Hands-On R Programming: Build Real World Data Projects

Published 8/2025
MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 2h 43m | Size: 837 MB

Hands-on learning with R: Analyze, visualize, and interpret real world data like a pro.

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 LearnR programming fundamentals and best practicesData cleaning and transformationExploratory Data Analysis (EDA)Working with real world datasets: business, healthcare, finance, and moreBuilding dashboards and automated reportsIntroduction to machine learning using caret and randomForestStatistical analysis, hypothesis testing, and correlation techniquesHow to structure, document, and present your projectsCourse FeaturesStep-by-step, beginner friendly tutorialsLifetime accessCertificate of CompletionStart Learning TodayBy the end of this course, you’ll be confident in using R to clean, analyze, visualize, and present data.