AI-Powered Data Analysis: A Practical Introduction

Overview

Class Central Tips

As generative artificial intelligence (AI) reshapes our world, the ability to analyze data is quickly becoming as fundamental as reading and writing. “AI-Powered Data Analysis: A Practical Introduction” explores how AI tools like ChatGPT are revolutionizing our approach to data, making advanced analysis accessible to everyone. Whether you're a complete novice or looking to enhance your skills, you'll learn how to navigate this new terrain. You'll learn to think critically about the context of data analysis, delve into the specifics of analyzing and visualizing data using AI, and consider broader factors that support but are not directly part of data analysis. This practical approach focuses on generative AI tools, ensuring you know how to ask the right questions to avoid common mistakes. Your final activity will allow you to set yourself up for continued learning with a prepared Python environment and data sets, which you can voluntarily showcase on GitHub—a code-sharing hub. By the end of this course, you'll be adept at using AI tools to analyze data effectively and seamlessly apply these skills to future projects.

Syllabus

Laying the Groundwork: Data Foundations

This module teaches learners to understand and define data, utilize Generative AI for data acquisition, and effectively navigate various data formats and sources. Gain hands-on experience with real-world datasets.

Building Skills: Essential Practice

This module equips learners with fundamental data analysis skills, including selecting appropriate tools, cleaning and organizing data, performing statistical analyses, and creating visualizations, all while leveraging generative AI to enhance their capabilities.

Finishing Touches: Supporting Skills & Next Steps

This module equips learners with essential support skills such as version control, utilizing generative AI for technical assistance, and applying their data analysis knowledge to practical, domain-specific projects.