ChatGPT for Data Analysis in Python from A-Z

Learn How to Analyze and Visualize Data in Python Using ChatGPT: A Complete Guide from A-Z

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ChatGPT for Data Analysis in Python from A-Z

What You Will Learn!

Learn how to use ChatGPT as your AI peer programmer for data analysis in Python
Pre-process and clean the dataset using ChatGPT in Python
Learn interesting techniques to gain more benefits from ChatGPT for data analysis
Run exploratory data analysis using ChatGPT
Run a predictive machine learning model using ChatGPT
Complete two hands-on projects on data analysis and visualization with ChatGPT in python

Description

This course will save you tons of time to effectively use ChatGPT for Data Analysis and Visualization in Python.

No programming experience needed. You will learn everything you need to know.

In this course, students use ChatGPT and Visual Studio Code. During this course, I will show you how to setup both of these tools in the "Installation Setup and Overview Chatgpt and Visual Studio Code" lecture.

Who this course is for:

Anyone interested in learning more about using ChatGPT for data analysis and data visualizations in Python.

Anyone interested about the rapidly expanding world of data analysis and automation!

You’ll get a full understanding of how to use ChatGPT to clean/pre-process datasets, explore your data and run exciting data analyses and visualizations. This course is ready for those looking to efficiently develop interesting insights from datasets that help them make better decisions in their day-to-day work.

By the end of this course, you will:

- Understand how to use ChatGPT for data analysis and visualization in Python.

- Know how to clean and pre-process your dataset using ChatGPT.

- Know how to run exploratory data analysis in python.

- Learn how to use matplotlib and seaborn libraries to create beautiful data visualization with the help of ChatGPT.

- Understand how to run predictive machine learning model with ChatGPT in Python.

Please make sure you read the entire page to understand if the course is the correct version for you.

Happy Learning!