Big Data with R


Learn how to process and manipulate Big Data with R language, including data visualization, statistical and machine learning algorithms.

About this course

The Big Data with R course is designed to introduce participants to the world of big data and the powerful R programming language. The course will start by introducing the concepts and challenges of big data, including the volume, variety, and velocity of big data, as well as the tools and technologies that are used to manage and analyze it.

The course will then dive into the R programming language, starting with the basics of data manipulation and visualization. Participants will learn how to use R to import, clean, and explore large datasets, and will gain hands-on experience working with a variety of data visualization tools.

As the Big Data with R course progresses, participants will learn about advanced statistical and machine learning techniques, using R’s extensive library of algorithms. Topics will include linear and logistic regression, random forests, and neural networks.

Participants will work on real-world case studies and projects, which will give them the opportunity to apply their new skills and knowledge to actual big data scenarios.

By the end of the Big Data with R course, participants will have a solid understanding of big data concepts and the R programming language, as well as the skills to manipulate, visualize, and analyze large datasets.

This course is suitable for anyone interested in data science, big data, and R, including data analysts, data scientists, and business professionals who want to learn more about big data and R.

What is Big Data?

Big data refers to the vast amounts of structured and unstructured data that are generated and collected by organizations and individuals on a daily basis. This data can come from a wide range of sources, including social media, online transactions, sensor data, and more. The sheer volume, variety, and velocity of big data make it challenging to process and analyze using traditional methods.

One of the key challenges of big data is the ability to store, manage, and analyze it in a timely and efficient manner. This requires powerful tools and technologies, such as distributed computing and data storage systems, as well as specialized software and algorithms. One of the most popular and widely-used programming languages for big data is R.

Why learn Big Data with R Language?

R is an open-source programming language that was developed specifically for data analysis and statistical computing. It is widely used in a variety of industries, including finance, healthcare, marketing, and more.

R has a number of advantages when it comes to working with big data, including its powerful data manipulation and visualization capabilities, as well as its extensive library of statistical and machine learning algorithms.



Short Course
Experience Level
20 hours
Free Trial

Frequently Asked Questions

What is a short course?

With a short course, you’ll typically deep-dive into a specific area of interest within a broader topic.

Short courses are typically between 1 and 12 hours in duration, and in the case of guided courses (i.e. with live instructors), are sometimes spread over a number of days or weeks. Most short courses are self-paced, which means you progress through a series of videos and projects at your own pace.

Depending on the institution and the platform, you may also get a certificate of completion that you can add to your LinkedIn profile.

Is this really 100% online?

This course is completely online, so you can study from anywhere! All you’ll need is a device with an internet connection, such as a computer or a smartphone. If the course has any live, instructor-led sessions, you may need a microphone and possibly a webcam to fully participate. The instructor will make you aware of this beforehand.