AI Materials: Advancing Performance Through Machine Learning
Explore how AI and machine learning accelerate material design and development. Learn about AI's impact on materials science and engineering.
Explore how AI and machine learning accelerate material design and development. Learn about AI's impact on materials science and engineering.
Dive into the fascinating world of AI Materials in this comprehensive course. Discover how artificial intelligence and machine learning are revolutionizing materials science and engineering. From the birth of AI to its applications in material processing, fabrication, and imaging, this course covers a wide range of topics. Learn how AI recognizes texts, images, and objects, and explore the concept of AI emotions in the multi-self metaverse era. Gain insights into AI-driven materials processing, fabrication techniques like molecular printing and 3D printing, and advanced imaging methods for material analysis. This course is designed for beginners and provides a solid foundation in understanding how AI is accelerating the design and development of novel materials.
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What you'll learn
Understand the historical development and basic principles of AI
Learn how AI recognizes and processes texts, images, and objects
Explore the concept of AI emotions and its implications in the metaverse era
Gain knowledge about AI applications in materials processing and fabrication
Understand AI-driven techniques in molecular printing and 3D printing
Learn about AI's role in materials imaging and structure analysis
Skills you'll gain
This course includes:
3.5 Hours PreRecorded video
17 assignments
Access on Mobile, Tablet, Desktop
FullTime access
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There are 7 modules in this course
This comprehensive course explores the intersection of Artificial Intelligence (AI) and Materials Science. It begins with an introduction to AI's history and development, progressing to its current applications in recognizing texts, images, and objects. The course delves into advanced topics such as AI emotions and the multi-self metaverse era. A significant portion focuses on AI's role in materials processing, fabrication, and imaging. Students will learn about AI-driven molecular printing, particle amplification, and 3D printing techniques. The course also covers AI's application in materials imaging, including structure and property analysis, and its role in materials design through machine learning. Throughout the modules, students gain insights into how AI and machine learning are accelerating the development of novel materials and revolutionizing materials science and engineering.
Birth of AI
Module 1 · 1 Hours to complete
AI recognizes
Module 2 · 6 Hours to complete
AI Emotion
Module 3 · 6 Hours to complete
AI learns Materials Processing
Module 4 · 9 Hours to complete
AI Materials Fab
Module 5 · 9 Hours to complete
AI Materials Imaging 1
Module 6 · 6 Hours to complete
AI Materials Imaging 2
Module 7 · 9 Hours to complete
Fee Structure
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Instructor
Pioneer in Nanoscale Materials Characterization and Engineering
Prof. Seungbum Hong graduated summa cum laude from KAIST with a B.S. in 1994 and earned his Ph.D. in nanoscale observation of ferroelectric thin films in 2000. After postdoctoral research at EPFL in Switzerland, he led the probe storage project at Samsung Advanced Institute of Technology. From 2007 to 2017, he served as a principal investigator at Argonne National Laboratory, focusing on local domain and transport studies of oxide heterostructures and polymer ferroelectrics. Prof. Hong returned to KAIST in 2017, became a full professor in 2021, and currently serves as the head of the Department of Materials Science and Engineering. With extensive experience linking fundamental science to industrial applications, he has authored 160 peer-reviewed journal papers, edited five books, and holds 79 patents. Recognized for his contributions, Prof. Hong has received numerous awards, including the Young Investigator Outstanding Achievement Award, and is actively involved in international collaborations and conference leadership roles.
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4.8 course rating
29 ratings
Frequently asked questions
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