Data Analysis with R
This tutorial will teach you the basics of R and how to explore different types of data. You’ll learn how to work with data sources, data cleaning techniques, how to perform statistical analysis, data visualization, and predictive analysis.
By the end of this course, you'll be able to:
- Basic and intermediate programming concepts
- How to clean and visualize data
- Probability and statistics for data analysis
Learn R for Data Analysis
Introduction to Programming in R
Learn the basics of R, a popular programming language for data analysis.
Reading files in R
Use libraries to read different file types in R.
Data Visualization in R
Learn to use the ggplot2 package for exploratory data visualization in R.
Statistics: Fundamentals
Learn about sampling, variables and distributions.
Statistics Intermediate: Averages & Variability
Learn to summarize distributions, measure variability using variance or standard deviation, and compare values using z-scores.
Data Cleaning in R
Learn how to clean and combine datasets, then practice your skills.
Project: Build your own Amazon scraper
Learn to combine the skills you learned to build a scraper which would extract reviews from Amazon.
Sentiment Analysis: Introduction
Learn to do sentiment analysis in R.
Project: Download reviews from Amazon and do a sentiment analysis
Learn to combine the skills you learned to do a sentiment analysis on the reviews obtained from Amazon
