This interactive R course covers everything from the basics, variables, and data types to advanced topics, such as recursion, file handling, and S3/S4 classes in R.

In today’s data-driven world, the ability to analyze large datasets is becoming a vital skill across industries. R, one of the most powerful languages for data analysis.
This interactive R course is designed for beginners, with no prior knowledge of R programming required. You will begin with fundamental concepts, such as R variables, data types in R, and basic functions like R print and R cat. As you progress, you will dive into more complex topics, including R vectors, lists, arrays, matrices, and data frames in R programming. You’ll also learn how to perform operations using arithmetic operators in R, relational operators in R, and logical operators in R. Further, the course covers advanced features like if statements in R, switch statements in R, loops in R, and recursion in R. 
Finally, you’ll gain hands-on experience with file handling in R, exception handling with try and except in R, and object-oriented programming using S3 and S4 classes in R.

Learn R

## Packages in R language

Learning to program in **R** is important if you’re serious about understanding data. In this course, we have mentioned the basics to get you started with **R** language but rest assured there is much much more to learn. 

However, the major ease that R language provides to programmers is the vast number of packages that can be imported in our programs. Many programmers and statisticians use R to design tools. These tools are then freely available as open source to the community. We can download these, import them as **packages** and easily use in our code.

> Packages are pre-assembled collections of functions and objects.  

We can import packages using the simple method:
```
install.packages("<nameOfPackage>")
```

### Loading a package
Once you have installed a package, we can load it in our program using the `library()` function.

```r
library(<package name>)
# Notice that we do not need the quotation marks now
```
Now you can simply use all the functions and objects of the respective package in our R program.

---

We have come to the end of this course. We have covered all the introductory concepts to get you started in programming with R. Remember, practice makes perfect. So keep practicing the concepts we have learned in this course. Keep learning and have fun with it.

# Packages in R language

Learning to program in **R** is important if you’re serious about understanding data. In this course, we have mentioned the basics to get you started with **R** language but rest assured there is much much more to learn. 

However, the major ease that R language provides to programmers is the vast number of packages that can be imported in our programs. Many programmers and statisticians use R to design tools. These tools are then freely available as open source to the community. We can download these, import them as **packages** and easily use in our code.

> Packages are pre-assembled collections of functions and objects.  

We can import packages using the simple method:
```
install.packages("<nameOfPackage>")
```

## Loading a package
Once you have installed a package, we can load it in our program using the `library()` function.

```r
library(<package name>)
# Notice that we do not need the quotation marks now
```
Now you can simply use all the functions and objects of the respective package in our R program.

---

We have come to the end of this course. We have covered all the introductory concepts to get you started in programming with R. Remember, practice makes perfect. So keep practicing the concepts we have learned in this course. Keep learning and have fun with it.

In this lesson, we briefly touch upon installing packages in R language.

Introduction to R

R variables

Data Structures in R

Operator in R

Conditional Statements in R

Loops in R

Function in R

Input/Output in R

Exception Handling in R

Classes in R

R Programming Challenges

Conclusion

More on R Language

Packages in R language

Loading a package