Learning Path

Machine Learning Fundamentals → Hands-on AutoML Project

This learning path equips data scientists with the knowledge to apply Automated Machine Learning (AutoML) frameworks effectively. It covers the core components of AutoML—hyperparameter optimization, neural architecture search, and automated feature engineering—and provides hands-on experience with popular frameworks like Auto-sklearn, H2O, and TPOT. By the end, learners will be able to integrate AutoML into their workflows to accelerate model development while understanding its limitations and best practices.