A Brief Introduction to Data Science

A Brief Introduction to Data Science

A Brief Introduction to Data Science. Data Science, Big Data, Data, and the Data Science process. So this article could serve as an intro to Data Science, and it could be a refresher to it as well. Nonetheless, I hope you learn something from it and have fun reading it.

Full series

Part 1 - What is Data Science, Big data and the Data Science process
Part 2 - The origin of R, why use R, R vs Python and resources to learn
Part 3 - Version Control, Git & GitHub and best practices for sharing code.
Part 4 - The types of questions you ask in Data Science
Part 5 - The ability to design experiments to answer your Ds questions
Part 6 - Big Data, it's benefits, challenges, and future

This series is based on the [Data Science Specialization_](https://www.coursera.org/specializations/jhu-data-science) offered by John Hopkins University on Coursera. The articles in this series are notes based on the course, with additional research and topics for my own learning purposes. For the first course, [Data Scientist Toolbox_](https://www.coursera.org/learn/data-scientists-tools), the notes will be separated into 4 parts. Notes on the series can also be found [here_](http://sux13.github.io/DataScienceSpCourseNotes/)._

Introduction

Data Scientist’s have the ability to find patterns and insights in oceans of data, akin to an astronomer looking out into the deep space with telescopes to find new planets and galaxies and black holes in the midst of billions of stars and other galaxies. Data Science, fundamentally like science, is used to answer questions about the world by combining different fields, ie Mathematics, Computer Science, Philosophy, etc., along with distinct methodologies and novel technology to augment and enhance our ability to answer them well.Whether you’re a beginner who’s new to Data Science, or you’re a working Data Scientist, it’s always good to go back to the central theme of what Data Science is all about. It’s easy to get sidetracked or distracted by new tools or the monotony of work that we forget the principal notion of Data Science and the amazing possibilities that it creates. So this article could serve as an intro to Data Science, and it could be a refresher to it as well. Nonetheless, I hope you learn something from it and have fun reading it.

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