Introduction to R

The main purpose of this training is to allow the trainee to be able to independently work with R. This is a heavily hands-on training featuring topics like: grammar of graphics, grammar of data manipulation, Rmarkdown for reports generation.

The course is targeted to people who are ready to move past Excel in their data analysis. The course does not assume any previous knowledge of programming/scripting. The course does not have any prerequisites. R is used widely in the data science world and this means pretty much every sector by now – be it IT, fintech, medicine or government sector. It will help you to automate data-driven reports. It helps you to easily understand your data by visualizing it and communicate the results using publication-ready graphs. It helps you to apply the most modern data analytics/machine learning concepts on your data.

The course is targeted to people who are ready to move past Excel in their data analysis. The course does not assume any previous knowledge of programming/scripting. The course does not have any prerequisites.

Day 1: 09:30 - 11:00 Introduction to R and Rstudio: Brief overview of R and Rstudio, Managing projects in RStudio, The basic of using R. 11:00 - 11:15 Coffee break. 11:15 - 12:45 The basics of using R: Data structures (vectors and data frames), Functions. 12:45 - 13:30 Lunch. 13:30 - 15:00 Initial overview of dataset, data types: Initial overview of dataset, data types, getting data in and out of R (part 1). 15:00 - 15:15 Coffee break. 15:15 - 16:45 Additional packages in R: Managing additional packages in R. Day 2: 09:30 - 11:00 Recap and Dates with lubridate: Quick recap of what we learned last time, Converting any bad dates to good ones with lubridate. 11:00 - 11:15 Coffee break. 11:15 - 12:45 Getting data in part 2; Filtering data: Reading data from various formats, Interfaces to online databases, Filtering data. 12:45 - 13:30 Lunch. 13:30 - 15:00 Visualizing data - Grammar of Graphics: Introduction to grammar of graphics. 15:00 - 15:15 Coffee break. 15:15 - 16:45 Grammar of graphics: Geometrics, aesthetics, grouping variables and facets. Day 3: 09:30 - 11:00 Grammar of graphics continues: Additional geometrics, positions, scales. 11:00 - 11:15 Coffee break. 11:15 - 12:45 Grammar of graphics continues: Color scales, manual scales, Legends, themes. 12:45 - 13:30 Lunch. 13:30 - 15:00 Lists and functions: Another data structure - list, Writing functions in R, Factor variables in R. 15:00 - 15:15 Coffee break. 15:15 - 16:45 Introduction to dplyr – grammar of data manipulation: Piping in R, Main verbs in grammar of data manipulation: filter(), select(), group_by(), summarize(), mutate(), arrange(). Day 4: 09:30 - 11:00 Recap and rmarkdown – writing automatic reports in R: Recap of grammar of graphics, Introduction to RMarkdown. 11:00 - 11:15 Coffee break. 11:15 - 12:45 Grammar of data manipulation continues: Data in long and wide format, converting between formats (tidyr). 12:45 - 13:30 Lunch. 13:30 - 15:00 Grammar of data manipulation continues: Additional training on grammar of data manipulation. 15:00 - 15:15 Coffee break. 15:15 - 16:45 Putting it all together and additional materials: Grammar of graphics, grammar of data manipulation and rmarkdown, additional materials.

After completing this course, students will be able to: create visualisations using grammar of graphic language, create reports using rmarkdown, process of data elegantly using grammar of data manipulation (dplyr and friends)

The training price also includes: study materials; a trainer's consultation on the topics learned, by e-mail after the training; certificate. As an added value, we offer: free parking; lunch; hot drinks with cookies; fresh fruits.