Earning the Certificate
The minimum standards for the Data Science for Materials Engineering certificate include a cumulative GPA of 3.0 for required courses and a grade of 2.7 or higher for each of the graded courses in this certificate. Students must complete a minimum of 15 credits for this certificate.
Course details and descriptions
MSE 542: DATA SCIENCE AND MATERIALS INFORMATICS (3 CREDITS)
Introduction to data science approaches and their applications to materials science research. Basic skills in data mining, data processing, and machine learning for materials research topics using Python taught through case studies and other methodologies.
MSE 543: MATERIALS AND DEVICE MODELING (3 CREDITS)
Implementation of computational and data science methods in materials science discovery and device modeling to gain physical and statistical insights of materials design. First-principles methods, multiscale simulations, and continuum modeling will be introduced within the framework of active machine learning with application of both computational and data science methods to materials study.
MSE 544: BIG DATA FOR MATERIALS SCIENCE (3 CREDITS)
Introduces the challenges and opportunities of the big data era for materials science and chemistry research. Students will gain basic knowledge and skills of data management using high performance computing, including automated data processing, batch processing, and cloud based computational tools that are suitable for materials science research.
MSE 570: GRADUATE TUTORIAL IN MATERIALS SCIENCE AND ENGINEERING I (2 CREDITS)
Physical and chemical structures of materials and their relationship to properties. Understanding and applying the following material science concepts: atomic bonding, crystallography, defects and diffusion, thermodynamics, phase diagrams, and phase transformations.
MSE 571: GRADUATE TUTORIAL IN MATERIALS SCIENCE AND ENGINEERING II (2 CREDITS)
Mechanical, electrical, dielectric, optical, and thermal properties of materials; applying these concepts.
MSE 520: SEMINAR (1 CREDIT, Culminating Experience)
The seminar provides a comprehensive exploration of the latest research in materials science and engineering. It is carefully designed as an interdisciplinary nexus, bringing to the forefront a variety of groundbreaking topics including aerospace materials, biomaterials, quantum materials, and sustainable energy solutions. The assignments for the seminar are designed to bring interactive engagements that require students to deploy critical thinking and analytical skills to propose how data science can be applied to that specific topic, which demonstrates an advanced understanding of material research and data science.
ENGR 591: UW DATA SCIENCE SEMINAR (1 CREDIT, Culminating Experience)
The seminar covers a wide range of current topics and applications of data science and artificial intelligence, including ethics. Students are required to reflect on data science methods described in the seminar and propose how these methods can be applied to certain material research or material data. The seminar reinforces the UW definition of data science as the combination of statistics, machine learning, artificial intelligence, data management, visualization and software engineering.