SQL for Data Scientists

SQL for Data ScientistsCondition: BRAND NEW ISBN: 9781119669364 Year: 2021 Publisher: John Wiley & Sons Inc (US) Pages: 288 Description: Jump start your career as a data scientistlearn to develop datasets for exploration, analysis, and machine learning SQL for Data Scientists: A Beginner's Guide for Building Datasets for Analysis is a resource thats dedicated to the Structured Query Language (SQL) and dataset design skills that data scientists use most. Aspiring data

Condition: BRAND NEW
ISBN: 9781119669364
Year: 2021
Publisher: John Wiley & Sons Inc (US)
Pages: 288


Description:


Jump-start your career as a data scientist—learn to develop datasets for exploration, analysis, and machine learning


SQL for Data Scientists: A Beginner's Guide for Building Datasets for Analysis is a resource that’s dedicated to the Structured Query Language (SQL) and dataset design skills that data scientists use most. Aspiring data scientists will learn how to how to construct datasets for exploration, analysis, and machine learning. You can also discover how to approach query design and develop SQL code to extract data insights while avoiding common pitfalls.


You may be one of many people who are entering the field of Data Science from a range of professions and educational backgrounds, such as business analytics, social science, physics, economics, and computer science. Like many of them, you may have conducted analyses using spreadsheets as data sources, but never retrieved and engineered datasets from a relational database using SQL, which is a programming language designed for managing databases and extracting data.


This guide for data scientists differs from other instructional guides on the subject. It doesn’t cover SQL broadly. Instead, you’ll learn the subset of SQL skills that data analysts and data scientists use frequently. You’ll also gain practical advice and direction on "how to think about constructing your dataset."


Gain an understanding of relational database structure, query design, and SQL syntax

Develop queries to construct datasets for use in applications like interactive reports and machine learning algorithm