This is the fourth course in our Data Analyst in R path. In it, you'll build on the R programming skills you learned in the first three courses as you start to work with more challenging data types: text data (strings), dates, and times.

In this course, you'll learn how to use R to interpret, proccess, and analyze text data (strings). You'll also learn how to work with dates and times, which is important for data projects like time series analysis.

As you learn these new R programming skills, you'll be writing your own code to practice them right in your browser window. And you’ll learn all of this while working with real-world data, much as you would for a real data science project.

At the end of the course, you'll complete the second part of our two-part project on building an efficient, reproducable data analysis workflow using R and R Studio.

By the end of this course, you'll be able to:

## Learn to Program using R

### String Manipulation in R: Fundamentals

Learn to work with text data by maniupulating strings with R.

### Date and Time Manipulation in R: Fundamentals

Learn how to work with dates and times as part of your data analysis work.

### The Map Function in R

Learn about the Map Function in R and how it's useful in a data analysis context.

### Guided Project: Creating an Efficient Data Analysis Workflow Part 2

Continue building an efficient data analysis project workflow using your R programming skills and R studio.