Courses and Training

Our training options include:

Decision-theoretic modeling

This is our most popular course, covering the principles of probabilistic modeling using Bayesian networks, building Bayesian networks based on expert knowledge (both structure and numerical parameters), dynamic Bayesian networks, learning Bayesian networks from data and causal discovery, parameter learning, validation techniques, elements of expected utility theory, utility elicitation, and influence diagrams. Even though this is a course focusing on general principles and not a course on how to use BayesFusion’s software (any Bayesian networks software can be used by the participants to practice the material), the lecturer will be using GeNIe and participants should be able to learn how to use it as a side effect of the course.

  • On-line one-on-one course (through teleconferencing software), short sessions at participant’s convenience, 12 hours total
  • On-site (two full days, 14 hours total)

Learning and Causal Discovery with Bayesian Networks

A guide through data analysis using Bayesian networks that focuses on model learning and causal discovery. Participants should be familiar with Bayesian networks and elements of statistics. Even though the course focuses on general principles and not on how to use BayesFusion’s software (any Bayesian networks software can be used by the participants to practice the materials), the lecturer will be using GeNIe and participants should be able to learn how to use its learning modules as a side effect of the course.

  • On-line one-on-one course (through teleconferencing software), short sessions at participant’s convenience, 8 hours total
  • On-site (two full days, 12 hours total)

Qualitative Modeling

A guide through qualitative probabilistic modeling and the functionality of the QGeNIe software. Participants should be familiar with Bayesian networks and basic probability theory.

  • On-line one-on-one course (through teleconferencing software), short sessions at participant’s convenience, 6 hours total
  • On-site (two full days, 12 hours total)

GeNIe Modeler

A guide through the functionality of the GeNIe Modeler software. Participants should be familiar with Bayesian networks, learning, influence diagrams, and elements of the expected utility theory.

  • On-line one-on-one course (through teleconferencing software), short sessions at participant’s convenience, 6 hours total
  • On-site (two full days, 12 hours total)

SMILE Programming (one of C++, Python, Java or .NET)

A guide to building programs and systems that are based on the decision-theoretic principles embedded in SMILE library. Participants should be familiar with Bayesian networks, learning, influence diagrams, elements of the expected utility theory, and GeNIe software.

  • On-line one-on-one course (through teleconferencing software), short sessions at participant’s convenience, 6 hours total
  • On-site (two full days, 12 hours total)

Custom training and tutoring

Custom training and tutoring is meant for advanced users of decision-theoretic approach, who feel that they will benefit most from a shorter interaction with us (through teleconferencing software) focused precisely on their needs.

  • Decision-theoretic modeling
  • Embedding decision-theoretic methods in decision support systems
  • Other topics – please ask

We can design courses focusing precisely on clients’ needs. Pricing will be competitive and will depend on the subject, duration of the course, and the number of participants.

Contact us for course availability and pricing.