Duke University tested whether Master-level data science programs, which usually have curricula that emphasize the professional skills and applied data skills missing from most PhD programs, can be leveraged to improve the preparation of PhD students. This project tested the outcomes of combining the applied approach of Master-level data science programs with the depth and experience of PhD STEM students. More specifically, it determined which aspects of Master-level professional curricula translate to PhD students.
The results provide guidance on approaches to extend the impact of a growing investment in data science Master programs to doctoral-level students and will inform the education community on better preparing the next generation of STEM scientists to work with and improve methods surrounding big data. In so doing, this project helps strengthen the pipeline between universities and non-academic employers.
Read the project abstract
Learn more with Duke’s Master in Interdisciplinary Science (MIDS) page