📊 WIN $25! Data Night | Online

🗓 13 August 2026, 7:00 PM (AEST)

📍 Zoom: https://une-au.zoom.us/j/82603385050?pwd=zbAYoR3ybriPTXnnotHcUMNaydyYmr.1

👉 Interested? Grab a ticket to RSVP by 11 August 2026!

Join us for a relaxed Data Night! It's a great opportunity to meet other students interested in data science and statistics, explore a dataset, try out some analysis, and (if you'd like) share what you found with the group.

🎁 Everyone who presents goes into a random draw to win a $25 Coles/Woolworths gift card.

We've had lots of new members join recently from different degrees and at different stages, so this event is designed to be flexible and beginner friendly. Whether you're learning the basics or experimenting with machine learning, we'd love to see what you build.

💡 Suggested datasets

Smaller dataset

House Prices: Advanced Regression Techniques
https://www.kaggle.com/competitions/house-prices-advanced-regression-techniques

Perfect if you're a beginner or looking for a manageable dataset. Whether you want to do EDA, hypothesis testing (e.g. t-tests), regression, or build a predictive model, this dataset has plenty to explore.

Larger datasets

NYC Yellow Taxi Trip Data
https://www.kaggle.com/datasets/elemento/nyc-yellow-taxi-trip-data

IEEE-CIS Fraud Detection
https://www.kaggle.com/competitions/ieee-fraud-detection

Great if you'd like to experiment with PySpark, machine learning, SQL, or other big data workflows.

Note: These datasets are several GB in size. Feel free to work with a subset if needed. On Kaggle, you can use the Data tab to choose which files to download, or use a Kaggle Notebook to access the data without downloading it to your own computer.

If there's a dataset you're already passionate about, feel free to bring that along instead.

🎤 Presentations

If you'd like to present, you'll have 2-3 minutes to share:

• What question you explored

• How you approached it

• What you found

This is intentionally low pressure. Whether you ran a t-test, created a few visualisations, or trained a machine learning model, you're welcome to share.

The goal is simply to practice working with real data, learn from each other, and maybe create something you can later upload to GitHub.

👀 You're also welcome to come along just to watch.

PS: This is also a great opportunity to request access to our free DataCamp Premium membership or show off some of the skills you've been building there. 💻

Want to connect with other data science and statistics students in the meantime? Join our Discord server! 💬