Table 4.
Twelve major resources for clinicians who wish to learn about data science.
| Topic | Type | Platform/Resource | Content summary |
|---|---|---|---|
| Data science (in general) | MOOC | Kahn academy | An online course that covers a wide range of topics about statistical analyses |
| MOOC | Coursera: data science specialization | An online course that provides a broad overview of data science | |
| MOOC | edX: introduction to probability (HarvardX STAT110x) | An online course that introduces the basics of probability theories, which are fundamental for data science, statistics, and causal inference | |
| MOOC | Stanford: statistical learning | An online learning course that offers an introduction to various statistical learning (including machine learning) approaches | |
| Textbook | An Introduction to Statistical Learning | A well-written introductory textbook that is used in the statistical learning course (see above) | |
| Paper | BMJ: research methods & reporting | BMJ series introduces important topics of epidemiology and biostatistics to help clinicians interpret the medical literature | |
| Paper | JAMA: guide to statistics and medicine | JAMA series introduces important statistical techniques to help clinicians interpret the medical literature | |
| Machine learning | MOOC | Coursera: machine learning | One of the most popular machine learning courses (as of January 2021, 3.9 million students have been enrolled). This introductory course provides an overview of various machine learning algorithms |
| MOOC | Coursera: Deep learning specialization | A more detailed online course that covers the basics and applications of various deep learning algorithms | |
| Causal inference | MOOC | edX: Causal diagrams (HarvardX PH559x) | An online course that introduces an overview of causal diagrams in clinical research |
| MOOC | Coursera: A crash course in causality | An online course offered that provides an introductory overview of causal inference theories and approaches | |
| Textbook | Causal Inference in Statistics: A Primer (64) | Introductory-level textbook that covers important topics in causal inference (e.g., causal diagram) | |
| Textbook | Causal Inference: What if (15) | Comprehensive intermediate-level textbook that provides the concepts of and methods for causal inference in clinical research | |
| Programming | MOOC | Coursera: foundations using R specialization | An online course that provides a broad overview of R programing |
| Others | DataCamp | A collection of introductory video lectures and hand-on coding practices in several programing languages (e.g., R, python) |
MOOC, massive open online course; BMJ, British Medical Journal; JAMA, Journal of the American Medical Association.
All of the listed MOOCs are publicly-available without fee.