Databases and SQL for Data Science

Databases and SQL for Data Science

About this Course
Much of the world's data resides in databases. SQL (or Structured Query Language) is a powerful language which is used for communicating with and extracting data from databases. A working knowledge of databases and SQL is a must if you want to become a data scientist.

The purpose of this course is to introduce relational database concepts and help you learn and apply foundational knowledge of the SQL language. 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 . As such, you will work with real databases, real data science tools, and real-world datasets. You will create a database instance in the cloud. Through a series of hands-on labs you will practice building and running SQL queries. You will also learn how to access databases from Jupyter notebooks using SQL and Python.

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

Anyone can audit this course at no-charge. If you choose to take this course and earn the Coursera course certificate, you can also earn an IBM digital badge upon successful completion of the course.

This course is part of multiple programs
This course can be applied to multiple Specializations or Professional Certificates programs.

Completing this course will count towards your learning in any of the following programs:

  • Introduction to Data Science Specialization
  • IBM Data Science Professional Certificate


WHAT YOU WILL LEARN

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, access multiple tables
Access databases from Jupyter using Python and work with real world datasets

SKILLS YOU WILL GAIN

  • Cloud Databases
  • Python Programming
  • Ipython
  • Relational Database Management System (RDBMS)
  • SQL

Post a Comment

0 Comments