Overview Outcomes Courses Admission Instructors

Program overview

The development of new materials is crucial to advancing technology in fields such as air and space travel, renewable energy and energy storage, transportation, and electrical vehicle production, as well as computing tools. Fortunately, emerging fields such as data science, AI, cloud computing, quantum computing, computational simulation, and automation offer new opportunities to accelerate the materials development process.  This program will provide students with a solid foundation in materials science and engineering fundamentals, while also offering hands-on training in data science techniques for materials development. Students will gain valuable skills in the use of versatile methods and computational tools for solving materials-related challenges.

This certificate program focuses on the application of data science in engineering, in particular to data for materials science and engineering. Data in the field of materials science possesses its own unique characteristics. Leveraging data science and machine learning techniques can significantly accelerate advancements in materials research. However, it is crucial to note that the application of data science in materials science data necessitates specialized techniques. This curriculum is designed to encompass both fundamental aspects of Materials Science and techniques from Data Science.

Learning outcomes

• Understand the fundamentals of materials and be able to describe microstructure-property-processing relationships for various materials types and be able to identify various data types and data structures associated with these relationships.
• Develop the ability to efficiently organize and manage materials datasets for further applying data science methods to them.
• Learn to apply data science methods, including machine learning models to data, to different types of materials data, be able to interpret the outcome of it, and further correlate analytical results with the fundamental underlying causes of observed outcomes.
• Master different computational simulation methods, gain the skills to choose and deploy suitable simulation tools for specific materials research problems based on the objective of the study and physical scale of the problem, and leverage machine learning or other data science methods to optimize the process and enhance results.
• Utilize different computational resources and methods, with an emphasis on cloud computing methods, for the analysis of materials data and be able to automate the workflow for materials science data analysis.
• Cultivate critical thinking skills to recognize and exploit the potential of artificial intelligence in advancing the materials science research for the future.

Courses

Complete the courses listed below to earn the certificate. You may be able to take individual courses without enrolling in the certificate program.

Course details

Admission requirements

Your application must include a resume or curriculum vitae, your statement of purpose and an unofficial transcript. Students must also demonstrate proficiency in basic programming concepts and mastery of at least one programming language.

Admission requirements

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