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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Chapter 5: Machine Learning for Cancer Research

Chapter Description

Why should you use artificial intelligence/machine learning (AI/ML) in your cancer research project? By the end of this chapter, you’ll break down this buzzword to better understand what AI and ML techniques are, get tips for where to start, and see how NCI-funded researchers leverage the technology for their projects.

Start the Course


Watch our ~6-minute-long video, “5 Tips for Using Machine Learning in Your Research”

Test your knowledge!

True or False: Machine learning is the same as artificial intelligence.
Explanation: Although often used interchangeably, they are related but not the same.
Explanation: Artificial intelligence allows a computing machine to solve problems by mimicking the human brain. Machine learning is a subset of this ability, improving on the problem-solving process by allowing a machine the ability to teach itself and learn from its mistakes.

Other Related Materials:

Keep Going!

Continue to Chapter 6 where you will learn about the unique professionals on the multidisciplinary cancer data science team (and where you fit in).


Ismail Baris Turkbey, M.D.
NCI Center for Cancer Research (CCR)
Dr. Turkbey is a senior clinician at NCI’s Molecular Imaging Branch and the director of NCI’s Artificial Intelligence Resource in CCR. His research focuses on artificial intelligence and imaging, biopsy techniques, and focal therapy for prostate cancer.

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