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Garbage in, garbage out. It’s the golden rule of data analytics. No matter what you plan to do - analyze, visualize, or build ML models - you need clean, accurate data. Messy, inaccurate data will lead to bad insights and bad business decisions.

So, this hands-on workshop is a practical sprint through the most critical first step of any analytics project: CLEANING YOUR DATA.
We’ll jump straight into real-world datasets (like social media data), define the key metrics that drive results and diagnose issues. We'll also leverage ChatGPT to reduce manual coding, and accelerate the data cleaning process.

In this session, you will:
- Identify and tackle common data quality problems
- Learn to use Python, Pandas, and Matplotlib to explore and clean data
- Define the right metrics to solve specific business problems
- Learn to craft prompts for ChatGPT to get better results

While some basic Python knowledge is a plus, we'll walk through explanations during the session. If you'd like a head start, check out these resources:
Python Basics Overview: https://www.youtube.com/watch?v=Gx5qb1uHss4
More Python Basics (Colab): https://colab.research.google.com/github/jckantor/CBE30338/blob/master/docs/01.02-Python-Basics.ipynb#scrollTo=puHNLUDFpqMZ
Python Conditionals & Libraries (Colab): https://colab.research.google.com/github/jckantor/CBE30338/blob/master/docs/01.03-Python-Conditionals-and-Libraries.ipynb

Let's get started!
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Event Details: https://bullsconnect.usf.edu/rsvp?id=1990076

DATASC, Education, Academic, Campus - Tampa