac or Windows PC [can also be applicable for Linux] Basic knowledge of R programming language is preferred but not necessary Willing to learn and use R Statistical Software Basic knowledge of command line is preferred but not necessary