Confident work in RStudio - You will learn to work comfortably in R and RStudio: run code, write scripts, use the console, and keep your workspace organized, so everyday analytical tasks become faster and easier.
Reliable data operations - You will master selecting elements, filtering rows, and creating new columns, so you can prepare datasets for analysis on your own without fixing spreadsheets manually or repeating clicks.
Better object control - You will learn how to inspect data structure and class, manage objects in memory, and save or reload results, which helps you stay in control of your project and avoid workspace clutter.
Efficient import and export - You will learn to import and export text data and work with data frames, lists, and matrices, so you can move data smoothly between files and your analytical environment.
Comfort with vectors - You will understand R data types, conversions, logical, text, and numeric vectors, as well as missing values, factors, and dates, so you can prepare variables correctly for later analysis.
Faster data summaries - You will learn practical ways to calculate means, sums, and frequency tables, and to summarize grouped data, helping you draw conclusions from raw datasets much more quickly.
Effective use of dplyr and data.table - You will practice using dplyr and data.table for filtering, grouping, sorting, sampling, and joining datasets, so you can choose tools that are both convenient and efficient for your work.
Independent skill growth - You will learn how to find, install, and load packages and use R help resources, so after the course you can solve many issues on your own and keep expanding your analytical toolkit.
Basic computer skills - You should be comfortable using your operating system, launching programs, working with files and folders, and installing simple applications on your own computer.
Working with data files - You should understand what data files are and how to use them, for example opening, saving, and organizing datasets in folders so you can work smoothly during the exercises.
Basic logical thinking - You should be comfortable with simple relationships, conditions, and step-by-step sequences, because during the course you will filter data and create variables.
Basics of data work - You should recognize basic terms such as column, row, value, and table so you can follow examples on filtering, summaries, and combining data in R more easily.
