Introduction to R for Data Science: An online course by Microsoft

Microsoft is conducting an online course on Learn the R statistical programming language, the lingua franca of data science.The course enables students to solve real data problems while receiving instant and personalized feedback that guides you to the correct solution.

About The Course:

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 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.

 Intro to R for Data Science: An online course

Course Syllabus:

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 behavior 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: Lists

Lists allow you to store components of different types. Learn how to work with lists.

Sections 6: 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.

Section 7: Basic Graphics

Discover R's packages to do graphics and create your own data visualizations


Prior experience is not mandatory, but experience in basic mathematics is helpful.

Course Details:

  • Course Length: 4 weeks
  • Course Starts on: April 1

For more details on the course, visit the website

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