Skip to main content
An official website of the United States government
Government Funding Lapse
Because of a lapse in government funding, the information on this website may not be up to date, transactions submitted via the website may not be processed, and the agency may not be able to respond to inquiries until appropriations are enacted.

The NIH Clinical Center (the research hospital of NIH) is open. For more details about its operating status, please visit cc.nih.gov.

Updates regarding government operating status and resumption of normal operations can be found at opm.gov.

Chapter 1: Data Science Myths

It's never too late to learn cancer data science. 

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.

Watch the Video

Watch 5 Data Science Myths (approx. 6 minutes long).

Test Your Knowledge

The best technology for conducting data science is expensive.

A. True
B. False

The correct answer is B.
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. 

The incorrect answer is A.
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.

Keep Going

Continue to Chapter 2 to learn about big data technologies we think can accelerate your education and 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.

For questions and feedback about this chapter, email our team at ncicbiit@mail.nih.gov

  • Updated:

If you would like to reproduce some or all of this content, see Reuse of NCI Information for guidance about copyright and permissions. In the case of permitted digital reproduction, please credit the National Cancer Institute as the source and link to the original NCI product using the original product's title; e.g., “Chapter 1: Data Science Myths was originally published by the National Cancer Institute.”

Email