Explore, visualize, and transform data to enhance analysis, handle issues, and improve modeling.

Learn to build predictive models that drive business impact while addressing data and ethical considerations.

Evaluate classification models using precision, recall, F1 score, and ROC-AUC effectively.

Tune hyperparameters: boost accuracy, prevent overfitting, improve generalization and model performance.

Transform raw data into impactful visuals using pandas, matplotlib, and seaborn for clear communication.

Build foundational Python skills and theory to succeed in bootcamp and practical applications.

Learn decision tree classification, apply splitting criteria, and build models through hands-on practice.

Apply ML concepts through the Kaggle Titanic challenge with real data and modeling.

Master ensemble methods: combine models, reduce bias, boost accuracy, gain practical skills.