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SQL for Data Science with R

Build a baseline understanding about relational database concepts and learn how to apply foundational knowledge of the SQL and R languages through a series of hands-on labs to practice building and running SQL queries.

SQL for Data Science with R

There is one session available:

After a course session ends, it will be archived.
Starts Oct 22
Estimated 6 weeks
2–3 hours per week
Self-paced
Progress at your own speed
Free
Optional upgrade available

About this course

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A majority of the world's data resides in databases. SQL (or Structured Query Language) is a powerful language for communicating with and extracting data from databases. A working knowledge of databases and the SQL language is a must if you want to become a data scientist. The purpose of this course is to introduce relational database concepts and to help you learn and apply foundational knowledge of the SQL and R languages. It is also intended to get you started with performing SQL access in a data science environment.

The emphasis in this course is on hands-on and practical learning, which means you will work with real databases, real data science tools, and real-world datasets. You will also create a database instance in the cloud. Through a series of hands-on labs you will practice building and running SQL queries. And you will learn how to access databases from Jupyter notebooks using SQL and R.

No prior knowledge of databases, SQL, R, or programming is required.

At a glance

What you'll learn

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  • Create and access a database instance on cloud

  • Write basic SQL statements: CREATE, DROP, SELECT, INSERT, UPDATE, DELETE

  • Filter, sort, group results, use built-in functions, compose nested queries, access multiple tables

  • Access databases from Jupyter using R and SQL to query real-world datasets

About the instructors

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