Course description

Artificial Intelligence (AI) in materials science is revolutionizing the way materials are designed, synthesized, and characterized. AI algorithms enable the prediction of material properties and behaviors, speeding up the discovery of novel materials. Machine learning models assist in optimizing manufacturing processes and analyzing experimental data. AI applications extend to predicting material failure, improving performance, and enhancing sustainability in material design.

What will i learn?

• Understand the basic concepts of machine learning and its applications in materials science.
• Develop skills to use Python libraries for machine learning, such as scikit-learn, Pymatgen, and graphviz.
• Gain hands-on experience in applying machine learning techniques to solve materials science problems.
• Learn how to evaluate the performance of machine learning models and interpret their results.
• Develop a critical understanding of the limitations and challenges of machine learning in materials science.