Cancer Data Science Course

Are you interested in the field of cancer data science? Whether you’re intending to transform your career with it, or you’re just looking for some perspective, we hope this beginner series can be your roadmap to better understanding this pivotal field. 

Watch, read, and review your way through each chapter to learn fundamental information and skills. 

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Chapters

Chapter 1: It’s Never Too Early to Learn Cancer Data Science


Chapter Description

We’ve spoken with early career cancer researchers and trainees, and many of them lamented that they wished they had started gaining data science skills earlier in their career. In this chapter, you’ll learn the truth about common data science myths and explore overview resources of the data science process, where you fit into the process, and how you can use it in your projects.

Start the Course

Required:

Watch our video, “5 Data Science Myths" (approx. 6 minutes long).

Test your knowledge!

1
True or False: The best technology for conducting data science is expensive.
Explanation: Many data science resources are freely accessible. You don’t necessarily need a big budget for technologies to use data science to do high-quality research. NCI provides the cancer research community with many free tools.
Explanation: Many data science resources, such as those produced by NCI, are freely accessible. You don’t necessarily need a big budget for technologies to use data science to do high-quality research.
False
Correct
Incorrect

Other Related Materials:

Keep Going!

Continue to Chapter 2 to explore coding basics for cancer research.

Instructor

Shan Li, Ph.D.
NCI Center for Cancer Research (CCR)
Dr. Li is a staff scientist with NCI CCR’s Cancer and Data Science Laboratory. Her research focuses on identifying the functional non-coding mutations in cancer progression.

Have a question or feedback about this course chapter?