I disagree. Machine learning education almost always involves a lot of focus on design of experiments, causal inference, A/B testing and related topics.
I could agree with your claim if you meant bootcamp programs or data science sorts of coursework, but machine learning is generally grounded in both measure theoretic probability theory and a robust understanding of applied statistics before moving on. After that will be the basics of pattern classification, clustering, regression and dimensionality reduction. Last of all will be very domain-specific tools for NLP, computer vision, audio processing involving e.g. deep neural networks.
I could agree with your claim if you meant bootcamp programs or data science sorts of coursework, but machine learning is generally grounded in both measure theoretic probability theory and a robust understanding of applied statistics before moving on. After that will be the basics of pattern classification, clustering, regression and dimensionality reduction. Last of all will be very domain-specific tools for NLP, computer vision, audio processing involving e.g. deep neural networks.