Kaggle Fundamentals

Learn how to get started with and participate in Kaggle competitions with Kaggles Titanic competition.

Our free Kaggle tutorial on the Kaggle titanic competition using Python. Includes logistic regression, cross validation, random forests and feature engineering.

By the end of this course, you'll be able to:

  • Build a simple machine learning model and make your fist Kaggle submission.
  • Create new features and select the best-performing features to improve your score.
  • Work with multiple algorithms including logistic regression, k nearest neighbors, and random forest.
  • How to select the best algorithm and tune your model for the best performance.

Course Info:

Kaggle Fundamentals


The median completion time for this course is 5.9 hours.

This course requires a premium subscription, and includes three missions and one guided project.  It is the 28th course in the Data Scientist in Python path.


Learn the Fundamentals for Kaggle

Getting Started with Kaggle

Learn how to make your first submission to the Titanic competition.

Feature Preparation, Selection, and Engineering

Improve your Kaggle score by selecting the best features and creating new ones.

Model Selection and Tuning

Lean how to select the optimum model and tune hyperparameters in Kaggle competitions.

Creating a Kaggle Workflow

Learn how to create and use a machine learning worlflow with Kaggle's Titanic competition.