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Working knowledge of SQL (or Structured Query Language) is a must for data professionals like Data Scientists, Data Analysts and Data Engineers. Much of the world's data resides in databases. SQL is a powerful language used for communicating with and extracting data from databases.
In this course you will learn SQL inside out- from the very basics of Select statements to advanced concepts like JOINs.
You will:
-write foundational SQL statements like: SELECT, INSERT, UPDATE, and DELETE
-filter result sets, use WHERE, COUNT, DISTINCT, and LIMIT clauses
-differentiate between DML & DDL
-CREATE, ALTER, DROP and load tables
-use string patterns and ranges; ORDER and GROUP result sets, and built-in database functions
-build sub-queries and query data from multiple tables
-access databases as a data scientist using Jupyter notebooks with SQL and Python
-work with advanced concepts like Stored Procedures, Views, ACID Transactions, Inner & Outer JOINs
Through hands-on labs and projects, you will practice building SQL queries, work with real databases on the Cloud, and use real data science tools. In the final project you’ll analyze multiple real-world datasets to demonstrate your skills.
Overview
Syllabus
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- Getting Started with SQL
- In this module, you will be introduced to databases. You will create a database instance on the cloud. You will learn some of the basic SQL statements. You will also write and practice basic SQL hands-on on a live database.
- Introduction to Relational Databases and Tables
- In this module, you will explore the fundamental concepts behind databases, tables, and the relationships between them. You will then create an instance of a database, discover SQL statements that allow you to create and manipulate tables, and then practice them on your own live database.
- Intermediate SQL
- In this module, you will learn how to use string patterns and ranges to search data and how to sort and group data in result sets. You will also practice composing nested queries and execute select statements to access data from multiple tables.
- Accessing Databases using Python
- In this module you will learn the basic concepts related to using Python to connect to databases. In a Jupyter Notebook, you will create tables, load data, query data using SQL, and analyze data using Python.
- Course Assignment
- In this assignment, you will be working with multiple real world datasets for the city of Chicago. You will be asked questions that will help you understand the data just as you would in the real wold. You will be assessed on the correctness of your SQL queries and results.
- Bonus Module: Advanced SQL for Data Engineering (Honors)
- This module covers some advanced SQL techniques that will be useful for Data Engineers. If you are following the Data Engineering track, you must complete this module. Completion of this module is not required for those completing the Data Science or Data Analyst tracks. In this module, you will learn how to build more powerful queries with advanced SQL techniques like views, transactions, stored procedures and joins.
