On some opinions and suggestions for statistics education in engineering in the age of AI

In the age of artificial intelligence that we are in, the possibility of obtaining larger volumes of data sets along with the development of data acquisition methods has led to an increase in the need for statistical science. The need for statistics and data science in engineering disciplines that directly contribute to the development of technology has increased in parallel. The article argues that the content and teaching style of statistics courses in engineering curricula need to be updated to meet the current requirements. In this context, this article focuses not on how to teach statistics using generative AI tools, but rather on how to adapt contemporary topics directly linked to probability and statistics concepts and methods-such as digital twins, data-centric engineering, and large language models-into the course curriculum.