FIT
Data Science

FIT Competition 2026

Data Science

In the Data Science category, each team will be presented with a challenge that requires them to analyze and develop the best model using machine learning or deep learning to solve a problem based on a given dataset. There will be two types of datasets provided: Image Datasets and Tabular Datasets. Image Datasets can be analyzed using classification, segmentation, or object detection methods, while Tabular Datasets can be analyzed using regression, classification, clustering, or time series forecasting methods. Each team is allowed to use one or more datasets of the same or different types.

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Timeline

1 May – 12 June 2026
Registration & Proposal Submission
Online
01
12 June – 16 June 2026
Preliminary Round
02
17 June – 21 June 2026
Proposal Review
03
23 June 2026
Finalist Announcement
04
23 June – 30 June 2026
Re-registration
05
7 July 2026
Seminar & Technical Meeting
FTI UKSW
06
8 July 2026
Final Round (Coding)
FTI UKSW
07
9 July 2026
Final Round (Presentation) & Winner Announcement
FTI UKSW
08

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Guidebook

The Data Science category focuses on the ability to analyze data and produce meaningful insights. The guidebook includes dataset descriptions, analysis objectives, recommended techniques (such as machine learning or data visualization), and assessment criteria based on model accuracy, result interpretation, and innovation.

Download Guidebook