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Introduction to Reproducibility in Cancer Informatics

Learn essential reproducibility skills for cancer informatics. Master project organization, version control, and documentation techniques.

Learn essential reproducibility skills for cancer informatics. Master project organization, version control, and documentation techniques.

This course introduces reproducibility concepts in cancer informatics. Learn project organization, GitHub usage, package management, and documentation to create more reliable and replicable data analyses.

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Introduction to Reproducibility in Cancer Informatics

This course includes

7 Hours

Of Self-paced video lessons

Intermediate Level

Completion Certificate

awarded on course completion

2,435

What you'll learn

  • Understand the concept and importance of reproducibility in cancer informatics

  • Implement effective project organization strategies for data analysis

  • Use notebooks and integrated development environments to enhance reproducibility

  • Make projects open source using GitHub

  • Manage package versions effectively in R and Python projects

  • Write durable code that enhances project reproducibility

Skills you'll gain

reproducibility
cancer informatics
project organization
GitHub
package management
R programming
Python
data analysis
documentation
code review

This course includes:

PreRecorded video

8 quizzes

Access on Mobile, Tablet, Desktop

FullTime access

Shareable certificate

Get a Completion Certificate

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There are 8 modules in this course

This course provides an introduction to reproducibility concepts and tools in cancer informatics. It begins with defining reproducibility and its importance in scientific research. The curriculum covers project organization strategies, use of notebooks and integrated development environments, and making projects open source with GitHub. Students learn about package version management, writing durable code, and the importance of code review in creating reproducible analyses. The course emphasizes practical skills with hands-on exercises, allowing students to apply reproducibility concepts to their existing analysis scripts and projects. It concludes with techniques for effectively documenting analyses to enhance reproducibility.

Introduction to this Course

Module 1 · 0 Hours to complete

Organizing your project

Module 2 · 25 Minutes to complete

Using notebooks

Module 3 · 52 Minutes to complete

Making your project open source with GitHub

Module 4 · 25 Minutes to complete

Managing package versions

Module 5 · 1 Hours to complete

Writing durable code

Module 6 · 2 Hours to complete

Code review

Module 7 · 1 Hours to complete

Documenting analysis

Module 8 · 35 Minutes to complete

Fee Structure

Payment options

Financial Aid

Instructor

Candace Savonen, MS
Candace Savonen, MS

3,117 Students

10 Courses

Pioneering Accessible Genomic Data Science Education

Candace Savonen has established herself as a dedicated educator and innovator in genomic data science, focusing on making complex bioinformatics tools and concepts accessible to diverse audiences. Her work centers on developing comprehensive educational materials that emphasize reproducibility and scalable teaching methods in bioinformatics and cancer genomics. As a key contributor to various educational initiatives, she has been instrumental in creating and delivering bioinformatics education materials specifically tailored for cancer genomics research. Her approach combines practical application with theoretical understanding, ensuring that learners can effectively apply genomic tools to their specific areas of expertise. Through her involvement in developing online learning modules and educational resources, she has demonstrated a commitment to breaking down barriers in genomic data science education, making these essential tools and knowledge more attainable for researchers and practitioners across different fields. Her teaching methodology emphasizes the importance of reproducible research practices and sustainable approaches to data analysis, contributing significantly to the democratization of genomic data science education.

Introduction to Reproducibility in Cancer Informatics

This course includes

7 Hours

Of Self-paced video lessons

Intermediate Level

Completion Certificate

awarded on course completion

2,435

Testimonials

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Frequently asked questions

Below are some of the most commonly asked questions about this course. We aim to provide clear and concise answers to help you better understand the course content, structure, and any other relevant information. If you have any additional questions or if your question is not listed here, please don't hesitate to reach out to our support team for further assistance.