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R Programming Training Course

R Programming

Learn to lead data-driven projects with our R programming certification!

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Highlights of R Programming Course

Data Analysis and Visualization with R Programming

22 Hours of Live Instructor-Led Sessions

8 Hours MCQs and Assignments for Practice

3 Live Projects for Applied Learning

16 Hours of Hands-on Training with R

One of the leading programming languages, R is widely used for statistics and data modeling. Its popularity can be attributed to the fact that is that it is sophisticated, extremely versatile, and flexible and can be applied in a variety of fields, including data science, engineering, business, medicine, and pure science. R allows data analysis using a variety of statistical techniques, such as linear and nonlinear modeling, classical statistical tests, and time-series analysis, to name a few; and also has capabilities to produce a range of graphics including charts, plots, graphs and so on that can be used for presentations.

Our course offers an expert's-eye overview of how these advanced tasks fit together in R as a whole along with practical examples. Through hands-on exercises and in-depth coaching, you will get a thorough understanding of R, its data structures, data processing functions, and data summarizing with R.

Why KnowledgeHut for R Programming Course

Get The KnowledgeHut Advantage

Instructor-Led Live Classroom

Engage live with industry expert instructors—listen, learn, ask questions, and apply skills hands-on.

Curriculum Designed by Experts

Stay updated with the latest tech advancements to remain globally relevant and empowered.

Learn through Doing

Gain real-world skills with hands-on coding, case studies, and exercises you can apply immediately.

Mentored by Industry Leaders

Learn from the best in the field. Our mentors are all experienced professionals in the fields they teach.

Advance from the Basics

Learn from the basics and progress with step-by-step guidance on tools and techniques.

Code Reviews by Professionals

Get reviews and feedback on your final projects from professional developers.

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Prerequisites for R Programming Course

Prerequisites and Eligibility
Prerequisites and Eligibility

R Programming Course Curriculum

Curriculum

1. Introduction to R Programming

Learning Objectives:

Get an idea of what R is and why it is so popular among Data Scientists.

Topics Covered:

  • What is R?
  • Why is it in demand?

Hands-on: No hands-on

2. Installing and Loading Libraries

Learning Objectives:

In this module, you will learn to install R and its components, install and load R libraries and learn about the frequently used libraries.

Topics Covered:

  • Installation of R - step-by-step
  • Installing Libraries
  • Getting to Know Important Libraries

Hands-on:

Know how to install R, R Studio, and other libraries.

3. Data Structures in R

Learning Objectives:

Learn about data structures in R.

Topics Covered:

  • List
  • Vectors
  • Arrays
  • Matrices
  • Factors
  • String
  • Data Frames

Hands-on:

Write R Code to understand and implement R Data Structures.

4. Control & Loop Statements in R

Learning Objectives:

Learn all about loops and control statements in R.

Topics Covered:

  • For Loop
  • While Loop
  • Break Statement
  • Next Statements
  • Repeat Statement
  • if, if…else Statements
  • Switch Statement

Hands-on:

Write R Code to implement loop and control structures in R.

5. Functions in R

Learning Objectives:

Learn how to write custom functions, nested functions and functions with arguments.

Topics Covered:

  • Writing your own functions (UDF)
  • Calling R Functions
  • Nested Function Calls in R
  • Functions with Arguments
  • Calling R Functions by passing Arguments

Hands-on:

Write R Code to create your own custom functions without or with arguments. Know how to call them by passing arguments wherever required

6. Loop Functions in R

Learning Objectives:

Learn all about loop functions available in R which are efficient and can be written with a single command.

Topics Covered:

  • apply
  • lapply
  • sapply
  • mapply
  • Tapply

Hands-on:

Write R Code to implement various types of apply functions and understand their usage.

7. String Manipulation & Regular Expression in R

Learning Objectives:

Learn all about string manipulations and regular expressions. The functions can be extremely useful for text or unstructured data manipulations.

Topics Covered:

  • stringr()
  • grep() & grepl()
  • regexpr() & gregexpr()
  • regexec()
  • sub() & gsub()

Hands-on:

Write R Code for string manipulation and handle regular expression.

8. Working with Data in R

Learning Objectives:

Learn how to import data from various sources in R and how to write files from R. Also learn how to connect to various databases from R.

Topics Covered:

  • Reading data files in R
  • Reading data files from other Statistical Software
  • Writing files in R
  • Connecting to Databases from R
  • Data Manipulation & Analysis

Hands-on:

Write R Code to read and write data from/to R. Read data not only from CSV files but also using direct connection to various databases.

9. Querying, Filtering, and Summarizing

Learning Objectives:

Learn how to apply various data processing functions in R. These operations can be useful to describe data and perform certain operations on it. This will help you to take necessary steps for further analysis.

Topics Covered:

  • Pipe operator for data processing
  • Using the dplyr verbs
  • Using the customized function within the dplyr verbs
  • Using the select verb for data processing
  • Using the filter verb for data processing
  • Using the arrange verb for data processing
  • Using mutate for data processing
  • Using summarise to summarize a dataset

Hands-on:

  • Write R code to preprocess, to
  • summarize data and basic
  • visualization of the data

10. Basic Data Visualization

Learning Objectives:

Learn basic data visualization techniques to build charts using R.

Topics Covered:

  • Basic Data Visualization with standard libraries

Hands-on:

Write R code to perform basic visualization of the data

What You'll Learn in R Programming Course

Learning Objectives
1
Basics of R

Install R studio. Explore R language fundamentals, including basic syntax, variables, and types

2
Data Structures

Learn about data structures that R can handle. Create and manipulate regular R lists, tuple etc.

3
Conditional Statements

Learn about control structures and loop statements for efficient programming.

4
Object Oriented Programming

Learn to write user-defined functions and object-oriented way of writing classes and objects.

5
Functions

Learn how to use R functions and import necessary packages for data analysis.

6
Querying and Filtering

Learn to apply data processing functions in R for describing and performing operations on data.

Who Should Attend the R Programming Course

Who This Course Is For
  • Those interested in the field of data science
  • Those who want to learn R programming from scratch
  • Those looking for a robust, structured learning program on R
  • Software or Data Engineers interested in learning R Programming
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R Programming Course FAQs

Frequently Asked Questions
The Course FAQs

1. Why is this R Programming course relevant?

Glassdoor has ranked Data Science as the best job in America 3 years in a row, with a median base salary of $110000 and 4,524 job openings. This demand is only increasing year on year, making it the fastest growing tech employment area today. Jobs that require knowledge of data science include Data scientist, Analytics Manager, Database Administrator, Data Engineer, Business Intelligence Developer etc. This course will help you learn the R programming language which is one of the most commonly used languages in the Data Science space.

2. What practical skill sets can I expect to have upon completion of the R Programming course?

  • How to use the R programming language and its environment
  • How to use R functions to manipulate data
  • How to analyze and manipulate data with R

3. What can I expect to accomplish by the end of this R Programming course?

By the end of this course, you will have gained knowledge of the use of R language to build applications on data statistics. This will help you land jobs as data analyst.

4. What are the Tools and Technology used for R Programming course?

Tools and Technologies used for this course are

  • R
  • R Studio

5. Does this R Programming class have any restrictions?

There are no restrictions but participants would benefit if they have elementary programming knowledge.

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