Refresher
Welcome: Introductions (9.00 - 9.30)
Recap python basics and Bayesian inference (09.30 – 10:30)
Break (10.30-11.00)
Lecture: Statistical learning (11.00-12.00)
Lecture: Intro to Stan (12.00 - 13:00)
Lunch (13.00 - 13.30)
Hands-on: Introduction to statistical learning with Stan in python (13.30 - 15.30)
Recap session (15:30-16:00)
Scalable Gaussian process regression models in Stan
Q&A in break-out rooms (max 10 ppl) (09.00 - 09.30)
Lecture: Intro to Gaussian processes (09.30-10.30)
Break (10.30-11.00)
Lecture/hands-on: Scalable Gaussian process regression models in Stan (11.00-13.00)
Lunch (13.00-13.30)
Hands-on: Scalable Gaussian process regression models (13.30-14.30)
Inspirational Lecture: Two research talks from the Machine Learning and Global Health Network (14.30 - 15.30)
Recap session (15:30-16:00)
Gaussian processes continued
Q&A in break-out rooms (max 10 ppl) (09.00 - 09.30)
Lecture/Hands-on: Scalable Gaussian process regression models (09:30 – 10:30)
Break (10.30-11.00)
Group project analysing real-world datasets e.g. of malaria cases, spatial data on drought, HIV drug resistance (11.00 - 13:00)
Lunch (13:00-13:30)
Group project continued (13.30 - 15.00)
Groups present (15.00-16.00)
Infectious Disease Modelling with Stan
Lecture: Introduction to Infectious Disease Modelling and Compartmental Modelling (09.00-10:20)
Break (10.20-10.50)
Practical: Deriving simple SIR type models with pen and paper (10:50 – 11:30)
Practical: SIR models in Stan (11.30-13:00)
Lunch (13:00-13:30)
Practical: SIR models in Stan (continued) (13.30-15.00)
Inspirational Lecture: Local research talks (two-three) (15.00 - 16.00)
Phylogenetics
Recap session and Q&A in break-out rooms (max 10 ppl) (09.00 - 09.30)
Lecture: Introduction to phylogenetics (09:30-10:30)
Break (10.30-11.00)
Practical: Running a phylogenetic pipeline (11:00-13:00)
Lunch (13:00-13:30)
Guided practical: More phylogenetics (13:30 – 14:30)
Q&A (14:30 - 15:00)
Quiz (15:00 - 15:30)
Introduce take-home assignment (15:30-16:00)
Social: BBQ or similar (18.00 - 20.00)