Introduction to R for Data Science

Learn the R statistical programming language, the lingua franca of data science in this hands-on course.

Created by: Jonathan Sanito

Produced in 2018

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Overall Score : 88 / 100

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Course Description

R is rapidly becoming the leading language in data science and statistics. Today, R is the tool of choice for data science professionals in every industry and field. Whether you are full-time number cruncher, or just the occasional data analyst, R will suit your needs.
This introduction to R programming course will help you master the basics of R. In seven sections, you will cover its basic syntax, making you ready to undertake your own first data analysis using R. Starting from variables and basic operations, you will eventually learn how to handle data structures such as vectors, matrices, data frames and lists. In the final section, you will dive deeper into the graphical capabilities of R, and create your own stunning data visualizations. No prior knowledge in programming or data science is required.
What makes this course unique is that you will continuously practice your newly acquired skills through interactive in-browser coding challenges using the DataCamp platform. Instead of passively watching videos, you will solve real data problems while receiving instant and personalized feedback that guides you to the correct solution.
Enjoy!
edX offers financial assistance for learners who want to earn Verified Certificates but who may not be able to pay the fee. To apply for financial assistance, enroll in the course, then follow this link to complete an application for assistance.
Section 1: Introduction to Basics
Take your first steps with R. Discover the basic data types in R and assign your first variable.
Section 2: Vectors
Analyze gambling behaviour using vectors. Create, name and select elements from vectors.
Section 3: Matrices
Learn how to work with matrices in R. Do basic computations with them and demonstrate your knowledge by analyzing the Star Wars box office figures.
Section 4: Factors
R stores categorical data in factors. Learn how to create, subset and compare categorical data.
Section 5: Data Frames
When working R, you'll probably deal with Data Frames all the time. Therefore, you need to know how to create one, select the most interesting parts of it, and order them.
Section6: Lists
Lists allow you to store components of different types. Section 6 will show you how to deal with lists.
Section 7: Basic Graphics
Discover R's packages to do graphics and create your own data visualizations.

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Instructor Details

Jonathan Sanito

Jonathan works as a content developer and project manager for Microsoft focusing in Data and Analytics online training. He has worked with trainings for developer and IT pro audiences, from Microsoft Dynamics NAV to Windows Active Directory. Before coming to Microsoft, Jonathan worked as a consultant for a Microsoft partner, implementing Microsoft Dynamics NAV solutions.

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Reviews

4.4

13 total reviews

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By Hchan H on 12/15/2015

This course is actually more like half a course, but it does that half extremely well. This class will give you solid foundations in the basic data structures of R, and it does so very efficiently and very well - just a few minutes of lectures and exercises and you've learnt what is needed - demonstrating the effectiveness of Datacamp's platform. There is no coverage on control flow, functions, or vectorized operations, which is needed for an actual working knowledge of R.

By Bob B on 10/23/2015

This is a very useful introduction to R. I was taking the DAT203X - Data Science and they suggested to take an R or Python to follow along better. It was well worth it. You get a basic understanding of data structures, operators, and basic graphing.

By Aliaksandr B on 11/4/2015

A good course overall especially for novices. Material is very basic and covers only simplest data-structures and graphics. Course designed for those who can not program at all.

By Farsan R on 9/20/2015

Only because of one ambiguous assignment I am not giving it 5 stars but I highly recommend this course to anyone who wants to start R programming.

By Dmitriy Prokopyev on 8/12/2015

It is the best course for non-programmers who are wishing to start their Data Science carrier using R Programming language as a tool. I have done similar courses in another well know online source, but that one forcing students to use from begging tools like Git Bash and Git.

By Elisa Jacobs on 11/23/2019

The content was good I think but it's sad to see that you can only get access to the exercices if you pay for it. I am a student myself, so I'm not able to afford the full version

By Lawrence Wong on 6/15/2019

Good way to get started! Lot of great examples, and the data camp platform that's particularly good for self-study and independent learners.

By Joanna Ochen on 3/30/2019

The course was good but I don't feel satisfied. First problem: I had too short time to complete the course. It should be much longer, like 1-2 months. Because of the limited time I hadn't time to practice and understand the basics. Second problem: sometimes I had impression that in the videos there were basics of the basics, and then in the "practical" part everything was much much more difficult, the commands weren't clear , I didn't understand what to do, and because of the limited time I couldn't explore the tasks.

By Oscar Snchez on 12/12/2018

I consider that the course is widely recommended for people with a desire to learn the basics of R. It is perfectly formulated, structured and explained. The teaching times are optimal. The exercises are excellent for putting knowledge into practice. They really challenge your intellect to solve them. This course is a must.

By Wallace Calzita on 11/6/2018

Overall I found the course very informative for beginners who want to learn and understand the basics of data analytics. The content was excellently delivered.

By Adam H on 9/1/2018

Excellent program designed to deliver R for the novice. The course material was very good and the instructor was clear and knowledgeable about the subject. The final exam could have been designed more effectively to ensure clarity.

By Martyn Roddy on 3/16/2018

The course is well designed and structured in an interesting way, and is a great intro to R. Course content, timescale and layout make it easy to spread out the learning time. Videos are well presented and not too long.