Introduction to Data Science

Download free course Introduction to Data Science, pdf file on 722 pages by Rafael A Irizarry.
The demand for skilled data science practitioners in industry, academia, and government is rapidly growing. This book introduces concepts and skills that can help you tackle real-world data analysis challenges. It covers concepts from probability, statistical inference, linear regression and machine learning. It also helps you develop skills such as R programming, data wrangling with dplyr, data visualization with ggplot2, algorithm building with caret, file organization with UNIX/Linux shell, version control with Git and GitHub, and reproducible document preparation with knitr and R markdown. The book is divided into six parts: R, Data Visualization, Data Wrangling, Probability, Inference and Regression with R, Machine Learning, and Productivity Tools. Each part has several chapters meant to be presented as one lecture. The book includes dozens of exercises distributed across most chapters.

Table of contents

  • R
  • Getting Started with R and RStudio
  • R Basics
  • Programming basics
  • The tidyverse
  • Importing data
  • Data Visualization
  • Introduction to data visualization
  • ggplot2
  • Visualizing data distributions
  • Data visualization in practice
  • Data visualization principles
  • Robust summaries
  • Statistics with R
  • Introduction to Statistics with R
  • Probability
  • Random variables
  • Statistical Inference
  • Statistical models
  • Regression
  • Linear Models
  • Association is not causation
  • Data Wrangling
  • Introduction to Data Wrangling
  • Reshaping data
  • Joining tables
  • Web Scraping
  • String Processing
  • Parsing Dates and Times
  • Text mining
  • Machine Learning
  • Introduction to Machine Learning
  • Smoothing
  • Cross validation
  • The caret package
  • Examples of algorithms
  • Machine learning in practice
  • Large datasets
  • Clustering
  • Productivity tools
  • Introduction to productivity tools
  • Organizing with Unix
  • Git and GitHub
  • Reproducible projects with RStudio and R markdown
Pages : 722
Size : 55.8 MB
File type : PDF
Downloads: 178
Created: 2022-02-03
License: CC BY-NC-SA
Author(s): Rafael A Irizarry
Introduction to Data Science

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