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The R Programming Environment

This course is a part of Mastering Software Development in R, a 5-course Specialization series from Coursera.

This course provides a rigorous introduction to the R programming language, with a particular focus on using R for software development in a data science setting. Whether you are part of a data science team or working individually within a community of developers, this course will give you the knowledge of R needed to make useful contributions in those settings. As the first course in the Specialization, the course provides the essential foundation of R needed for the following courses. We cover basic R concepts and language fundamentals, key concepts like tidy data and related "tidyverse" tools, processing and manipulation of complex and large datasets, handling textual data, and basic data science tasks. Upon completing this course, learners will have fluency at the R console and will be able to create tidy datasets from a wide range of possible data sources.
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Johns Hopkins University

Rating 4.0 based on 165 ratings
Length 5 weeks
Starts Feb 17 (3 days ago)
Cost $49
From Johns Hopkins University via Coursera
Instructors Roger D. Peng, PhD, Brooke Anderson
Download Videos On all desktop and mobile devices
Language English
Subjects Programming Data Science
Tags Computer Science Data Science Data Analysis Software Development

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What people are saying

According to other learners, here's what you need to know

data science in 8 reviews

Would make it much better if it had video tutorials however Felt lost during the final, the course was not well suited to the end quiz Nice Learn basics and some good data science tools.

Except the last programming assignment in week 4, which deals with large dataset that my computer had tough time reading, the course if pretty good and had provided me a basis for specialization in Data Science.

Also a great refresher course after taking the Data Science Specialization.

!...really helpful for building data science concept through R Programming.........Really salute for hardworking of instructor..................!!!

I would recommend to take the other R programming course from the Data Science track before.

Nonetheless I definitely learned a few practical things that will up my data science game (which can always use upping).

If you have done the Data Science Specialization prior, this is a lot of review.

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really enjoyed in 5 reviews

I really enjoyed this course.

I really enjoyed it!

Muy buen curso introductorio de R. Altamente recomendado Really enjoyed the way the course was presented.

I'd recommend the course to anyone interested in doing serious work in R. Really enjoyed and learned a lot.

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final quiz in 4 reviews

Finally, the final quiz material had spaces in the column headings which was fixable but added a level of monotony and inconvenience that was not needed.

My advice - rewrite final quiz and make it more easy for understanding.

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introduction to r. in 3 reviews

A really good introduction to R. very good start English is not my native language so i had troubles with tasks, because it is sometimes hard to understand what you have to do.

I thought it was a really good introduction to R. I thought Swirl was a really good tool as well.

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last week in 3 reviews

I feel that the first weeks are too easy relative to the last week - more involved practice and exercises would have been good before getting to the final quiz.

Basic data manipulation is invaluable when using the scale matrices, the tools that this course has provided me with has had a direct impact on how I conduct my own research and I have changed how I now 'tidy' my data prior to analysis It is a good starting point to utilize the advanced R programming techniques It was very dificul, i think yoou need to improve the example you give the the students and be more interactive Good content, a lot of work loaded in the quiz of the last week, beware of this.

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tidy data in 3 reviews

And have fun with the world of tidy data!

An excellent introduction to the concept of tidy data and the tools to manipulate it.

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Careers

An overview of related careers and their average salaries in the US. Bars indicate income percentile.

AD, Data Science $47k

Associate Data Science Supervisor $55k

Science writer / data analyst $63k

Genomic Data Science Programmer $75k

Volunteer Director of Data Science $78k

Expert Data Science Supervisor $79k

Supervisor 1 Data Science Supervisor $91k

Guest Director of Data Science $101k

Data Science Architect $105k

Head of Data Science $131k

Assistant Director 1 of Data Science $133k

Owner Director of Data Science $149k

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Coursera

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Johns Hopkins University

Rating 4.0 based on 165 ratings
Length 5 weeks
Starts Feb 17 (3 days ago)
Cost $49
From Johns Hopkins University via Coursera
Instructors Roger D. Peng, PhD, Brooke Anderson
Download Videos On all desktop and mobile devices
Language English
Subjects Programming Data Science
Tags Computer Science Data Science Data Analysis Software Development

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