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How Machine Learning Impacts the Undergraduate Computing Curriculum

Ben Shapiro
Rebecca Fiebrink
CACM Viewpoints (2018)
Google Scholar


Machine learning now powers a huge range of applications, from speech recognition systems to search engines, self-driving cars, and prison sentencing systems. Many applications that were once designed and programmed by humans now combine human-written components with behaviors learned from data. This shift presents new challenges to computer science (CS) practitioners and educators. In this article, we consider how the rising importance of machine learning might change what we consider to be core computer science knowledge and skills, and how this should impact the design of both machine learning courses and the broader CS university curriculum.