Schedule

This course will span over 3 consecutive days from 8am to 3pm.

  • Lectures : this page contains the recorded lecture videos, the lecture notes and the slides for this class.
  • Practicals : this page contains the practicals code exercise corresponding to the topics covered each of the 3 days.
  • Prerequisites : this page contains the prerequisites, including some coding exercises, to be completed on your own time before the start of the class.

Date Time Activity Topic
Before October 29th On your own time (2h to 4h) 👨‍💻 📝 ✅ Pre-requisites Refresher on
• Maximum Likelihood Estimations


October 29th (Boris Hejblum) 8am-10am 📽️ 👨‍🏫 🗣️ Interactive lecture • Part I: Intro to Bayesian stat concepts
• Exercise 1: “Prior elicitation”
10am-10:15am ☕ ⏸️ Coffee break
10:15am-12pm 📽️ 👨‍🏫 🗣️ Interactive lecture • End of Part I
• Part II: Bayesian computations (intro)
12pm-1pm 🥪 ⏸️ Lunch break
1pm-3pm 💻 👥 🧠 Practicals in break-out groups • Exercise 2: “Monte Carlo”
• Exercise 3: “Inverse transform sampling”


October 30th (Boris Hejblum) 8am-10am 📽️ 👨‍🏫 🗣️ Interactive lecture • Finish Part II: Bayesian computations
10am-10:15am ☕ ⏸️ Coffee break
10:15am-12pm 💻 👥 🧠 Practicals in break-out groups • Exercise 4: “Metropolis-Hastings”
12pm-1pm 🥪 ⏸️ Lunch break
1pm-3pm 📰 🧠 👥 Read and discuss in break-out groups • Exercise 5: “BUGS & JAGS
• Part III intro: Goligher et al.


October 31st (Boris Hejblum) 8am-10am 💻 👥 🧠 Practicals in break-out groups Part III: Bayesian applications in biomedical science
• Exercise 6: “Post-mortem Bayes”
10am-10:15am ☕ ⏸️ Coffee break
10:15am-12pm 💻 👥 🧠 Practicals in break-out groups • Exercise 7: “Bayesian meta-analysis”
12pm-1pm 🥪 ⏸️ Lunch break
1pm-3pm 💻 👥 🧠 Practicals in break-out groups • Exercise 8: “Bayesian regression”