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This online course gives an introduction to patient safety and quality improvement in healthcare (part 1 of 3).
This online course gives an introduction to patient safety and quality improvement in healthcare (part 3 of 3).
This class provides an introduction to the Python programming language and the iPython notebook. This is the third course in the Genomic Big Data Science Specialization from...
This online course explores the ethical and policy/governance issues that arise in the design, conduct and application of synthetic biology.
This online course program provides an introduction to topics in single and multivariable calculus, and focuses on using calculus to address questions in the natural and social...
This course will cover the basic components of building and applying prediction functions with an emphasis on practical applications. The course will also introduce a range of...
This course presents the fundamental probability and statistical concepts used in elementary data analysis.
This course covers how to program in R and how to use R for effective data analysis. Students will learn how to install and configure software necessary for a statistical...
This online course gives an introduction to patient safety and quality improvement in healthcare (part 2 of 3).
This course covers the basics of creating data products using Shiny, R packages, and interactive graphics. The course will focus on the statistical fundamentals of creating a...
This MOOC explores "neurohacking", which describes how to use the R programming language to perform manipulation, processing, and analysis of neuroimaging data.
This course focuses on the concepts and tools behind reporting modern data analyses in a reproducible manner. Reproducible research is the idea that data analyses, and more...
This online course provides a rigorous introduction to the R programming language, with a particular focus on using R for software development in a data science setting.
This online course explores advanced topics in R programming that are necessary for developing powerful, robust, and reusable data science tools. Topics covered include...
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