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SQL for Data Science

Approx. 14 hours to complete

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Course Summary

Learn SQL for Data Science from scratch and build your career as a data analyst or data scientist. This course teaches you how to use SQL to access and analyze data to make better business decisions.

Key Learning Points

Learn SQL from scratch with real-world examples
Understand how to use SQL to access and analyze data for business decisions
Gain practical skills to build your career as a data analyst or data scientist

Job Positions & Salaries of people who have taken this course might have

- USA: $63,000 - $106,000
- India: ₹391,000 - ₹1,247,000
- Spain: €19,000 - €35,000
- USA: $63,000 - $106,000
- India: ₹391,000 - ₹1,247,000
- Spain: €19,000 - €35,000
- USA: $95,000 - $165,000
- India: ₹611,000 - ₹2,000,000
- Spain: €30,000 - €55,000
- USA: $63,000 - $106,000
- India: ₹391,000 - ₹1,247,000
- Spain: €19,000 - €35,000
- USA: $95,000 - $165,000
- India: ₹611,000 - ₹2,000,000
- Spain: €30,000 - €55,000
- USA: $58,000 - $106,000
- India: ₹352,000 - ₹1,109,000
- Spain: €19,000 - €35,000

Learning Outcomes

Use SQL to access and analyze data for business decisions
Build a strong foundation in relational databases
Develop practical skills to advance your career in data analysis or data science

Prerequisites or good to have knowledge before taking this course

No prior knowledge of SQL required
Access to a computer with internet connection

Course Difficulty Level

Beginner

Course Format

Online self-paced course
Video lectures
Real-world examples and exercises

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Description

As data collection has increased exponentially, so has the need for people skilled at using and interacting with data; to be able to think critically, and provide insights to make better decisions and optimize their businesses. This is a data scientist, “part mathematician, part computer scientist, and part trend spotter” (SAS Institute, Inc.). According to Glassdoor, being a data scientist is the best job in America; with a median base salary of $110,000 and thousands of job openings at a time. The skills necessary to be a good data scientist include being able to retrieve and work with data, and to do that you need to be well versed in SQL, the standard language for communicating with database systems.

This course is designed to give you a primer in the fundamentals of SQL and working with data so that you can begin analyzing it for data science purposes. You will begin to ask the right questions and come up with good answers to deliver valuable insights for your organization. This course starts with the basics and assumes you do not have any knowledge or skills in SQL. It will build on that foundation and gradually have you write both simple and complex queries to help you select data from tables. You'll start to work with different types of data like strings and numbers and discuss methods to filter and pare down your results. You will create new tables and be able to move data into them. You will learn common operators and how to combine the data. You will use case statements and concepts like data governance and profiling. You will discuss topics on data, and practice using real-world programming assignments. You will interpret the structure, meaning, and relationships in source data and use SQL as a professional to shape your data for targeted analysis purposes. Although we do not have any specific prerequisites or software requirements to take this course, a simple text editor is recommended for the final project. So what are you waiting for? This is your first step in landing a job in the best occupation in the US and soon the world!

Knowledge

Identify a subset of data needed from a column or set of columns and write a SQL query to limit to those results.
Use SQL commands to filter, sort, and summarize data.
Create an analysis table from multiple queries using the UNION operator.
Manipulate strings, dates, & numeric data using functions to integrate data from different sources into fields with the correct format for analysis.

Outline

Getting Started and Selecting & Retrieving Data with SQL
Course Introduction
Module Introduction
What is SQL Anyway?
Data Models, Part 1: Thinking About Your Data
Data Models, Part 2: The Evolution of Data Models
Data Models, Part 3: Relational vs. Transactional Models
Retrieving Data with a SELECT Statement
Creating Tables
Creating Temporary Tables
Adding Comments to SQL
Summary
SQL Overview
Data Modeling and ER Diagrams
Let's Practice!
Practice Simple Select Queries
Module 1 Quiz
Module 1 Coding Questions

Filtering, Sorting, and Calculating Data with SQL
Module Introduction
Basics of Filtering with SQL
Advanced Filtering: IN, OR, and NOT
Using Wildcards in SQL
Sorting with ORDER BY
Math Operations
Aggregate Functions
Grouping Data with SQL
Putting it All Together
SQL for Various Data Science Languages
Module 2 Practice Quiz
Module 2 Quiz
Module 2 Coding Assignment

Subqueries and Joins in SQL
Module Introduction
Using Subqueries
Subquery Best Practices and Considerations
Joining Tables: An Introduction
Cartesian (Cross) Joins
Inner Joins
Aliases and Self Joins
Advanced Joins: Left, Right, and Full Outer Joins
Unions
Summary
SQL and Python
Union and Union All
Practice Quiz - Writing Queries
Module 3 Quiz
Module 3 Coding Assignment

Modifying and Analyzing Data with SQL
Module Introduction
Working with Text Strings
Working with Date and Time Strings
Date and Time Strings Examples
Case Statements
Views
Data Governance and Profiling
Using SQL for Data Science, Part 1
Using SQL for Data Science, Part 2
Course Summary
Additional SQL Resources to Explore
Welcome to Peer Review Assignments!
Yelp Dataset SQL Lookup
Module 4 Quiz
Module 4 Coding Questions

Summary of User Reviews

This SQL for Data Science course on Coursera has received positive reviews from users. Many users found the course to be comprehensive and well-structured, allowing them to gain a strong understanding of SQL and its applications in data science.

Key Aspect Users Liked About This Course

The course is comprehensive and well-structured.

Pros from User Reviews

Covers a wide range of SQL topics and concepts.
Hands-on exercises and quizzes help reinforce learning.
Instructors are knowledgeable and provide clear explanations.
Course content is relevant and applicable to real-world data science scenarios.

Cons from User Reviews

Some users found the course to be too basic and not challenging enough.
A few users reported technical issues with the platform or course materials.
Some users found the pace of the course to be too slow or too fast.
A few users reported that the course could benefit from more practical examples.

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