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R Programming Coursera

Highlights
Tuition fee
Free
Free
Unknown
Tuition fee
Free
Free
Unknown
Duration
2 days
Duration
2 days
Apply date
Anytime
Unknown
Apply date
Anytime
Unknown
Start date
Anytime
Unknown
Start date
Anytime
Unknown
Taught in
English
Taught in
English

About

In this R Programming offered by Coursera in partnership with Johns Hopkins University, you will learn how to programme in R and how to use R for effective data analysis. 

Overview

You will learn how to install and configure software necessary for a statistical programming environment and describe generic programming language concepts as they are implemented in a high-level statistical language. The R Programming offered by Coursera in partnership with Johns Hopkins University covers practical issues in statistical computing which includes programming in R, reading data into R, accessing R packages, writing R functions, debugging, profiling R code, and organizing and commenting R code. Topics in statistical data analysis will provide working examples.

What you will learn

  • Collect detailed information using R profiler
  • Configure statistical programming software
  • Make use of R loop functions and debugging tools
  • Understand critical programming language concepts

Programme Structure

Courses include:

  • Background, Getting Started, and Nuts & Bolts
  • Programming with R
  • Loop Functions and Debugging
  • Simulation & Profiling

Key information

Duration

  • Part-time
    • 2 days

Start dates & application deadlines

You can apply for and start this programme anytime.

Language

English

Delivered

Online
  • Self-paced

Campus Location

  • Mountain View, United States

What students do after studying

Join for free or log in to access our complete career info list.

Academic requirements

We are not aware of any specific GRE, GMAT or GPA grading score requirements for this programme.

English requirements

We are not aware of any English requirements for this programme.

Other requirements

General requirements

Intermediate Level

  • Familiarity with regression is recommended.
  • To obtain additional information about the programme, we kindly suggest that you visit the programme website, where you can find further details and relevant resources.  

Tuition Fees

Tuition fees are shown in and the most likely applicable fee is shown based on your nationality.
  • International

    Non-residents
    Free
  • Out-of-State
    Free

Additional Details

  • Audit: free access to course materials except graded items
  • Certificate: a trusted way to showcase your skills
  • A year of unlimited access with Coursera Plus $399

Funding

Coursera provides financial aid to learners who cannot afford the fee. Apply for it by clicking on the Financial Aid link beneath the "Enroll" button on the left. You'll be prompted to complete an application and will be notified if you are approved. You'll need to complete this step for each course in the Specialization, including the Capstone Project.

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