The Algorithmic Information Dynamics course promoted and distributed by the Santa Fe Institute is coming to an end. Sponsored by Wolfram Research, the course students made heavy use of the Wolfram Language to follow lectures, read, write and share code from the cloud. This has been an enriching experience for both instructors and students and people may want to share their thoughts about it.
About the Course:
Probability and statistics have long helped scientists make sense of data about the natural world to find meaningful signals in the noise. But classical statistics prove a little threadbare in todays landscape of large datasets, which are driving new insights in disciplines ranging from biology to ecology to economics. It's as true in biology, with the advent of genome sequencing, as it is in astronomy, with telescope surveys charting the entire sky.
The data have changed. Maybe it's time our data analysis tools did, too.
During this three-month online course, starting June 11th, instructors Hector Zenil and Narsis Kiani will introduce students to concepts from the exciting new field of Algorithm Information Dynamics to search for solutions to fundamental questions about causality that is, why a particular set of circumstances lead to a particular outcome.
Algorithmic Information Dynamics (or Algorithmic Dynamics in short) is a new type of discrete calculus based on computer programming to study causation by generating mechanistic models to help find first principles of physical phenomena building up the next generation of machine learning.
The course covers key aspects from graph theory and network science, information theory, dynamical systems and algorithmic complexity. It will venture into ongoing research in fundamental science and its applications to behavioral, evolutionary and molecular biology.
