Kaggle

Kaggle is an online platform for data science and machine learning that hosts competitions, public datasets, notebooks, and community discussion. Users can explore shared datasets, develop models in hosted notebook environments, participate in challenges, and learn from public code and discussions. Kaggle also offers short, hands-on courses (“Kaggle Learn”) that teach practical skills in Python, ML, data visualization, and more.​

Kaggle can be used as a supplemental environment for teaching data science and ML, providing ready-made datasets, examples, and practice problems. Instructors can use competitions and kernels as assignment templates or inspiration, while students can use Kaggle to build portfolios. Research computing groups can reference Kaggle notebooks and approaches when helping users understand ML workflows, then guide them in porting successful prototypes to campus or national CI resources for larger-scale experiments.

Kaggle Competitions are online machine learning challenges where individuals and teams build models to solve a defined prediction or analysis problem using a provided dataset, then submit their results to be scored on a leaderboard. Each competition specifies a task, an evaluation metric, rules, and deadlines, and participants iteratively improve their models based on public leaderboard feedback.
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Competitions are offered in several categories, including beginner-friendly “Getting Started” and “Playground” problems, commercially focused “Featured” challenges with larger prizes, and “Research” or “InClass” competitions used by organizations and instructors to explore new ideas or support courses. For learners and practitioners, they provide a structured way to practice end-to-end workflows—data exploration, feature engineering, model training, validation, and documentation, while learning from shared notebooks, discussions, and post-competition solution write-ups.

View current competitions here.