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Introduction to R Programming for Data Science
  • Level Foundation
  • Duration 11 hours
  • Course by IBM
  • Offered by

About

When working in the data science field you will definitely become acquainted with the R language and the role it plays in data analysis. This course introduces you to the basics of the R language such as data types, techniques for manipulation, and how to implement fundamental programming tasks. You will begin the process of understanding common data structures, programming fundamentals and how to manipulate data all with the help of the R programming language. The emphasis in this course is hands-on and practical learning . You will write a simple program using RStudio, manipulate data in a data frame or matrix, and complete a final project as a data analyst using Watson Studio and Jupyter notebooks to acquire and analyze data-driven insights. No prior knowledge of R, or programming is required.

Modules

Course Introduction

    • 1 Videos
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1 Videos

  • Welcome to Introduction to R Programming for Data Science

R Basics

    • 6 Videos
    • 1 Readings
    • 1 Quiz
    • 2 ExternalTool
    • 1 Assignment
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1 Assignment

  • Practice Quiz

2 External Tool

  • Hello World with R using RStudio
  • Basic Math with R using Jupyter Notebook

6 Videos

  • Introduction to R Language
  • Basic Data Types
  • Math, Variables, and Strings
  • R Environment
  • Introduction to RStudio
  • Writing and Running R in Jupyter Notebooks

1 Readings

  • Summary & Highlights

1 Quiz

  • Graded Quiz

Common Data Structures

    • 5 Videos
    • 1 Readings
    • 3 ExternalTool
    • 2 Assignment
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2 Assignment

  • Practice Quiz
  • Graded Quiz

3 External Tool

  • Hands-on Lab: Vectors and Factors
  • Hands-on Lab: Arrays and Matrices
  • Hands-on Lab: Lists and Dataframe in R

5 Videos

  • Vectors and Factors
  • Vector Operations
  • Lists
  • Arrays and Matrices
  • Data Frames

1 Readings

  • Summary & Highlights

R Programming Fundamentals

    • 6 Videos
    • 1 Readings
    • 3 ExternalTool
    • 2 Assignment
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2 Assignment

  • Practice Quiz
  • Graded Quiz

3 External Tool

  • Hands-on Lab: Conditions and Loops
  • Hands-on Lab: Functions in R
  • Hands-on Lab: Strings and Regular Expressions

6 Videos

  • Conditions and Loops
  • Functions in R
  • String Operations in R
  • Regular Expressions
  • Date Format in R
  • Debugging

1 Readings

  • Summary & Highlights

Working with Data

    • 5 Videos
    • 1 Readings
    • 3 ExternalTool
    • 2 Assignment
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2 Assignment

  • Practice Quiz
  • Graded Quiz

3 External Tool

  • Hands-on Lab: Importing Data in R
  • Hands-on Lab: HTTP Requests in R
  • Hands-on Lab: Webscraping in R

5 Videos

  • Reading CSV, Excel, and Built-in Datasets
  • Reading Text Files in R
  • Writing and Saving to Files
  • HTTP Request and REST API
  • Web Scraping in R

1 Readings

  • Summary & Highlights

Final Project

    • 1 PeerReview
    • 1 ExternalTool
    • 1 Plugin
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1 External Tool

  • Hands-on Lab: Final Project

1 Peer Review

  • Peer Review: Submit your Work and Review your Peers

Final Exam

    • 1 Assignment
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1 Assignment

  • Final Exam

Course Wrap Up

    • 1 Readings
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1 Readings

  • Congratulations & Next Steps

Credits and Acknowledgments

    • 1 Readings
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1 Readings

  • Credits and Acknowledgments

Auto Summary

Embark on your data science journey with "Introduction to R Programming for Data Science" on Coursera. This foundational course, led by industry experts, focuses on R language basics, data manipulation, and programming fundamentals. Over 660 minutes, engage in hands-on learning with RStudio, Watson Studio, and Jupyter notebooks. Ideal for beginners, no prior programming knowledge required. Subscribe with the Starter option to get started.

Yan Luo
Instructor

Yan Luo