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ChatGPT and SQL

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AI is changing the world around us, and completely revolutionizing the way we work. Data professionals now have access to tools that provide superpowers to work smarter and faster than ever before. In this course, the Maven Analytics team guides you through the world of deep learning and generative AI and shows you how to leverage SQL and ChatGPT together to work more efficiently and make smarter, data-driven decisions.

Explore the rapid rise of large language models like ChatGPT and Google Gemini, and get up and running with free tools that will take your skills to the next level. You'll also dive into the art of prompt engineering, review tips and best practices for generating consistent and accurate model outputs, and find out how to address common limitations and pitfalls to be aware of. From there, John Pauler takes you through some of the most powerful and practical ChatGPT use cases for data science and analytics, with instructor-led demos in SQL.

Note: This course was created by John Pauler and Maven Analytics. We are pleased to host this training in our library.


01 - Introduction
  • 01 - The future is now Intro to AI for data analytics
  • 02 - Setting expectations

  • 02 - 1. Why AI for Data Analytics
  • 01 - Why AI is a game-changer for data analysis
  • 02 - AI use cases for data analytics

  • 03 - 2. Intro to AI, LLMs, and ChatGPT
  • 01 - The AI landscape
  • 02 - Generative AI and large language models
  • 03 - The road to ChatGPT
  • 04 - Generative AI tools
  • 05 - Warning Pitfalls of ChatGPT
  • 06 - Accessing ChatGPT and Google Bard

  • 04 - 3. Prompt Engineering
  • 01 - Intro to prompt engineering
  • 02 - Prompt tip Be clear and specific
  • 03 - Prompt tip Provide context
  • 04 - Prompt tip Establish roles
  • 05 - Prompt tip Set the tone

  • 05 - 4. ChatGPT for SQL
  • 01 - Intro to ChatGPT for SQL
  • 02 - Explain fundamental SQL concepts
  • 03 - Explain a SQL query
  • 04 - Add comments to a SQL query
  • 05 - Debug and troubleshoot SQL code
  • 06 - Create a SQL query from scratch
  • 07 - Optimize SQL queries

  • 06 - Conclusion
  • 01 - Key takeaways and next steps
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    تاریخ انتشار: 22 مرداد 1403
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