Microsoft Future Ready: Fundamentals to R for Data Science

R is rapidly becoming the leading language in data science and statistics.

Duration

3 weeks

Weekly study

5 hours

Included in an ExpertTrack

Course 4 of 6

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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 a 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 visualisations. No prior knowledge in programming or data science is required.

What makes this course unique is that you will continuously practise 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 personalised feedback that guides you to the correct solution.

This course is designed to give you practical experience in executing commands using R. In this course you will learn the basic syntax of R and prepare you for data analysis using R. Starting with variables and basic operations, we will learn how to handle data structures such as vectors, matrices, data frames, and lists, and we will delve deeper into the graphical capabilities of R to create data visualisation.

Course Outcomes The following are the course learning objectives:

The R language fundamentals and basic syntax What R is and how it’s used to perform data analysis The major R data structures How to create visualizations using R

What topics will you cover?

Introduction to:

  • R language
  • Vectors
  • Matrices
  • Factors
  • Data frames
  • Graphics

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