Are LLMs changing how students learn Machine Learning or just changing how they access information?
One interesting shift happening right now is that students entering AI and data fields no longer learn in the same way previous generations did. Instead of spending hours searching documentation or debugging alone, many now learn interactively alongside AI systems.
That creates both opportunity and risk.
On one side, LLMs can dramatically accelerate learning, experimentation, prototyping, and accessibility to complex concepts. They can help students move faster and lower the barrier to entry into AI and machine learning fields.
But at the same time, there is also a growing concern around depth of understanding. If learners become too dependent on generated answers without understanding the reasoning behind them, the industry could eventually face a gap between tool usage and actual foundational expertise.
Curious to hear how others in AI and data see this shift evolving over the next few years.
