Steps to become an AI Developer
Foundations: linear algebra, probability, statistics
Practical ML: data preprocessing and feature engineering
Modeling: from classical ML to deep learning
Tooling: Python, scikit-learn, PyTorch/TensorFlow
Project ideas and deployment basics