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Build R Skills with Projects

R Programming projects can help you learn data manipulation, statistical analysis, and data visualization techniques. You can build skills in creating reproducible reports, developing algorithms, and implementing machine learning models. Many courses introduce tools like RStudio and libraries such as ggplot2 and dplyr, that support transforming raw data into actionable insights and presenting findings effectively.

Full List of R Projects


  • C

    Coursera

    Getting Started with R

    Skills you'll gain: R (Software), Data Import/Export, Package and Software Management, R Programming, Data Structures, Software Installation, Data Analysis Software, Data Analysis, Data Science

    4.3
    Rating, 4.3 out of 5 stars
    ·
    386 reviews

    Beginner · Guided Project · Less Than 2 Hours

  • C

    Coursera

    Introduction to R: Basic R syntax

    Skills you'll gain: R (Software), R Programming, Computational Logic, Arithmetic, Statistical Programming, Development Environment, Programming Principles, Data Import/Export

    4.5
    Rating, 4.5 out of 5 stars
    ·
    52 reviews

    Beginner · Guided Project · Less Than 2 Hours

  • C

    Coursera

    Calculating Descriptive Statistics in R

    Skills you'll gain: Descriptive Statistics, Data Analysis, Exploratory Data Analysis, Quantitative Research, R Programming, Statistical Analysis, Histogram, R (Software), Statistical Methods, Statistical Programming, Probability & Statistics, Descriptive Analytics, Statistics, Statistical Software, Data Science

    4.8
    Rating, 4.8 out of 5 stars
    ·
    52 reviews

    Beginner · Guided Project · Less Than 2 Hours

  • C

    Coursera

    Data Analysis in R: Predictive Analysis with Regression

    Skills you'll gain: Ggplot2, Model Evaluation, Plot (Graphics), Regression Analysis, Predictive Analytics, Predictive Modeling, Statistical Visualization, Data-Driven Decision-Making, Statistical Modeling, R Programming, Descriptive Statistics, R (Software), Exploratory Data Analysis, Descriptive Analytics, Statistical Analysis, Data Analysis

    4.2
    Rating, 4.2 out of 5 stars
    ·
    13 reviews

    Intermediate · Guided Project · Less Than 2 Hours

  • C

    Coursera

    Getting Started with Rstudio

    Skills you'll gain: Interactive Data Visualization, Plot (Graphics), R (Software), Hypertext Markup Language (HTML), Software Installation, Package and Software Management, R Programming, Integrated Development Environments, Statistical Programming

    4.6
    Rating, 4.6 out of 5 stars
    ·
    146 reviews

    Beginner · Guided Project · Less Than 2 Hours

  • C

    Coursera

    Build and deploy a stroke prediction model using R

    Skills you'll gain: Feature Engineering, Model Evaluation, Predictive Modeling, Model Deployment, Model Training, Predictive Analytics, R (Software), R Programming, Data Analysis, Statistical Modeling, Statistical Analysis, Data Wrangling, Data Cleansing, Data Manipulation, Classification Algorithms, Data Import/Export, Data Preprocessing, Data Presentation, Machine Learning

    4.5
    Rating, 4.5 out of 5 stars
    ·
    33 reviews

    Intermediate · Guided Project · Less Than 2 Hours

What brings you to Coursera today?

  • C

    Coursera

    Data Visualization using dplyr and ggplot2 in R

    Skills you'll gain: Ggplot2, Plot (Graphics), Tidyverse (R Package), Data Visualization, Statistical Visualization, Data Analysis, Exploratory Data Analysis, R Programming, Data Visualization Software, Data Wrangling, Data Manipulation, R (Software)

    5
    Rating, 5 out of 5 stars
    ·
    20 reviews

    Intermediate · Guided Project · Less Than 2 Hours

  • C

    Coursera

    Joining Data in R using dplyr

    Skills you'll gain: Data Cleansing, Data Manipulation, Data Integration, R Programming, Data Wrangling, Data Preprocessing, Tidyverse (R Package), Data Processing, R (Software), Data Management

    4.2
    Rating, 4.2 out of 5 stars
    ·
    6 reviews

    Intermediate · Guided Project · Less Than 2 Hours

  • C

    Coursera

    Tidy Messy Data using tidyr in R

    Skills you'll gain: Ggplot2, Plot (Graphics), Data Cleansing, Tidyverse (R Package), Data Wrangling, Data Transformation, Data Visualization, R Programming, Data Manipulation, Statistical Visualization, R (Software), Data Analysis, Data Management, Pivot Tables And Charts

    4.6
    Rating, 4.6 out of 5 stars
    ·
    10 reviews

    Intermediate · Guided Project · Less Than 2 Hours

  • C

    Coursera

    Demand Planning in RStudio: Create Demand Forecast

    Skills you'll gain: Demand Planning, Customer Demand Planning, Supply Chain Planning, Production Planning, Forecasting, Time Series Analysis and Forecasting, Trend Analysis, Inventory Management System, Data Analysis, Plot (Graphics), R Programming, Data Visualization, R (Software), Model Evaluation, Model Training

    Intermediate · Guided Project · Less Than 2 Hours

  • C

    Coursera

    RStudio for Six Sigma - Basic Descriptive Statistics

    Skills you'll gain: Sampling (Statistics), Plot (Graphics), Statistical Methods, Descriptive Statistics, Statistical Visualization, Data Import/Export, Pareto Chart, Histogram, Statistical Programming, Descriptive Analytics, Statistical Analysis, R (Software), Box Plots, R Programming, Data Synthesis, Probability Distribution, Probability & Statistics, Exploratory Data Analysis, Statistics, Data Science

