Learn R programming
Learn the basics and applications of R programming for data handling, analysis, and visualization. The course page highlights R as useful for data science, statistics, and career development in technical fields.
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Course Overview
R programming is presented as a language for data handling and analysis, graphic projections, and working with large data sets. The course page explains that R is used for statistical research, legacy software, and data science across fields such as computer research, education, healthcare, and software publishing. The page describes learning paths that range from introductory classes to intermediate and advanced certificates. Topics mentioned include R libraries, visualizations, functional programming, object-oriented programming, debugging, and profiling. This content is aimed at learners exploring programming languages as well as students and professionals who want to build data analysis and data science skills. The page notes that online courses can be taken at a flexible pace on a computer, tablet, or phone.
Who is this for?
People exploring programming languages, and students or professionals interested in data science, statistics, and data analysis.
Prerequisites
None stated; the page suggests starting with introductory classes if you are still exploring programming languages.
About the Provider
UC Berkeley Center for the Science of Psychedelics (BCSP), founded in September 2020 by a multidisciplinary faculty group including neuroscientist Michael Silver and author Michael Pollan, conducting psilocybin research into cognition, perception, emotion, and their neural bases in the human brain. BCSP's four pillars of basic science, journalism, culture, and community have established it as a leading interdisciplinary hub for psychedelic research and public engagement, producing The Microdose newsletter and a global clinical trials map.
View Berkeley University profileCourse Details
- PricePrice on request
- FormatSelf-paced
- Lifecycle statusNo New Dates
- SkillsR programmingdata handlingdata analysisdata visualizationstatistical researchworking with large data setsR librariesfunctional programmingobject-oriented programmingdebuggingprofiling
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