In this course, we will learn about the impact of computation on materials science and the emerging field of Materials Informatics. Computer models of materials are widely used, but there is an increasing trend towards data driven approaches. This data might be derived from high throughput computations as well as experiments.

The course will begin with an introduction to databases, including modern document oriented approaches, and then move onto a description of the fundamentals of computers and programming. We will discuss how material structure might be systematically described, taking an inspiration from crystallography and bio-/cheminformatics. Materials models across the length scales will be introduced, with an emphasis on density functional based methods.

The core computational task of optimisation will be investigated, along with its application to regression, machine learning and material structure prediction. We will discuss whether materials science has entered the era of "big data", and explore data mining as a way to make sense of large amounts of data.

This lecture course will cover:

• Databases
• Computers and computation
• Symmetry
• Systematics of structure
• Models and theories
• Optimisation
• Regression/Machine learning
• Data mining
• High throughput computation
• Structure prediction
• Computational materials discovery/design