diff --git a/README.md b/README.md
index 1f86d6207..d21b2dcde 100644
--- a/README.md
+++ b/README.md
@@ -90,6 +90,20 @@ cost of the granularity of estimates or real-time performance, include:
 - Adjustment for the remaining susceptible population beyond the
   forecast horizon.
 
+By default, all these models are fit with [MCMC
+sampling](https://mc-stan.org/docs/reference-manual/mcmc.html) using the
+[`rstan`](https://mc-stan.org/users/interfaces/rstan) R package as the
+backend. Users can, however, switch to use approximate algorithms like
+[variational
+inference](https://en.wikipedia.org/wiki/Variational_Bayesian_methods),
+the
+[pathfinder](https://mc-stan.org/docs/reference-manual/pathfinder.html)
+algorithm, or [Laplace
+approximation](https://mc-stan.org/docs/reference-manual/laplace.html)
+especially for quick prototyping. The latter two methods are provided
+through the [`cmdstanr`](https://mc-stan.org/cmdstanr/) R package, so
+users will have to install that separately.
+
 The documentation for `estimate_infections` provides examples of the
 implementation of the different options available.
 
@@ -175,6 +189,12 @@ the two main functions in the package and how to set up them up. It also
 discusses how to summarise and visualise the results after running the
 models.
 
+More broadly, users can also learn the details of estimating delay
+distributions, nowcasting, and forecasting in a structured way through
+the free and open short-course, [“Nowcasting and forecasting infectious
+disease dynamics”](https://nfidd.github.io/nfidd/), developed by some
+authors of this package.
+
 </details>
 <details>
 <summary>