Harnessing the Power of Generative AI with Hellixia
This new three-day course program is designed to help you employ Generative AI in the context of Bayesian networks.
Date and time
Location
FAU Office Depot Center
777 Glades Road Boca Raton, FL 33431Refund Policy
About this event
- Event lasts 2 days 8 hours
This new three-day course program is designed to help you employ Generative AI in the context of Bayesian networks using [Hellixia](/bayesialab/hellixia-user-guide), BayesiaLab's GenAI assistant. Hellixia offers a powerful set of capabilities to streamline the design, analysis, and documentation of knowledge models.
The course focuses on the four core functions of Hellixia, giving you practical skills to integrate them into your modeling workflows. These core functions can use internal knowledge embedded in Large Language Models (LLMs) or combine it with Retrieval-Augmented Generation (RAG), i.e., utilizing specific knowledge files.
About the Instructor
Dr. Lionel Jouffe is co-founder and CEO of France-based Bayesia S.A.S. Lionel holds a Ph.D. in Computer Science from the University of Rennes and has worked in Artificial Intelligence since the early 1990s. While working as a Professor/Researcher at ESIEA, Lionel started exploring the potential of Bayesian networks.
After co-founding Bayesia in 2001, he and his team have been working full-time on the development of BayesiaLab, which has since emerged as the leading software package for knowledge discovery, data mining, and knowledge modeling using Bayesian networks. BayesiaLab enjoys broad acceptance in academic communities, business, and industry.
Frequently asked questions
Statisticians, data scientists, data miners, decision scientists, environmental scientists, epidemiologists, econometricians, economists, market researchers, knowledge managers, marketing scientists, operations researchers, social scientists, students and teachers in related fields.
The course is an instructor-led classroom-based program with a maximum of 15 participants. The small group size allows for one-on-one coaching during the hands-on exercises and facilitates a lively dialog between participants.
You must bring your own notebook or laptop computer running a 64-bit version of Windows or macOS. Before the course, you will receive download and activation instructions for BayesiaLab, so that your setup is ready to go when the course starts. A mouse as a pointing device is highly recommended.
No, this is an in-person course, and you will need to be present in the classroom.
You may cancel your registration for a full refund of the course fees up to 30 days before the start of the course. If you cancel within 30 days of the event, your course fee will not be refunded. However, you will be able to apply 100% of the paid course fees towards future BayesiaLab courses
Basic data manipulation skills, e.g., creating pivot tables with Excel. No prior knowledge of Bayesian networks is required. No programming skills are required. You will use the graphical user interface of BayesiaLab for all exercises.