Modern engineering education is increasingly assuming an interdisciplinary character, where developments in one area almost invariably affect other areas. A prominent example is that of signal processing, which has undergone significant changes with the emergence of machine learning (ML) and deep learning (DL) in recent years. While the impact of ML/DL is clearly visible from the viewpoint of research and development as well as industrial applications, it is not immediately clear how signal processing education should evolve in terms of pedagogy and content. Hence, the main purpose of this article is to provide some insight into this aspect. In particular, we emphasize that the introduction and popularity of ML/DL, especially at the level of teaching, has provided an opportunity to bring the focus back to some of the fundamental ideas rooted in signal processing and other related fields of study. © 1991-2012 IEEE.