Yaroslava Yingling1 Elizabeth Dickey1 Ashleigh Wright1

1, North Carolina State University, Raleigh, North Carolina, United States

International Data Corporation predicted that 60% of organization in 2021 will use machine learning approaches for more extensive data analysis and insights. However, traditional materials engineering education on the undergraduate and graduate levels falls short to address this need. In this talk, I will discuss how NCState response to this shortcoming. For graduate education, we introduced the a graduate certificate which isdesigned for interdisciplinary graduateeducation at the intersection of materialsscience, engineering, and data science withthe aim of preparing the next generation of materials engineers given the growingdemand for data-science skills andknowledge of the artificial intelligence. The skills and knowledge obtained here will serveas foundation for the understanding of materials informatics and high throughputmaterials discovery that will improve a graduate student’s career prospects. To address the immediate knowledge gaps in graduate and undergraduate education, we introduced a general hands-on introductory class on Materials Informatics with the aim to introduce the emergent field of materials informatics and current approaches that employ informatics and experimental and computational data to accelerate the process of materials optimization, discovery and development. The goal of our efforts was to prepare students to move into career positions that require a basic comprehension of data science techniques as applied to materials science and engineering problems.