Bayesian Training
Bayesian Training shows statisticians how to build priors, compute posteriors, and interpret vaccine efficacy with credible intervals, robustness checks, and clear visual summaries for confident, data-driven decisions.

4 to 360 hours of flexible workload
valid certificate in your country
What Will I Learn?
Bayesian Training gives you a focused, hands-on guide to analyzing vaccine trial data with confidence. You will define binomial models, build realistic trial scenarios, construct expert-informed priors for vaccine efficacy, and perform Bayesian updating. Learn to summarize posteriors, design robustness checks, avoid common pitfalls, and clearly communicate uncertainty to decision makers in real-world studies.
Elevify Differentials
Develop Skills
- Bayesian VE modeling: build and analyze binomial vaccine efficacy models fast.
- Prior elicitation: turn expert VE beliefs into practical Beta priors that work.
- Posterior analysis: compute VE means, credible intervals, and Pr(VE>50%).
- Robustness checks: run prior sensitivity, skeptical priors, and prior predictive.
- Communication: explain Bayesian VE results clearly to technical stakeholders.
Suggested Summary
Before starting, you can change the chapters and workload. Choose which chapter to start with. Add or remove chapters. Increase or decrease the course workload.What our students say
Your classes are perfect. I purchased the one-year package and finally have the opportunity to follow various topics of my interest without needing to switch platforms... I thank you for everything you do, I've already recommended you to other people...

Giulio CarloDigital Marketing Student
I like how the lessons are straight to the point and how I can switch chapters and skip content I don't need.

Mariana FerresPhotography Student
I like the content and the presentation style and video transcription, which speeds up the process!

Luciana AlvarengaNail Design Student
The platform is fast, simple to use. The diversity of content and complementary videos really help with learning.

André FelipePrompt Engineering Student
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