Location: Virtual
Time: 8:30 am to 4:30 pm
Course Description:
The course focus is on constructing and analyzing Bayesian networks (BNs) in Netica – from simple models for learning the basics to more complex, real-world applications for learning advanced features. Through a hands-on learning process, students will have the opportunity to explore examples and work on networks from their own work places during class exercises.
The cost is $1900 which includes snacks each day. A discount of $200 for early registration three weeks prior to course is available. We also offer a $200 discount for multiple persons from the same organization. Only one discount can be used.
A temporary student license for the Netica software will be provided. Students do not need to purchase Netica for the course. PLEASE bring your own laptop. The course is very hands-on.
Instructors:
Further Information:
Please keep an eye on this webpage for further information and updates. We can also teach this course at your site at another time. Email Dennis at dmbuede@innovativedecisions.com with questions or suggestions.
Course Topics (order is subject to change):
Day 1
- Introduction
- Building a simple Bayesian network (BN) – drug testing
- Just enough probability
- A complete diagnostic BN – Liver diagnosis case study
- Elicitation of BN structure and probabilities
- Student Project Definition
- BN Process Models
Day 2
- Troubleshooting systems – Industrial system example
- D-Separation and sensitivity to findings
- Student Workshop (opportunity to work on your own BN problem)
- Learning probabilities for a BN from data
- Combining expert knowledge and data
- Learning structure for a BN from data
- Learning a BN with continuous variables
Day 3
- Netica API and programming
- Student Workshop
- Introduction to GeoNeticaTM
- Student Workshop
Advanced topics available on a case-by-case basis
- Decision making in Netica using influence diagrams
- Using the Netica library in the ExtendSim discrete event simulation
- Explore BN structure building using R