Since 2009, we have been teaching Introductory and Advanced BayesiaLab courses all over the world. New York, Paris, London, Dubai, Singapore, and Sydney, just to name a few cities, are part of our regular teaching schedule.
Beginning in 2019, we started offering Livestream options as well, so you can now participate in courses in real-time regardless of where they are hosted.
And, just before the pandemic hit, we added on-demand self-study courses to our training portfolio, enabling you to start a full-featured BayesiaLab curriculum at any time.
In the context of the 2020 BayesiaLab Conference in October 2020, we added VR-based courses, which opens up entirely new opportunities for learning.
Go beyond descriptive analytics and enter the realm of probabilistic and causal reasoning with Bayesian networks. Learn all about designing and machine-learning Bayesian networks with BayesiaLab
This highly acclaimed course gives you a comprehensive introduction that allows you to employ Bayesian networks for applied research across many fields, such as biostatistics, decision science, econometrics, ecology, marketing science, sensory research, sociology, just to name a few.
The hallmark of this 22-hour course is that every segment on theory is immediately followed by a corresponding practice session using BayesiaLab. Thus, you have the opportunity to implement on your computer what the instructor just presented in his lecture. This includes knowledge modeling, probabilistic reasoning, causal inference, machine learning, probabilistic structural equation models, plus many more examples. Given the strictly limited class size, the instructor is always available to coach you one-on-one as you progress through the exercises.
After the end of the course, you can continue your studies as you will have access to your training BayesiaLab license. The BayesiaLab's Media Center will give you access to the slides, as well as a complete recording of the seminar.
To date, over 1,500 researchers from all over the world have taken this course. For most of them, Bayesian networks and BayesiaLab have become crucial tools in their research.
We propose four types of training sessions:
Take your BayesiaLab certification to the next level by joining our 21-hour Advanced BayesiaLab Course. This course gives you a broad view of Bayesian network applications. In the Advanced Course, we explore those topics in greater details that we only touched briefly during the Introductory Course:
Given that you are already familiar with all the basic concepts, we also have a lot more hands-on exercises in the Advanced Course compared to the Introductory Course.
The class is limited to a maximum of 15 participants to allow for one-on-one coaching during the hands-on exercises with BayesiaLab. This small-group format provides a productive yet informal learning environment that facilitates a lively dialog between participants from a wide range of backgrounds.
After the end of the course, you can continue your studies as you will have access to your training BayesiaLab license. The BayesiaLab's Media Center will give you access to the slides, as well as a complete recording of the seminar.
We propose four types of training sessions: