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Hello and welcome to SQL for data science.

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The demand for data scientists is high,

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boasting a median base salary of $110,000 and job satisfaction score of 4.4 out of five.

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It's no wonder that it's the top spot on Glassdoor's best jobs in America.

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Glassdoor analyzed data from data scientist job postings on

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Glassdoor and found that SQL is listed

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as one of the top three skills for a data scientist.

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Before you step into the field of data science,

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it is vitally important that you set yourself

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apart by mastering the foundations of this field.

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One of the foundational skills that you will require is SQL.

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SQL is a powerful language that's used for communicating with databases.

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Every application that manipulates any kind of data

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needs to store that data somewhere; whether it's big data,

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or just a table with a few simple rows for government, or a small startup,

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or a big database that spans over

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multiple servers or a mobile phone that runs its own small database.

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Here are some of the advantages of learning SQL for someone interested in data science.

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SQL will boost your professional profile as a data scientist,

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as it is one of the most sought after skills by hiring employers.

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Learning SQL will give you a good understanding of relational databases.

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Tapping into all this information requires being able

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to communicate with the databases that store the data.

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Even if you work with reporting tools that generate SQL queries for you,

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it may be useful to write your own SQL statements so that you need

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not wait for other team members to create SQL statements for you.

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In this course, you will learn the basics of

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both the SQL language and relational databases.

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The course includes interesting quizzes and hands on lab assignments,

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where you can get experience working with databases.

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In the first few modules,

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you work directly with the database and develop a working knowledge of SQL.

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Then, you will connect to a database and run

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SQL queries like a data scientist typically would,

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where you will use Python and Jupyter notebooks to connect

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to relational databases to access and analyze data.

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There is also an assignment included towards the end of the course,

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where you will get an opportunity to apply the concepts that you learned.

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So, let's get started with SQL for data science.