Core concepts: supervised learning, evaluation, and features.
ML Fundamentals
Start with supervised learning basics, feature engineering, model evaluation metrics, and simple algorithms like linear/logistic regression and decision trees.
Next Steps
Practice with scikit-learn or simple TensorFlow examples
Understand overfitting, cross-validation, and metrics