Databases and SQL for Data Science with Python Description:
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.
- 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
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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.