R Programming Practice Quiz
10 minA short readiness check for R Programming.
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Tutorial
Free course
R Programming for Data Science
Learn R Programming from scratch — installation, RStudio, data types, data frames, statistical analysis, data visualization, and real business analytics applications. Perfect for engineering students and data science beginners.
Install R and RStudio — understand the IDE interface and navigation
Master R data types: vectors, matrices, lists, data frames, factors
Perform data manipulation: subsetting, filtering, sorting, merging
Handle missing values and data cleaning techniques
Apply statistical functions: mean, median, SD, correlation, regression
Create professional visualizations with ggplot2
Work with real datasets for business analytics
Read and write CSV, Excel, and database data in R
Write reusable functions and apply functional programming concepts
Introduction to machine learning concepts with R
- Basic computer knowledge and internet access
- No prior programming experience required
- Willingness to learn statistical concepts
- Interest in data analysis and business analytics
Complete beginner to advanced progression
Real business datasets used in all examples
Covers both base R and modern tidyverse packages
Practical data analysis projects included
Certificate of completion
Lifetime free access
Curriculum
10 lessons
Course Content
4
Arithmetic Operations and Vectors
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5
Handling Missing Data — NA Values
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6
Control Structures — if, for, while
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7
Functions in R
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8
Data Frames and dplyr Manipulation
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9
Statistical Analysis with R
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10
Data Visualization with ggplot2
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Practice
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