Intro to Machine Learning

The course covered foundational machine learning concepts including how models work, basic data exploration with Pandas, and building Decision Tree models. It progressed through model validation, the bias-variance tradeoff of underfitting and overfitting, and the use of Random Forests as a more robust algorithm.

This course established my practical ML foundation, providing hands-on experience building, evaluating, and tuning predictive models using real-world datasets.