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.
Databases and SQL for Data Science with Python
Databases and SQL for Data Science with Python
This course is part of multiple programs.
Instructors: Rav Ahuja
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Gain insight into a topic and learn the fundamentals.
4.7
(21,734 reviews)
Beginner level
Recommended experience
Flexible schedule
Approx. 20 hours
Learn at your own pace
94%
Most learners liked this course
What you'll learn
Analyze data within a database using SQL and Python.
Create a relational database and work with multiple tables using DDL commands.
Construct basic to intermediate level SQL queries using DML commands.
Compose more powerful queries with advanced SQL techniques like views, transactions, stored procedures, and joins.
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Assessments
17 assignments
Taught in English
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There are 6 modules in this course
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.
What's included
6 videos2 readings2 assignments3 app items3 plugins
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.
What's included
5 videos2 readings2 assignments3 app items4 plugins
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.
What's included
7 videos4 readings4 assignments4 app items2 plugins
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.
What's included
6 videos2 readings2 assignments7 app items1 plugin
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.
What's included
2 videos3 readings2 assignments3 app items
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.
What's included
6 videos4 readings5 assignments5 app items2 plugins
Instructors
Instructor ratings
4.6 (3,621 ratings)Offered by
Recommended if you're interested in Data Analysis
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4.7
21,734 reviews
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Showing 3 of 21734
MM
4
Reviewed on Oct 6, 2023
This course was an Excellent, Interesting, and knowledgeful game for me. I have been excited to lean SQL and Databases and finally IBM and Coursera let my dream come true. Thanks both of them!
SR
5
Reviewed on Aug 25, 2022
I am thankful to coursera for providing database and sql for data science course in such a way that anyone canunderstand the basic fundamental of sql and database. I learn a lot from this course.
RK
4
Reviewed on Jan 6, 2022
Most of it really good. I think joins should be covered in the base material and there should be less of an emphasis on sub-queries. The Peer Reviewed final was a little confusing in its questioning.
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