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Coursera

Data Analysis with R

The R programming language is purpose-built for data analysis.

Data Analysis with R is a beginner-level online course from Coursera in Data Analytics. It is structured in 6 modules with 4 stated learning outcomes, over 15h 6m. Learners rate it 4.7/5 from 378 ratings on Coursera.

Part of our Data Analytics courses collection, where we compare it against 22 other courses.

★★★★★4.7(378 reviews) English

Course highlights

Provider Coursera
Duration 15h 6m
Level Beginner
Mode Self-paced
Language English
Certificate Yes — shareable certificate
Rating 4.7★ (378 reviews)
Price Check price Free

What you’ll learn

Prepare data for analysis by handling missing values, formatting and normalizing data, binning, and turning categorical values into numeric values.
Compare and contrast predictive models using simple linear, multiple linear, and polynomial regression methods.
Examine data using descriptive statistics, data grouping, analysis of variance (ANOVA), and correlation statistics.
Evaluate a model for overfitting and underfitting conditions and tune its performance using regularization and grid search.

Level and time commitment

Coursera lists this course at Beginner level.
No prior experience in the subject is assumed — this is where the provider expects a newcomer to start.
Time commitment: 15h 6m.
It is self-paced, so that figure is the material, not a fixed schedule.

Skills you’ll gain

Data ScienceR ProgrammingData TransformationModel TrainingModel EvaluationExploratory Data AnalysisData ManipulationData AnalysisData WranglingRegression AnalysisStatistical MethodsStatistical Visualization

What this course covers

6 modules

The 6-part outline Coursera publishes for this course, across 15h 6m.

Module 1 · Introduction to Data Analysis with R
Module 2 · Data Wrangling
Module 3 · Exploratory Data Analysis
Module 4 · Model Development in R
Module 5 · Model Evaluation
Module 6 · Project

What learners rate it

4.7
★★★★★
378 ratings

Rated 4.7/5 by 378 learners on Coursera (checked 26 Aug 2026).

This rating is collected by Coursera from its own enrolled learners. We reproduce it as reported and do not accept paid or incentivised reviews. See it on Coursera →

How this page is put together

Compiled by the 10courses editorial desk. Fees, ratings, duration and certificate details for the 1 course shown are read directly from Coursera course pages — we never estimate a price or a rating. Last verified 26 August 2026.

How we compare and rank courses · Our review policy · Affiliate disclosure

Compare with alternatives

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Data Analysis with R This Coursera 4.7★ Check price 15h 6m Most popular — 0 learners
Introduction to Data Analytics Coursera 4.8★ Check price 11h 38m Highest rated (4.8★ from 20.8K reviews)
AWS Cloud Practitioner Essentials Coursera 4.8★ Check price 35h 48m Beginner-friendly · 35h 48m
ChatGPT Advanced Data Analysis Coursera 4.8★ Check price 10h 52m Quickest to finish (10h 52m)
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Where Data Analytics leads

Roles we map to Data Analytics on 10courses. This is our own mapping of subject to job, not a placement claim by Coursera.

Data Analyst

Browse every course we track for one of these — courses for data analysts.

Common questions

How much does Data Analysis with R cost?

Coursera does not publish a price we can read on the course page, so we do not show one. Check the fee on the provider site — we would rather say nothing than quote a number we did not collect.

Does Data Analysis with R come with a certificate?

Yes — Coursera lists a certificate on completion. It is a course certificate, not a formal qualification or university credit.

How long does Data Analysis with R take?

Coursera lists it at 15h 6m. It is self-paced, so that is the volume of material rather than a deadline — how long it actually takes depends on the hours you put in each week.

Is Data Analysis with R suitable for beginners?

Yes. Coursera lists it at Beginner level, so no prior experience in the subject is assumed.

What does Data Analysis with R cover?

It is organised into 6 modules, starting with Introduction to Data Analysis with R and going on to Data Wrangling, Exploratory Data Analysis, Model Development in R, Model Evaluation, among others. The full outline is on this page.