SQL for Data Science

Overview

As data collection has increased exponentially, so has the need for people skilled at using and interacting with data; to be able to think critically, and provide insights to make better decisions and optimize their businesses. This is a data scientist, “part mathematician, part computer scientist, and part trend spotter” (SAS Institute, Inc.). According to Glassdoor, being a data scientist is the best job in America; with a median base salary of $110,000 and thousands of job openings at a time. The skills necessary to be a good data scientist include being able to retrieve and work with data, and to do that you need to be well versed in SQL, the standard language for communicating with database systems.

You will begin to ask the right questions and come up with good answers to deliver valuable insights for your organization. This SQL for Data Science course offered by Coursera in partnership with UC Davis starts with the basics and assumes you do not have any knowledge or skills in SQL. It will build on that foundation and gradually have you write both simple and complex queries to help you select data from tables.  You'll start to work with different types of data like strings and numbers and discuss methods to filter and pare down your results. 

You will create new tables and be able to move data into them. You will learn common operators and how to combine the data. You will use case statements and concepts like data governance and profiling. You will discuss topics on data, and practice using real-world programming assignments. You will interpret the structure, meaning, and relationships in source data and use SQL as a professional to shape your data for targeted analysis purposes. 

Although we do not have any specific prerequisites or software requirements to take this course, a simple text editor is recommended for the final project. So what are you waiting for? This is your first step in landing a job in the best occupation in the US and soon the world!

What You Will Learn

• Identify a subset of data needed from a column or set of columns and write a SQL query to limit to those results.
• U​se SQL commands to filter, sort, and summarize data.
• Create an analysis table from multiple queries using the UNION operator.
• Manipulate strings, dates, & numeric data using functions to integrate data from different sources into fields with the correct format for analysis.