Lilly Tech Systems
Learn Kaggle
Master the world's largest data science and machine learning community. Learn to compete in ML competitions, explore datasets, build notebooks, use pre-trained models, and build your data science portfolio — all for free.
What You'll Learn
By the end of this course, you'll be a confident Kaggle user ready to compete and build your data science portfolio.
Competitions
Understand competition types, submission formats, evaluation metrics, and strategies used by top Kagglers to win.
Datasets
Browse, download, and publish datasets. Use the Kaggle API to integrate datasets into your workflow.
Notebooks
Write and publish Kaggle Notebooks with free GPU/TPU access. Earn medals and build your profile.
Models
Explore the Kaggle Models hub, use pre-trained models in your notebooks, and publish your own models.
Course Lessons
Follow the lessons in order or jump to any topic you need.
1. Introduction
What is Kaggle? The world's largest DS/ML community with competitions, datasets, notebooks, and models.
2. Getting Started
Create your account, set up your profile, explore notebooks with free GPU, and use the Kaggle API.
3. Competitions
Competition types, how they work, evaluation metrics, team formation, prizes, and winning strategies.
4. Datasets
Browse, download, create, and publish datasets. Learn about dataset types, licensing, and the Kaggle API.
5. Notebooks
Kaggle Notebooks environment, free GPU/TPU, publishing, earning medals, and integration with competitions.
6. Models
Explore the Kaggle Models hub, use pre-trained models, Hugging Face integration, and publish your own.
7. Best Practices
Competition strategies, EDA tips, feature engineering, ensemble techniques, and building your Kaggle portfolio.
Prerequisites
What you need before starting this course.
- Basic Python knowledge (pandas, numpy helpful but not required)
- A free Kaggle account
- A web browser
- Curiosity about data science and machine learning