Brooke Anderson

Dr. Anderson is an Assistant Professor at Colorado State University in the Department of Environmental & Radiological Health Sciences, as well as a Faculty Associate in the Department of Statistics. She is also a member of the university’s Partnership of Air Quality, Climate, and Health and is a member of the editorial boards of Epidemiology and Environmental Health Perspectives. Previously, she completed a postdoctoral appointment in Biostatistics at Johns Hopkins Bloomberg School of Public and a PhD in Engineering at Yale University. Her research focuses on the health risks associated with climate-related exposures, including heat waves and air pollution, for which she has conducted several national-level studies. As part of her research, she has also published a number of open source R software packages to facilitate environmental epidemiologic research.

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Building Data Visualization Tools (Coursera)

The data science revolution has produced reams of new data from a wide variety of new sources. These new datasets are being used to answer new questions in way never before conceived. Visualization remains one of the most powerful ways draw conclusions from data, but the influx of new [...]
Average: 8 (4 votes)

Building R Packages (Coursera)

Writing good code for data science is only part of the job. In order to maximizing the usefulness and reusability of data science software, code must be organized and distributed in a manner that adheres to community-based standards and provides a good user experience. This course covers the primary [...]
Average: 6 (4 votes)

Advanced R Programming (Coursera)

This course covers advanced topics in R programming that are necessary for developing powerful, robust, and reusable data science tools. Topics covered include functional programming in R, robust error handling, object oriented programming, profiling and benchmarking, debugging, and proper design of functions. [...]
Average: 7 (4 votes)

The R Programming Environment (Coursera)

This 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. Whether you are part of a data science team or working individually within a community of developers, this course will give you [...]
Average: 3 (4 votes)