Machine Learning for Materials Informatics

Overview

What you will learn

By taking the Machine Learning for Materials Informatics course offered by Massachusetts Institute of Technology (MIT) , you will:

• Explore the cutting-edge of modern material informatics tools, including machine learning, data analysis and visualization, and molecular/multiscale modeling

• Learn how to fine-tune general-purpose models for materials applications

• Learn how to work with small, sparse, or low-quality datasets and build predictive models 

• Deepen your knowledge of the frontiers of data-driven material analysis and ready-to-deploy code solutions

• Master computational methods and codes for building better materials, such as language models, protein models, and graph neural networks, and how to build and use your own custom datasets

• Learn how to identify the most effective tool for solving your specific challenge, and gain an overview across the most promising neural network architectures and their most suitable application areas, challenges and potentials; including specific code examples that will be discussed in detail

• Solve inverse design problems using AI

• Enhance the speed, efficiency, and cost effectiveness of your materials design and production processes through next-generation molecular modeling

• Monetize your existing data and develop an actionable vision for incorporating material informatics into your organization’s current strategies