Data Analyst with R

Master the basics of data analysis by manipulating common data structures such as vectors, matrices, and data frames.

Continue your journey to becoming an R ninja by learning about conditional statements, loops, and vector functions.

Get started on the path to exploring and visualizing your own data with the tidyverse, a powerful and popular collection of data science tools within R.

Learn to transform and manipulate your data using dplyr.

Learn to combine data across multiple tables to answer more complex questions with dplyr.

Learn to produce meaningful and beautiful data visualizations with ggplot2 by understanding the grammar of graphics.

Master core concepts about data manipulation such as filtering, selecting and calculating groupwise statistics using data.table.

This course will show you how to combine and merge datasets with data.table.

In this course, you will learn to read CSV, XLS, and text files in R using tools like readxl and data.table.

Parse data in any format. Whether it's flat files, statistical software, databases, or data right from the web.

Develop the skills you need to go from raw data to awesome insights as quickly and accurately as possible.

Learn how to use graphical and numerical techniques to begin uncovering the structure of your data.

Use data manipulation and visualization skills to explore the historical voting of the United Nations General Assembly.

Learn how to describe relationships between two numerical quantities and characterize these relationships graphically.

Get ready to categorize! In this course, you will work with non-numerical data, such as job titles or survey responses, using the Tidyverse landscape.

Leverage the power of tidyverse tools to create publication-quality graphics and custom-styled reports that communicate your results.

Master the basics of querying tables in relational databases such as MySQL, SQL Server, and PostgreSQL.

Learn how to create one of the most efficient ways of storing data - relational databases!

Join two or three tables together into one, combine tables using set theory, and work with subqueries in PostgreSQL.