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Introduction
- Overview
- Expectations and assessments
- Exercise: Getting started
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Machine Learning Basics
- Terminology
- Learning by example
- Supervised
- Unsupervised
- Reinforcement
- Exercise: Crystal hardness
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Materials Data
- Data sources and formats
- API queries
- Exercise: Data-driven thermoelectrics
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Crystal Representations
- Compositional
- Structural
- Graphs
- Exercise: Crystal space
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Classical Learning
- k-nearest neighbours
- k-means clustering
- Decision trees and beyond
- Exercise: Metal or insulator?
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Artificial Neural Networks
- From neuron to perceptron
- Network architecture and training
- Convolutional neural networks
- Exercise: Learning microstructure
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Building a Model from Scratch
- Data preparation
- Model choice
- Training and testing
- Exercise: Crystal hardness II
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Accelerated Discovery
- Automated experiments
- Bayesian optimisation
- Reinforcement learning
- Exercise: Closed-loop optimisation
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Generative Artificial Intelligence
- Large language models
- From latent space to diffusion
- Exercise: Research challenge
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Recent Advances
- Guest lecture
- Exercise: Research challenge