Materials Science and Discovery Powered by Machine Learning
Offered By: Advanced Cyberinfrastructure Training at RPI via YouTube
Course Description
Overview
Explore the intersection of materials science and machine learning in this 1-hour 20-minute lecture presented by Trevor David Rhone, PhD, professor in the Department of Physics, Applied Physics, and Astronomy at Rensselaer Polytechnic Institute. Discover how advanced computational techniques are revolutionizing materials discovery and accelerating scientific breakthroughs in the field. Gain insights into the application of machine learning algorithms for predicting material properties, optimizing synthesis processes, and identifying novel compounds with desirable characteristics. Learn about the latest developments in data-driven materials research and the potential impact on various industries, from electronics to energy storage. Delve into the challenges and opportunities of integrating artificial intelligence with traditional materials science methodologies, and understand how this interdisciplinary approach is shaping the future of materials engineering and innovation.
Syllabus
Materials Science and Discovery Powered by Machine Learning
Taught by
Advanced Cyberinfrastructure Training at RPI
Related Courses
Big Data Analytics in HealthcareGeorgia Institute of Technology via Udacity Model Building and Validation
AT&T via Udacity Maths for Humans: Linear, Quadratic & Inverse Relations
University of New South Wales via FutureLearn Regression Modeling in Practice
Wesleyan University via Coursera Data Science at Scale - Capstone Project
University of Washington via Coursera