# Bayesian Class Videos

**URL:** <https://discourse.mc-stan.org/t/bayesian-class-videos/3173>\
**Category:** Publicity\
**Tags:** videos\
**Created:** [February 2, 2018, 7:38am UTC](https://discourse.mc-stan.org/t/bayesian-class-videos/3173 "2018-02-02T07:38:21Z")\
**Posts on this page:** 4\
**Page:** 1

<div class="post-metadata">

**Author:** ![bgoodri](https://yyz2.discourse-cdn.com/flex030/user_avatar/discourse.mc-stan.org/bgoodri/32/4451_2.png) [@bgoodri](https://discourse.mc-stan.org/u/bgoodri)\
**Post date:** [February 2, 2018, 7:38am UTC](https://discourse.mc-stan.org/t/bayesian-class-videos/3173/1 "2018-02-02T07:38:21Z")

</div>

I am teaching a somewhat advanced Master’s level class on Bayesian inference using Stan this semester with a focus on social science applications. There are low-tech videos of the lectures at  
https://www.youtube.com/embed/videoseries?list=PLSZp9QshJ8wyPCgoQR0Kw3HDNuy1FEZH9&wmode=transparent&rel=0&autohide=1&showinfo=1&enablejsapi=1  
where we finally got into a tiny bit of the Stan language and other videos will get added to that playlist over the course of the semester.

Also, @richard_mcelreath just wrapped up his Bayesian class, which has a playlist of high-tech videos at  
https://www.youtube.com/embed/videoseries?list=PLDcUM9US4XdM9_N6XUUFrhghGJ4K25bFc&wmode=transparent&rel=0&autohide=1&showinfo=1&enablejsapi=1

---

<div class="post-metadata">

**Author:** ![ignacio](https://yyz2.discourse-cdn.com/flex030/user_avatar/discourse.mc-stan.org/ignacio/32/1015_2.png) [@ignacio](https://discourse.mc-stan.org/u/ignacio)\
**Post date:** [February 3, 2018, 3:41pm UTC](https://discourse.mc-stan.org/t/bayesian-class-videos/3173/2 "2018-02-03T15:41:17Z")

</div>

Thanks for sharing this @bgoodri !

---

<div class="post-metadata">

**Author:** ![bgoodri](https://yyz2.discourse-cdn.com/flex030/user_avatar/discourse.mc-stan.org/bgoodri/32/4451_2.png) [@bgoodri](https://discourse.mc-stan.org/u/bgoodri)\
**Post date:** [February 4, 2018, 7:33pm UTC](https://discourse.mc-stan.org/t/bayesian-class-videos/3173/3 "2018-02-04T19:33:30Z")

</div>

Due to popular demand, I made everything I could world readable  
[https://courseworks2.columbia.edu/courses/54170/](https://courseworks2.columbia.edu/courses/54170/)

---

<div class="post-metadata">

**Author:** ![bgoodri](https://yyz2.discourse-cdn.com/flex030/user_avatar/discourse.mc-stan.org/bgoodri/32/4451_2.png) [@bgoodri](https://discourse.mc-stan.org/u/bgoodri)\
**Post date:** [March 1, 2019, 3:19pm UTC](https://discourse.mc-stan.org/t/bayesian-class-videos/3173/4 "2019-03-01T15:19:19Z")

</div>

It is that time of year again. And also @breckbaldwin was looking for introductory material for this weekend’s edition of _Stan Last Month_ .

@richard_mcelreath just finished a set of [videos](https://www.youtube.com/playlist?list=PLDcUM9US4XdNM4Edgs7weiyIguLSToZRI) for a graduate [class](https://github.com/rmcelreath/statrethinking_winter2019) that uses the experimental branch of Richard’s [rethinking](https://github.com/rmcelreath/rethinking/tree/Experimental) R package that will be used in the second edition of his textbook. If you have seen these lectures from a previous year, watch them again because they contain a bunch of new topics and more emphasis on what Stan is doing when it samples from a posterior distribution.

I am almost half-way through a semester [class](https://courseworks2.columbia.edu/courses/72393) with [videos](https://www.youtube.com/playlist?list=PLSZp9QshJ8wwWjrsGDbguwcPLUwHWUxo0). We just started doing stuff with the **rstanarm** package and will be moving into **loo** , **projpred** , **brms** , and writing your own models in the Stan language in the coming weeks but have already done many examples that use the `expose_stan_functions` function in the **rstan** package to call a Stan function that draws from the prior predictive distribution or evaluates the log-kernel of a posterior distribution.

@avehtari has started doing [videos](https://aalto.cloud.panopto.eu/Panopto/Pages/Sessions/List.aspx#folderID=%22f0ec3a25-9e23-4935-873b-a9f401646812%22) for a [class](https://github.com/avehtari/BDA_r_demos) that uses the _Bayesian Data Analysis_ textbook so there is more emphasis on writing Stan programs yourself rather than using an R package that comes with or generates Stan programs from R syntax. Apparently, they are upgrading Aki’s recording studio which has resulted in a delay in creating new videos but more are on the way.

@Ben_Lambert wrote a [textbook](https://ben-lambert.com/a-students-guide-to-bayesian-statistics/) using Stan and created a ton of mostly stand-alone [videos](https://www.youtube.com/playlist?list=PLwJRxp3blEvZ8AKMXOy0fc0cqT61GsKCG) but didn’t tell anyone around here. Ben also has a cool Shiny [app](https://ben18785.shinyapps.io/distribution-zoo/) for visualizing and understanding probability distributions that can generate code snippets in the Stan language (and other languages).

So, that should give you plenty to watch and work through until March of 2020.