R Programming for Data Analysis and Data Science

Name: R Programming for Data Analysis and Data Science
Rating: 5.0 (1 reviews)

R Programming for Data Analysis: Data Visualization, Statistical Modeling, Machine Learning & Reporting

Created byTraining Que

Last updated 3/2026

English

What you'll learn

Write and execute R scripts to clean, manipulate, and analyze structured and unstructured datasets.
Create professional data visualizations using ggplot2 to communicate insights effectively.
Perform statistical analysis including regression, hypothesis testing, and model evaluation.
Build and assess machine learning models for classification, prediction, and clustering tasks.

Course content

1 section • 14 lectures • 4h 54m total length

Module 120:04
Module 220:18
Module 324:52
Module 424:32
Module 519:37
Module 619:16
Module 719:14
Module 821:58
Module 920:34
Module 1022:53
Module 1122:25
Module 1221:26
Module 1318:01
Module 1419:27

Requirements

No prior R experience required. Basic computer skills and a willingness to learn programming are enough to get started.

Description

This course contains the use of artificial intelligence

Are you ready to master R Programming for Data Analysis and Data Science? This comprehensive course is designed to help you build practical, job-ready skills in data manipulation, statistical analysis, data visualization, and machine learning using R.

R is one of the most powerful and widely used programming languages for data science, analytics, and research. In this course, you will start with the fundamentals of R programming, including data types, functions, control structures, and scripting. From there, you will move into data wrangling using popular libraries such as dplyr and tidyr to clean, transform, and prepare real-world datasets.

You will also learn how to create compelling data visualizations using ggplot2, perform statistical analysis, build predictive models, and apply machine learning techniques. The course covers regression, classification, clustering, and model evaluation to ensure you understand both the theory and practical implementation.

In addition, you will learn how to generate professional reports using R Markdown and effectively communicate your findings to stakeholders.

Whether you are an aspiring data analyst, data scientist, researcher, or student, this course provides the hands-on experience and structured learning path you need to confidently analyze data and extract meaningful insights using R.

Who this course is for:

Aspiring data analysts, data scientists, students, researchers, business professionals, and beginners who want practical R programming skills for data analysis.