Fred Hutchinson Cancer Center
Enhancing Reproducible Science with GitHub and Docker Specialization
Fred Hutchinson Cancer Center

Enhancing Reproducible Science with GitHub and Docker Specialization

Make Your Scientific Data Analysis Reproducible. Learn best practices, methods, and tools to enhance the reproducibility of your data analyses

Included with Coursera Plus

Get in-depth knowledge of a subject
Beginner level

Recommended experience

Flexible schedule
1 month at 10 hours a week
Earn a career credential
Share your expertise with employers
Get in-depth knowledge of a subject
Beginner level

Recommended experience

Flexible schedule
1 month at 10 hours a week
Earn a career credential
Share your expertise with employers

Overview

  • Organize analysis files and track changes in your code over time with version control.

  • Automate the testing and re-running of your code.

  • Enable shareable computing environments so that your results are consistent.

What’s included

Shareable certificate

Add to your LinkedIn profile

Taught in English
Recently updated!

July 2025

55 practice exercises

Advance your subject-matter expertise

  • Learn in-demand skills from university and industry experts
  • Master a subject or tool with hands-on projects
  • Develop a deep understanding of key concepts
  • Earn a career certificate from Fred Hutchinson Cancer Center

Specialization - 5 course series

What you'll learn

  • Create reproducible data analyses

  • Apply reproducibility skills to existing analyses scripts and projects

Skills you'll gain

Category: Integrated Development Environments
Category: Package and Software Management
Category: Technical Documentation
Category: GitHub
Category: Open Source Technology
Category: Programming Principles
Category: Code Review
Category: Git (Version Control System)
Category: Rmarkdown
Category: Scientific Methods
Category: Jupyter
Category: Bioinformatics
Category: R Programming
Category: Data Analysis

What you'll learn

  • Enhance reproducibility and replicability of data analyses

  • Introduction to reproducibility tools

Skills you'll gain

Category: Code Review
Category: Docker (Software)
Category: GitHub
Category: Git (Version Control System)
Category: Automation
Category: Software Development Tools
Category: Technical Communication
Category: Containerization
Category: Health Informatics
Category: Data Analysis
Category: Version Control
Category: Science and Research
Category: R Programming
Category: Medical Science and Research
Category: Bioinformatics

What you'll learn

  • Goal of this course: Equip learners with basics skills and confidence to utilize containers within the context of scientific software analyses.

Skills you'll gain

Category: Docker (Software)
Category: Containerization
Category: Command-Line Interface
Category: Devops Tools
Category: Development Environment
Category: Debugging
Category: GitHub
Category: Software Installation
Category: Continuous Integration
Category: Software Development
Category: Software Versioning
Category: CI/CD
Category: Continuous Deployment
Category: Application Deployment

What you'll learn

  • Utilize automation to enhance scientific projects and save time

    Troubleshoot most common GitHub Actions errors

Skills you'll gain

Category: GitHub
Category: Continuous Integration
Category: CI/CD
Category: Automation
Category: Debugging
Category: Continuous Deployment
Category: Bioinformatics
Category: Scientific Methods
Category: Software Development
Category: Development Environment
Category: YAML
Category: Docker (Software)
Category: Test Automation
Category: Science and Research

What you'll learn

Skills you'll gain

Category: Version Control
Category: Key Management
Category: YAML

Earn a career certificate

Add this credential to your LinkedIn profile, resume, or CV. Share it on social media and in your performance review.

Instructors

Carrie Wright, PhD
Fred Hutchinson Cancer Center
14 Courses17,225 learners
Kate Isaac
Fred Hutchinson Cancer Center
1 Course33 learners
Candace Savonen, MS
Fred Hutchinson Cancer Center
13 Courses6,557 learners

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