Machine learning education is rapidly evolving as students increasingly use LLMs for coding, debugging, explanations, model building, and even project development.

While these tools can accelerate learning and experimentation, they also raise questions around foundational understanding, problem-solving ability, and how deeply students engage with core ML concepts.

Is AI enhancing machine learning education, or changing the way future professionals build expertise in the field?