[100% Off] Hands-On R Programming: Build Real World Data Projects
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 Learn
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R programming fundamentals and best practices
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Data cleaning and transformation
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Exploratory Data Analysis (EDA)
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Working with real world datasets: business, healthcare, finance, and more
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Building dashboards and automated reports
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Introduction to machine learning using caret and randomForest
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Statistical analysis, hypothesis testing, and correlation techniques
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How to structure, document, and present your projects
Course Features
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Step-by-step, beginner friendly tutorials
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Lifetime access
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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.
Author(s): Brighter Futures Hub
