I have been taking courses on complexity explorer, this course is a useful introduction. I really enjoyed the course. Lots of connected ideas of the interdependent fields. I got my first introduction to Wolfram programming language during this course. As a prospective complex system science researcher, I found the introduction to Wolfram one quite useful, I would like to thank the complexity explorer team for arranging 6 months license.

Nice course! I found it very inspiring and very connected with my research too. I hope to use AID in many of the topics of cancer and ecological dynamics of cell systems in which I am currently working.

I really enjoyed the course, it explained a lot of ideas and braided them together to create elegant explanations of the interdependency of algorithmic complexity and probability, amongst other core concepts. it was well structured and covered a lot of ground but still, manage to keep up with current areas of interest and share new research while also be pragmatic by showing how we could use the wolfram language to test what we were taught in the lectures. I would recommend this course to anyone who has an interest in complexity theory or general desire to learn fundamental approaches to understand causality in different systems - it was great!

Fascinating course, which delves into a range of interesting topics like Entropy, Information, Networks, Turing Machines, Randomness a.o. and weaves a coherent picture of the subject of Algorithmic Information Dynamics that enables us to reason causally about dynamic systems. The authors do a good job in bringing this together. I am sure this will improve further over time e.g. more complete slide deck, finished book, more practical examples, more code with real data. A big thank you to the team to making that theory & topic accessible!!

Hector and Narsis did an amazing job at communicating their research and explaining the core of Algorithmic Information Dynamics. The topics disussed during the MOOC will have profound implications in the study of complex systems. Specially in medicine and artificial intelligence, where new techniques are required beyond purely statistical methods in order to reprogram and understand behavior of adaptive systems. Moreover, the use of Wolfram Language enhanced learning by providing a transparent way of modelling real world phenomena and testing new ideas. Overall, I enjoyed the course and it motivated me to apply AID in my masters' thesis: birdsong analysis. I strongly recommend teachers to keep improving / sharing / creating new study materials and keep contact with students. I am sure eventually every field will find an interesting use for AID. Maybe in some years there will be enough projects for an International Conference.

I'm taking a couple of courses from Complexity Explorer of the Santa Fe Institute and they are a great way to have access to technics and knowledge at the forefront of science. Thus there are two types of courses , first it would be the courses already established with a lot of previous experiences that have let them correct common and particular mistakes that come with teaching such a new subject. The second type is what I experienced in the Algorithmic Information Dynamics: From Networks to Cells course, where they made a lot of effort to give us access to an ongoing project and a book that is on the writing at this very moment. This is something that I very much appreciate because this kind of access is usually only available in a direct personal way and on site , which means people like myself that are doing research in developing countries will see in 10 to 15 years, with no participation in the development with all the drawbacks that come with it. So if you are interested in a really new way to approach causality in complex dynamical systems this is the place. For me particularly was difficult to assimilate because I'm still getting used to algorithms and coding in general. And here's something additional to point out , as part of the course for at least two weeks we had coding tutorials that reviewed some topics with real applications, and thanks to Wolfram support they gave us access to the latest Mathematica software for which I'm very thankful that has a user-friendly interface which for me is a best way to start coding again.