Docker Containers for Data Science and Reproducible Research

Unlock the power of Docker Containers for Data Science and Reproducible Research! This hands-on course will get you started quickly by recreating practical examples, empowering you to build robust and portable workflows.

• Set up your Docker Environment: Learn to install and configure Docker Engine on any machine – Mac, Windows, or Linux.
• Create Custom Development Environments: We'll guide you through the process of building custom, isolated RStudio environments within containers. Say goodbye to tedious manual updates!
• Reproducible Research: Ensure your work is consistently reproducible, even years later, regardless of R version. This is crucial for reliable results and collaboration.
• Run R Programs Reliably: Discover how to containerize your R programs, guaranteeing consistent execution across different systems.
• Test Across Platforms: Learn to test your containers on various operating systems (Mac, Windows, Linux) to ensure seamless deployment.

Key Concepts Covered:

• Reproducing Work on Different Infrastructure: Deploy your projects effortlessly on any system.
• Long-Term Reproducibility: Guarantee your research remains valid and consistent over time.
• Isolated RStudio Environments: Work in a clean, controlled environment, free from conflicts.
• Automated Builds: Personalize your workflow with automated container builds.

What You'll Learn:

• Preparing Your Computer for Docker: Essential setup steps.
• Building a Development Pipeline: A streamlined process for creating Docker images.
• Creating Docker Images for RStudio: Develop and run RStudio in an interactive container.
• Running R Programs in Docker: Containerize and execute your R code reliably.
• Docker Networking: Connect and communicate between multiple containers.
• Deploying Shiny Apps: Containerize ShinyServer for easy deployment.
• Shiny App Deployment with Golem: A walkthrough example of developing a Shiny App as an R Package and deploying it using the Golem framework.

Future Enhancements: We plan to add more advanced topics like continuous integration/continuous deployment (CI/CD) and Docker Compose to this course.

Why Choose This Course?

This course provides a fast-track introduction to Docker Containers for Data Science. We offer practical methods and templates to build upon, making the learning journey as simple as possible. Just follow the videos and reuse the provided code!

Start using Docker Containers with your Data Science tools today!