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IBM

Databases and SQL for Data Science with Python

IBM via Coursera

Overview

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Whether you want to become a Data Scientist, Data Analyst, or Data Engineer, knowing how to work with SQL (Structured Query Language) is an essential skill. SQL is a powerful language used for communicating with and extracting data from databases. In this hands-on course, you’ll learn how to retrieve, organize, and manage data using SQL, starting with the fundamentals and moving to more advanced techniques. You’ll also explore how to combine SQL with Python to work with databases and analyze data. By the end of this course, you’ll be able to: - Write SQL queries using SELECT, INSERT, UPDATE, and DELETE to retrieve and manage data. - Filter and organize data using WHERE, COUNT, DISTINCT, LIMIT, ORDER BY, GROUP BY, and built-in database functions. - Create and manage database tables using CREATE, ALTER, and DROP, and understand the differences between DDL and DML. - Query complex datasets using subqueries, string patterns, ranges, and INNER and OUTER JOINs to work with data across multiple tables. - Connect SQL with Python using Jupyter notebooks to access databases and integrate SQL into your data science workflow. - Explore advanced database concepts such as Stored Procedures, Views, and ACID transactions. Throughout the course, you will complete hands-on labs, work with real databases on the Cloud, and gain experience with real data science tools. In the final project, you’ll analyze multiple real-world datasets to demonstrate your ability to query and work with data. Ready to build your SQL skills? Join over 670,000 learners who have enrolled in this course. Earn a shareable certificate to showcase your data science skills on LinkedIn, your resume, or your CV.

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 Engineers
    • 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

Reviews

2.0 rating, based on 1 Class Central review

4.7 rating at Coursera based on 22757 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.

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