B-Course is a free Web based Bayesian data mining service. This service allows the users to analyze their own data for multivariate probabilistic dependencies represented as Bayesian network models. In addition to this, B-Course also offers facilities for inferring certain types of causal dependencies from the data. The software is especially suitable for educational purposes as the tutorial style user friendly interface intertwines steps in the data analysis with support material that gives an informal introduction to the Bayesian approach adopted. Nevertheless, although the analysis methods, modeling assumptions and restrictions are totally transparent to the user, this transparency is not achieved at the expense of analysis power: with the restrictions stated in the support material, B-Course is a powerful analysis tool exploiting several theoretically elaborate results developed recently in the fields of Bayesian and causal modeling.

B-Course is a free Web-based online data analysis tool, which allows users to analyze their data for multivariate probabilistic dependencies. These dependencies are represented as Bayesian network models. In addition to this, B-Course also offers facilities for inferring certain type of causal dependencies from the data. The software uses a novel "tutorial style" user-friendly interface which intertwines the steps in the data analysis with support material that gives an informal introduction to the Bayesian approach adopted. Although the analysis methods, modeling assumptions and restrictions are totally transparent to the user, this transparency is not achieved at the expense of analysis power: with the restrictions stated in the support material, B-Course is a powerful analysis tool exploiting several theoretically elaborate results developed recently in the fields of Bayesian and causal modeling. B-Course can be used with most Web-browsers (even Lynx), and the facilities include features such as automatic missing data handling and discretization, a flexible graphical interface for probabilistic inference on the constructed Bayesian network models (for Java enabled browsers), automatic pretty-printed layout for the networks, exportation of the models, and analysis of the importance of the derived dependencies. We discuss both the theoretical design principles underlying the B-Course tool, and the pragmatic methods adopted in the implementation of the software.