Introduction to Data Science
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.
Download free tutorial in PDF (722 pages) created by Rafael A Irizarry .
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Take advantage of this course called Introduction to Data Science to improve your Programming skills and better understand Data Science.
This course is adapted to your level as well as all Data Science pdf courses to better enrich your knowledge.
All you need to do is download the training document, open it and start learning Data Science for free.
This tutorial has been prepared for the beginners to help them understand basic Data Science Programming. After completing this tutorial you will find yourself at a moderate level of expertise in Data Science from where you can take yourself to next levels.
This tutorial is designed for Data Science students who are completely unaware of Data Science concepts but they have basic understanding on Programming training.
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