Harvard University - Introduction to R for Data Science
- Offered byedX
Introduction to R for Data Science at edX Overview
Duration | 20 hours |
Start from | Start Now |
Total fee | Free |
Mode of learning | Online |
Schedule type | Self paced |
Difficulty level | Beginner |
Official Website | Explore Free Course  |
Credential | Certificate |
Introduction to R for Data Science at edX Highlights
- Offered By University of London, Birkbeck, University of London
- Requires effort of 2-3 hours per week
- Get a certificate for Rs. 7592 from Microsoft
- Learn from expert instructors of Microsoft & DataCamp
Introduction to R for Data Science at edX Course details
- Introductory R language fundamentals and basic syntax
- What R is and how it's used to perform data analysis
- Become familiar with the major R data structures
- Create your own visualizations using R
- 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.
Introduction to R for Data Science at edX Curriculum
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, 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.
Section6: 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 R's packages to do graphics and create your own data visualizations.
Introduction to R for Data Science at edX Entry Requirements
- None, but previous experience in basic mathematics is helpful.
- Not mentioned
Introduction to R for Data Science at edX Admission Process
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