If you’re a data scientist or you work with machine learning (ML) models, you have tools to label data, technology environments to train models, and a fundamental understanding of MLops and modelops.

If you really think about it, a data life cycle is quite difficult to pin down and depending on your industry or profession, the number of agreed steps vary widely. For example, the Harvard Business ...

Suggested Citation: "1 Introduction." National Academies of Sciences, Engineering, and Medicine. 2020. Roundtable on Data Science Postsecondary Education: A ...