Knowledge Modeling, Causal Analysis and Data Mining with Bayesian Networks
- Teaching objectives: Comprehensive understanding of the Bayesian network paradigm plus practical skills for real-world research applications
- Length: 3 days
- Required Level: The course is taught at a beginner level, so no prior knowledge of Bayesian networks is necessary. However, undergraduate-level familiarity with probability theory and statistics is recommended.
- Teaching methods: Tutorials with practical exercises using BayesiaLab plus plenty of one-on-one coaching
- Trainer: Dr. Lionel Jouffe, CEO, Bayesia SAS.
- Training materials: A printed tutorial (approx. 300 slides in two binders), plus a memory stick containing numerous exercises and white papers
- Bayesian network Software: Bayesia provides all trainees with an unrestricted 60-day license of BayesiaLab Professional Edition, so they can participate in all exercises on their own laptops
The registration is complete upon payment of the fee by Bank Transfer, or Credit Cards. Visit the BayesiaLab Store to get the prices corresponding to the type of your organization and number of seats your are interested in.
Day 1: Theoretical Introduction