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
- Getting Started with SQL
- In this module, you will be introduced to databases. You will learn how to use basic SQL statements like SELECT, INSERT, UPDATE and DELETE. You will also get an understanding of how to refine your query results with the WHERE clause as well as using COUNT, LIMIT and DISTINCT.
- Introduction to Relational Databases and Tables
- In this module, you’ll learn more about relational database concepts and their importance. This module helps you to understand the process of creating a table in your database on MySQL using the graphical interface and SQL scripts. Further, you will also learn how to alter the entries or delete the entries for any table in the database, or even delete the table itself.
- Intermediate SQL
- This module helps you 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 of using Python to connect to databases. In a Jupyter Notebook, you will create tables, load data, query data using SQL magic and SQLite python library. You will also learn how to analyze data using Python.
- Course Assignment
- In this module, 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 world. You will be assessed on the correctness of your SQL queries and results.
- Bonus Module: Advanced SQL for Data Engineer (Honors)
- This module covers some advanced SQL techniques that will be useful for Data Engineers. In this module, you will learn how to build more powerful queries with advanced SQL techniques like views, transactions, stored procedures, and joins. 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.
Taught by
Rav Ahuja and Hima Vasudevan
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Reviews
2.0 rating, based on 1 Class Central review
4.7 rating at Coursera based on 20589 ratings
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One of the courses you're not sure what they try to achieve. If you know SQL a bit, you'll probably find nothing interesting here. If you don't know - I don't think it's a good place to start.