    4.6
    Rating, 4.6 out of 5 stars
    ·
    68 reviews

    Beginner · Guided Project · Less Than 2 Hours

  • C

    Coursera

    R أساسيات لغة البرمجة

    Skills you'll gain: R (Software), Exploratory Data Analysis, R Programming, Data Manipulation, File I/O, Statistical Programming, Data Analysis, File Management, Integrated Development Environments, Programming Principles, Data Science, Data Structures, Computer Programming

    Beginner · Guided Project · Less Than 2 Hours

1234

Best R courses from Coursera

Top-rated R courses offered by Coursera on Coursera.

  1. 1
    Getting Started with R
    CourseraBeginnerLess Than 2 Hours4.3(386)Coursera
  2. 2
    Introduction to R: Basic R syntax
    CourseraBeginnerLess Than 2 Hours4.5(52)Coursera
  3. 3
    Calculating Descriptive Statistics in R
    CourseraBeginnerLess Than 2 Hours4.8(52)Coursera

Best R courses for beginners

Top-rated beginner-friendly R courses with no prerequisites.

  1. 1
    Getting Started with Rstudio
    CourseraBeginnerLess Than 2 Hours4.6(146)No prerequisites
  2. 2
    RStudio for Six Sigma - Basic Descriptive Statistics
    CourseraBeginnerLess Than 2 Hours4.6(68)No prerequisites
  3. 3
    R أساسيات لغة البرمجة
    CourseraBeginnerLess Than 2 Hours4.8(4)No prerequisites

Best short R courses

Quick R courses you can complete in a few hours or less.

  1. 1
    Data Analysis in R: Predictive Analysis with Regression
    CourseraIntermediateLess Than 2 Hours4.2(13)Quick completion
  2. 2
    Build and deploy a stroke prediction model using R
    CourseraIntermediateLess Than 2 Hours4.5(33)Quick completion
  3. 3
    Data Visualization using dplyr and ggplot2 in R
    CourseraIntermediateLess Than 2 Hours5.0(20)Quick completion

Skills you can learn in Data Analysis

Analytics (85)
Big Data (64)
Python Programming (47)
Business Analytics (40)
R Programming (37)
Statistical Analysis (36)
Sql (33)
Data Model (29)
Data Mining (27)
Exploratory Data Analysis (26)
Data Modeling (21)
Data Manipulation (20)

Frequently Asked Questions about R

R is a programming language and software environment primarily used for statistical computing and data analysis. It is important because it provides a robust framework for data manipulation, statistical modeling, and visualization, making it a popular choice among data scientists, statisticians, and researchers. R's extensive libraries and packages enable users to perform complex analyses and create high-quality graphics, which are essential in various fields such as finance, healthcare, and social sciences.‎

With skills in R, you can pursue various job roles, including data analyst, data scientist, statistician, and research analyst. These positions often require the ability to analyze data sets, create visualizations, and interpret statistical results. Additionally, R is valuable in industries such as finance, healthcare, and academia, where data-driven decision-making is crucial. As organizations increasingly rely on data, the demand for professionals skilled in R continues to grow.‎

To effectively learn R, you should focus on several key skills. First, understanding the basics of programming concepts is essential, including data types, control structures, and functions. Next, familiarize yourself with data manipulation and analysis using packages like dplyr and tidyr. Additionally, learning how to visualize data with ggplot2 and perform statistical analyses will enhance your capabilities. Finally, gaining experience with R Markdown for reporting and documentation can significantly improve your workflow.‎

Some of the best online courses for learning R include the Applied Data Science with R Specialization and the Data Science: Foundations using R Specialization. These courses cover essential topics such as data manipulation, visualization, and statistical analysis, providing a comprehensive foundation for anyone looking to enhance their skills in R.‎

__Yes. You can start learning r on Coursera for free in two ways:

  1. Preview the first module of many r courses at no cost. This includes video lessons, readings, graded assignments, and Coursera Coach (where available).
  2. Start a 7-day free trial for Specializations or Coursera Plus. This gives you full access to all course content across eligible programs within the timeframe of your trial.

If you want to keep learning, earn a certificate in r, or unlock full course access after the preview or trial, you can upgrade or apply for financial aid.__‎

To learn R effectively, start by exploring online courses that introduce the basics of the language. Engage with interactive coding environments and practice writing R scripts. Utilize resources like R documentation and community forums for support. Additionally, working on real-world projects can help reinforce your learning and build your portfolio.‎

R courses typically cover a range of topics, including data manipulation, statistical analysis, data visualization, and machine learning. You may also encounter specialized subjects such as time series analysis, data wrangling, and reporting with R Markdown. These topics equip learners with the skills needed to analyze and interpret data effectively.‎

For training and upskilling employees, the IBM Data Analytics with Excel and R Professional Certificate and the Data Analytics in the Public Sector with R Specialization are excellent options. These programs focus on practical applications of R in various industries, helping employees develop relevant skills that can be applied directly to their work.‎

This FAQ content has been made available for informational purposes only. Learners are advised to conduct additional research to ensure that courses and other credentials pursued meet their personal, professional, and financial goals.

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