Overview
Who this competition fits
Beginners who want a low-friction first competition on a learning platform with DataLab notebooks.
Read the original official blurb
Tuberculosis (TB) is a leading infectious disease affecting the lungs. Clinicians often use chest X-rays to support diagnosis, but reviewing many images manually is time-consuming and challenging. In this competition, you’ll build a simple classifier to distinguish between healthy lungs and lungs affected by TB, focusing on your process, decisions, and learnings rather than perfection. Train a model that classifies chest X-rays into Healthy vs TB cases. Scoring notes: This competition will not be judged. Use this opportunity to apply your conceptual and machine learning skills, and compare your work with your peers after the competition ends! Once the competition concludes, you'll have the opportunity to view and vote for the best submissions.
Preparation
From registration to a first submission
- 01
Python or R basics
- 02
DataCamp / DataLab workflow
- 03
basic image handling
Before you commit: Even learning competitions can stall if you have never turned analysis into a clean submission notebook.
Source
How this page was assembled
Competition information is structured from the official page. Scores are platform estimates for decision support; official rules take precedence.
- Official competition page
- DataCamp
- Last checked
- Sep 1, 2025