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SQL for Data Analysis

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If you’re looking to use Structured Query Language in your application development but your story is more prequel than SQL, you need to build a solid foundational knowledge of SQL analysis. In this course, instructor Nikiya Simpson starts with a quick review of SQL basics, then focuses on fundamental SQL queries used in beginning data analysis. Nikiya explains the importance of asking the right questions about your data and how those questions translate into SQL. She also shows how these concepts can be used to derive quick insights from your data to help drive effective decision-making. Nikiya finishes the course by demonstrating how to incorporate queries into tools like Jupyter Notebook to help bring your data to life.

This course is integrated with GitHub Codespaces, an instant cloud developer environment that offers all the functionality of your favorite IDE without the need for any local machine setup. With GitHub Codespaces, you can get hands-on practice from any machine, at any time—all while using a tool that you’ll likely encounter in the workplace. Check out both Codespaces videos to learn how to get started.


01 - Introduction
  • 01 - Using SQL for data analysis
  • 02 - What you should know
  • 03 - Setting up Codespaces
  • 04 - Getting started with a database in Codespaces

  • 02 - 1. SQL Introduction and Asking the Right Questions
  • 01 - A quick review of Structured Query Language (SQL)
  • 02 - What is a relational database
  • 03 - Common SQL structures

  • 03 - 2. Using Data Types
  • 01 - Using data types and identifying the wrong data types
  • 02 - Finding missing values
  • 03 - Finding possible inaccurate data values
  • 04 - Finding duplicate rows

  • 04 - 3. Working with Dates
  • 01 - Working with dates
  • 02 - Filtering data by dates

  • 05 - 4. Easy SQL Functions
  • 01 - Common SQL string functions
  • 02 - Common SQL aggregate functions
  • 03 - Introduction to data manipulation

  • 06 - 5. Presenting Your SQL Results in Data Visualization
  • 01 - Getting started with data visualization
  • 02 - Creating data visualization

  • 07 - Conclusion
  • 01 - Leveling up SQL
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    تاریخ انتشار: 14 شهریور 1402
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