AI-Powered Data Analysis

AI-Powered Data Analysis

By USC Race and Equity Center

Join us for an online workshop that teaches how to apply AI to streamline quantitative data analysis to boost accuracy and efficiency.

Date and time

Location

Online

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Highlights

  • 2 hours 30 minutes
  • Online

Refund Policy

Refunds up to 14 days before event

About this event

Business • Other

AI-Powered Data Analysis

Welcome to our online event where we delve into the exciting world of data analysis powered by artificial intelligence. Join us for a deep dive into how AI is revolutionizing the way we interpret and utilize data. Whether you're a seasoned data analyst or just starting out, this event is perfect for anyone interested in the intersection of AI and data analysis.

During this event, you'll have the opportunity to learn from Jihye Kwon, Associate Director for Survey Research, participate in interactive workshops, and network with professionals passionate about data and AI. Don't miss out on this unique chance to expand your knowledge and skills in the rapidly evolving field of data analysis. Space is limited, secure your spot today!


Workshop Description
This workshop introduces practical methods for integrating artificial intelligence into quantitative data analysis. Participants will learn how to use AI tools to streamline the entire data analysis process—from cleaning and preparing datasets, fixing errors, and receiving syntax assistance, to conducting descriptive and regression analyses. The session will also cover strategies for interpreting results from statistical programs. By the end, attendees will gain confidence in applying AI to enhance accuracy, efficiency, and insight in their quantitative data analysis projects.


Learning contents

AI for the data workflow: choosing the right AI tool and tracking projects

Data cleaning & prep: detecting missing/duplicate values, recoding, type conversion, and tidy data structure

Error fixing: understanding and rewriting code for errors

Syntax assistance: generating code (e.g., R, Stata, SPSS); converting code between languages

Descriptive analysis: summary stats, tables, and quick visuals

Regression analysis: linear/logistic models and assumptions

Result interpretation: Interpreting coefficients, effect sizes, and statistical significance

Responsible use: data privacy and when not to trust AI


Contact Dr. Jihye Kwon for questions about this workshop (kwonjihy@usc.edu)

Organized by

USC Race and Equity Center

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$164.52
Nov 12 · 9:30 AM PST