Participants will obtain a strong foundation on the R data-types and data-structures (vectors, matrices, lists, ames) and how to properly work with them (access data, modify, filter). A good foundation of R data structures is very important for progressing in R for Data Science. They will learn how to work with variables to store data, and how to apply functions to data. Participants will get to know the R language syntax, how to write proper code for solving a given problem. Introduce participants to R Studio, an advanced environment for using the R language (scripts, projects, customizing R studio). Getting familiar with the R language environment. The course will be a combination of lectures and practicals. This is the first module in a series or courses in Data Science with R, covering many different subjects, from cleaning up datasets to creating interactive and reproducible reports with transferable skills that would apply to any scientific or business domain. The focus is on the application of the techniques with R, and not the underlying statistical theory behind them. Finally we will showcase how to use R for analyzing experimental data using simple statistical techniques like t-tests, analysis of variance and linear regression. Participants will learn about R data-types and data-structures, and they will be taught how to explore data and produce plots. Participants will be introduced to R language syntax, enabling them to write their own R code. The aim of this course is to provide an introduction to data science, using R and R Studio. 
Introduction to Data Science with R and R Studio (online) To be announced Scope
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