Upcoming Open Courses

Bespoke Courses

I am available for training, in particular courses covering introductory and advanced Bayesian modeling with Stan. My courses are highly interactive, with exercises demonstrating a principled Bayesian workflow and range of modeling techniques run in either R or Python environments. Courses run from one to five days and the curriculum can be customized to include material spanning

  • Introduction to probability theory and the foundations of inference
  • Introduction to statistical computation
  • Introduction to the Stan and the Stan Modeling Language
  • Principled workflow for model development
  • Regression modeling
  • Hierarchical modeling
  • Sparsity in Bayesian Models
  • Gaussian processes
  • Time series
  • Ordinary differential equation models
  • Item response theory models

and more.

Previous clients include top research universities, government research organizations, pharmaceutical companies, consumer goods companies, and e-commerce companies.

Please contact me for any inquiries about hosting a course for your institution. I also offer a limited number of discounted and free courses for nonprofit organizations each year.

Testimonials from Previous Clients

We had a fantastic four-day course at Roche during which Mike guided us from the very foundations of statistical inference to multilevel models and gaussian processes. Each topic was accompanied by carefully designed exercises in Stan, which greatly helped in understanding and absorbing the material.

One of the most valuable and most appreciated aspects of the course was Mike’s emphasis on not only the “how” but also the “why” of the topics we covered. It was much more than just learning a new set of tools. In the course of these four days we learned a different, principled way of thinking about data, from how it is generated to how we should model it. The enthusiastic feedback we received from our participants confirms that this approach is something novel and extremely valuable.”

Giovanni d'Ario, Senior Data Scientist, Roche, trivago

“We had a brilliant 3-day course at trivago with Michael Betancourt! The first day was filled with a very strong theoretical foundation for statistical modelling/decision making, followed by a crash course on MCMC and finished off with practical examples on how to diagnose healthy model fitting. In the 2nd and 3rd days we learned about many different types of hierarchical/multi-level models and spent most of the time practicing how to actually create and fit these models in Stan.

Michael is both a very engaging teacher, a very knowledgeable statistical modeller and, of course, a Stan master. This course has opened up new ways for us at trivago to gain better insights from our data through Stan models that fit our needs.”

Data Scientists in the Automated Bidding Team, trivago

“The Stan tutorial workshop was a great experience for both students and faculty alike. Michael provided through and in-depth lectures on the foundations of Bayesian inference. These lectures were then followed by coding exercises that provided real-world exercises of the material. The combination of lectures and exercises provided a thorough approach to the material. The course is highly recommended.”

Joseph Formaggio, Associate Professor of Physics, Massachusetts Institute of Technology

“The 1-day training course provided a great introduction to Bayesian models and their implementation in the Stan language. The practical focus really helped jumpstart our transition to Bayesian methods, and the slides, recorded lecture, and exercises also provide a great resource for new group members.”

Stanley Lazic, Associate Director in Statistics and Machine Learning, AstraZeneca

“The workshop at MIT led by Michael Betancourt was a fun and very useful introduction to Stan. Mike worked with us to customize the lectures to our interests, he presented the material in an engaging and accessible way, and the physicists who attended, many of whom had never used Stan before, left with the resources to begin developing our own analyses. Mike’s background in physics makes him an especially effective teacher for scientists. The coding exercises were thoughtfully developed to progress in complexity and were well-integrated into the course; having such useful exercises was critical for participants to successfully internalize the concepts presented in the lectures.”

Elizabeth Worcester, Associate Physicist, Department of Physics, Brookhaven National Laboratory

“Stan is the cream of the crop platform for doing Bayesian analysis and is particularly appealing because of its open source nature. The programming language and algorithms are well designed and thought out. With that said, Stan has a very steep learning curve requiring lots of hours to get up to speed on your own. I have been to two training courses taught by Dr. Michael Betancourt and took an opportunity to have some consulting time. These sessions have proven invaluable to improve my use of Stan, increased my learning and usage rate, and informed me how to diagnose and detect issues that will inevitable will arise.”

Robert Johnson, Corporate R&D, Procter & Gamble

“We are very grateful for the excellent course which Mike gave at Newcastle University. Mike’s passion for Bayesian inference and the Stan modelling language and software was clear from every aspect of his delivery of the course. He managed to provide a high-level, clearly-reasoned presentation of the basics of Bayesian inference and Bayesian computing, before carefully leading us through the core constructs of the Stan modelling language, and the key ideas when writing Stan models for inference. This included a number of tricks which have been indispensable! I now regularly use Stan to fit models in my own work. I can’t praise Mike highly enough.”

Sarah Heaps, Teaching Fellow in Statistics, Newcastle University