What You'll Learn

  • What is R?
  • History and applications of R
  • Installing and Configuring R and RStudio
  • Basic R Syntax and Data Types
  • Vectors
  • Matrices
  • and Arrays
  • Data Frames and Lists
  • Conditional Statements (if-else)
  • Loops (for
  • while)
  • Creating and Using Functions in R
  • Function Arguments and Scoping
  • Data Manipulation with dplyr (filter
  • select
  • mutate
  • arrange)
  • Data Tidying with Tidyr (pivot_longer
  • pivot_wider)
  • Joining and Merging Data Frames
  • Creating Various Types of Plots (scatter plots
  • bar plots
  • line plots
  • histograms)
  • Customizing Plot Aesthetics (colors
  • labels
  • themes)
  • Creating Interactive Plots
  • Descriptive Statistics (mean
  • median
  • standard deviation
  • quartiles)
  • Hypothesis Testing (t-tests
  • chi-squared tests)
  • Regression Analysis (linear regression
  • multiple regression)

Requirements

  • No R programming experience needed

Description

Welcome to Hands-On R Programming: Build Real World Data Projects — your practical path to mastering R through real life applications. Whether you're a beginner or someone looking to strengthen your data skills, this course will give you hands-on experience with one of the most powerful tools in data science.


Why Learn R?

R is widely used in data science, statistics, machine learning, and academia — especially when working with large datasets and generating clean, meaningful visualizations. It’s a favorite among data analysts, researchers, and companies worldwide.


But instead of just learning R syntax in isolation, this course focuses on building real world projects that reflect the kinds of tasks data professionals face every day.


What You'll Learn

  • R programming fundamentals and best practices

  • Data cleaning and transformation

  • Exploratory Data Analysis (EDA)

  • Working with real world datasets: business, healthcare, finance, and more

  • Building dashboards and automated reports

  • Introduction to machine learning using caret and randomForest

  • Statistical analysis, hypothesis testing, and correlation techniques

  • How to structure, document, and present your projects


Course Features

  • Step-by-step, beginner friendly tutorials

  • Lifetime access

  • Certificate of Completion


Start Learning Today

By the end of this course, you'll be confident in using R to clean, analyze, visualize, and present data.

Who this course is for:

  • Anyone who wants to build a strong portfolio of R data projects
  • Students in statistics
  • economics
  • or data science
  • Beginners who want to learn R by doing
  • not just watching
  • Data analysts and professionals transitioning into R from Excel or Python
Hands-On R Programming: Build Real World Data Projects

Course Includes:

  • Price: FREE
  • Enrolled: 4432 students
  • Language: English
  • Certificate: Yes
  • Difficulty: Beginner
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