Course Curriculum
View Agenda
The detailed course agenda is now available. Download the PDF now for a look at topics that will be covered during this program.
This two-day course is aimed at introducing the state-of-the-art in machine learning and teaching the application of machine learning approaches to materials science and engineering via real world examples. By the end of this course, attendees will be able to:
- Create, critically evaluate, and interpret machine learning models for materials
- Describe how machine learning can positively impact their work as scientists
- Organize their data in a way that’s suitable for machine learning
- Design an experiment that incorporates machine learning, including
- Create a sequential learning workflow for their experiment
- Predict the properties of an unknown material with a machine learning model
- Develop experimental material candidates that satisfy target conditions/properties
This interactive course will include detailed lectures with open group discussions. Hands-on learning lab experiences will also enable attendees to design their own experiments that incorporate machine learning. Individual lectures will be centered on the following topical areas:
- Rationale for applying machine learning to materials science
- Machine learning 101—demystifying machine learning
- How does machine learning apply to materials?
- Success stories and opportunities
- Best practices in data management for machine learning
- Hands-on materials learning lab work
- Evaluating machine learning’s applicability to your materials R&D problem
- How to apply machine learning to your R&D efforts
For More Information
For more information about this meeting, please complete the meeting inquiry form or contact:
TMS Meeting Services
5700 Corporate Drive Suite 750
Pittsburgh, PA 15237
Telephone:
U.S. and Canada Only: 1-800-759-4867
Other Countries: 1-724-776-9000
Fax: 1-724-776-3770