AIMS-Imperial workshop: Modern Statistics and Machine Learning for Global Health

Course Contents

Thursday  February 22 

Lecture 1: Introductions (9.00-9.30) 

Bayesian Inference 

Lecture 2: Introduction to Stan for applied Bayesian analyses (9.30-10.00) 

Practical 1: Stan basics (10.00-11.30) 

Lecture 3: Scalable Gaussian process regression models (11.45-12.30) 

Practical 2: Scalable GP regression models (12.30-13.00) 

Practical 2: Scalable GP regression models continued (14.00-16.00) 

Friday  February 23 

Infectious Disease Modelling 

Lecture 4: Introduction to Infectious Disease Modelling (09.00-10:00) 

Lecture 5: Introduction to phylogenetics (10:00-10:40) 

Lecture 6: (11.00-13:00) Four remote research talks from the Machine Learning and Global Health Network (Oliver Ratmann, Seth Flaxman, Samir Bhatt, Liza Semenova)

Practical 3: Running a phylogenetic pipeline (14:00-15:00) 

Lecture 6: SIR models (15:00-16:00) 

Saturday  February 24 

Practical 4: Deriving SIR type models (09:00-10:30) 

Lecture 7: Introduction to Fitting an SIR model practical (10:45-11:00) 

Practical 5: Fitting an SIR model in Stan (11.00-13.00) 

Course material All course material is freely available from https://github.com/MLGlobalHealth/aims_rwanda_2024