Contents

1. Introduction

   • Overview
   • What is DFT
   • Install QE
   • Exercise: Getting started

2. Productivity tools

   • Ubuntu command
   • JupyterLab
   • Exercise: Crystal hardness

3. Hands-on tutorials of QE I: Basics parameters

   • Terminology
   • Learning by example
     • Supervised
     • Unsupervised
     • Reinforcement
   • Exercise: Crystal hardness

4. Hands-on tutorials of QE II: Electronic properties

   • Data sources and formats
   • API queries
   • Exercise: Data-driven thermoelectrics

5. Hands-on tutorials of QE III: Phonon properties

   • Compositional
   • Structural
   • Graphs
   • Exercise: Navigating crystal space

6. Hands-on tutorials of QE IV: Optical properties

   • k-nearest neighbours
   • k-means clustering
   • Decision trees and beyond
   • Exercise: Metal or insulator?

7. Hands-on tutorials of QE V: Subjects for 2D materials

   • From neuron to perceptron
   • Network architecture and training
   • Convolutional neural networks
   • Exercise: Learning microstructure

8. Hands-on tutorials of QE VI: Wannier90

   • Data preparation
   • Model choice
   • Training and testing
   • Exercise: Crystal hardness II

9. Special topic I: QERaman - Raman spectra calculation

   • Automated experiments
   • Bayesian optimisation
   • Reinforcement learning
   • Exercise: Closed-loop optimisation

10. Special topic II: Applications of DFT in materials research

    • Large language models
    • From latent space to diffusion
    • Exercise: Research challenge