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ChatGPT For Data Analytics

Published by O'Reilly Media, Inc.

Beginner to intermediate content levelBeginner to intermediate

How to 10x your data analysis productivity with generative AI

This live event utilizes interactive environments
  • Understand the potential of ChatGPT for data analytics and how to use it with the most common data analysis tools such as SQL, Python, Excel, and Google Sheets.
  • Examine the vulnerabilities and risks of using ChatGPT
  • Discover data analytics use cases for ChatGPT that will 10x your productivity today
  • Understand future applications of ChatGPT and its potential impact on data analytics

In this course, you will learn the top use cases and prompt templates that will increase your productivity as a data analyst, data scientist, or BI engineer. You will learn how ChatGPT can help you from structuring your data analysis approach, to using it in Microsoft Excel or Google Sheets, to writing, reading, and improving Python or SQL code. You will learn how to improve the quality and enhance the output of your data analysis using ChatGPT. This hands-on course includes practical examples that any data analyst can immediately relate to and use on the job.

What you’ll learn and how you can apply it

  • Apply example ChatGPT prompts provided for different analytics use cases, and adapt them to the specifics of your own job
  • Integrate ChatGPT into your data analytics workflow to be more productive
  • Leverage ChatGPT’s functionality without breaking any of your company’s security/compliance requirements

This live event is for you because...

  • You're a data analyst, data scientist, or BI professional who wants to be more productive or move into a senior or leadership role.
  • Your day-to-day work consists of analyzing data using spreadsheet software such as Excel or Google Sheets, or a scripting language such as SQL or Python.

Prerequisites

  • A free OpenAI account for ChatGPT access (ideally a ChatGPT Plus subscription for access to the GPT-4 model)
  • A computer set up with Microsoft Excel installed
  • A free Google account to access Google Sheets
  • An IDE of your choice (e.g. Google Colab or Jupyter Notebooks)
  • You have at least a few months of data analytics experience

Recommended follow-up:

Schedule

The time frames are only estimates and may vary according to how the class is progressing.

Day 1

Using ChatGPT for Data Analysis (180 minutes)

Course Introduction (15 minutes)

  • Presentation: Check-in, agenda and learning outcomes
  • Discussion: What’s your experience level with ChatGPT?
  • Q&A

ChatGPT Fundamentals (45 minutes)

  • Presentation: What is ChatGPT and how does it work? Comparing GPT-3.5 vs. GPT-4
  • Business Use Cases: Overview and general capabilities
  • Prompt Engineering Essentials: How to write a good prompt
  • Q&A
  • Break

Use Cases For ChatGPT in Business Analytics (60 minutes)

  • Presentation: Issue trees, RCA frameworks, data storytelling
  • Hands-on exercise: Create effective issue trees with ChatGPT, conduct a root-cause analysis, improve your data story presentation
  • Q&A
  • Break

Use Cases For ChatGPT with Microsoft Excel (60 minutes)

  • Presentation: How to use ChatGPT with Microsoft Excel
  • Hands-on exercises: 4 use cases for using ChatGPT in Excel
  • Q&A

Day 2

Advanced ChatGPT Use Case For Data Analytics (180 minutes)

Introduction and Recap (15 minutes)

  • Presentation: Recap learning from the last day
  • Q&A

Using ChatGPT with Google Sheets (45 minutes)

  • Presentation: How to use ChatGPT directly within Google Sheets
  • Hands-on exercises: 4 use cases for using ChatGPT in Google Sheets
  • Q&A
  • Break

ChatGPT Use Cases for SQL & Python (75 minutes)

  • Presentation: 8 use cases for ChatGPT with SQL & Python
  • Hands-on exercises: Create SQL and Python code for data analysis, optimize queries, explain / document code, create an exploratory data analysis with visualizations, data cleaning & prepration
  • incl. Q&A and break

Limitations and security concerns of ChatGPT (30 minutes)

  • Presentation: Common limitations of ChatGPT and how to overcome them
  • Discussion: How to ensure data security and privacy
  • Q&A

Future Outlook and Closing (15 minutes)

  • Presentation: What's next for ChatGPT? A preview of ChatGPT plugins
  • Discussion: Future use cases and potential impact on data analytics
  • Q&A session
  • Wrap up and feedback

Your Instructor

  • Tobias Zwingmann

    Tobias Zwingmann is an experienced data scientist with a strong business background. He has more than 15 years of professional experience in a corporate setting, where he has been responsible for building out data science use cases and developing a company-wide data strategy. He is also a cofounder of the German AI startup RAPYD.AI and is on a mission to help companies adopt machine learning and artificial intelligence faster while achieving meaningful business impact.

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