Participants will be asked to construct forecasts, based on the models demonstrated in class. The primary item in our tool box is
GeNIe Modeler, a free software for Bayesian networks. Additionally, the use of such tools as Excel or distribution calculators will be recommended and demonstrated. No prior knowledge of calculus is required, neither it is a part of this course.
List of workshops:
● GeNIe's Interface and Functions
● Diving Deeper. Q&A Session
● Final Projects Presentations
Throughout the course, and especially after the second workshop when the participants will enter the active phase of their work on the final project, active communication with Mr. Heinrich and questions are not only welcome, but strongly encouraged.
Recommended Literature:
● Kit YATES, How to Expect the Unexpected. The Science of Making Smart Predictions; Kindle e-Books, 2023
● Nate SIVER, The Signal and the Noise. Why So Many Predictions Fail-And Some Don’t. Kindle e-Books 2015
*Some of the workshops may be conducted by Mr. Heinrich’s colleague – an IT specialist with specific GeNIe 5.0 training.