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Introduction to R for Data Science Course Outline

 (3 days)

Overview
This course is part of the Microsoft Professional Program Certificate in Data Science.

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 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 visualizations. No prior knowledge in programming or data science is required.

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

Enjoy!

Duration
Approximately 4 weeks assuming 2 to 3 hours of effort per week.

What you'll learn
Introductory R language fundamentals and basic syntax
What R is and how its used to perform data analysis
Become familiar with the major R data structures
Create your own visualizations using R

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 behaviour 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: Data Frames
When working R, youll 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 6: Lists
Lists allow you to store components of different types. Section 6 will show you how to deal with lists.

Section 7: Basic Graphics
Discover Rs packages to do graphics and create your own data visualizations.
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