👓 EdX introduces support fee for free online courses | Inside Higher Ed

Read EdX introduces support fee for free online courses (insidehighered.com)
In its quest to find a sustainable business model, online course provider edX will test charging users for access to previously free content. Observers say the move was inevitable.
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👓 Algorithmic Information Dynamics: A Computational Approach to Causality and Living Systems From Networks to Cells | Complexity Explorer | Santa Fe Institute

Read Algorithmic Information Dynamics: A Computational Approach to Causality and Living Systems From Networks to Cells (Complexity Explorer | Santa Fe Institute)

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 today’s 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.

Students should have basic knowledge of college-level math or physics, though optional sessions will help students with more technical concepts. Basic computer programming skills are also desirable, though not required. The course does not require students to adopt any particular programming language for the Wolfram Language will be mostly used and the instructors will share a lot of code written in this language that student will be able to use, study and exploit for their own purposes.

Course Outline:

  • The course will begin with a conceptual overview of the field.
  • Then it will review foundational theories like basic concepts of statistics and probability, notions of computability and algorithmic complexity, and brief introductions to graph theory and dynamical systems.
  • Finally, the course explores new measures and tools related to reprogramming artificial and biological systems. It will showcase the tools and framework in applications to systems biology, genetic networks and cognition by way of behavioral sequences.
  • Students will be able apply the tools to their own data and problems. The instructors will explain  in detail how to do this, and  will provide all the tools and code to do so.

The course runs 11 June through 03 September 2018.

Tuition is $50 required to get to the course material during the course and a certificate at the end but is is free to watch and if no fee is paid materials will not be available until the course closes. Donations are highly encouraged and appreciated in support for SFI's ComplexityExplorer to continue offering  new courses.

In addition to all course materials tuition includes:

  • Six-month access to the Wolfram|One platform (potentially renewable by other six) worth 150 to 300 USD.
  • Free digital copy of the course textbook to be published by Cambridge University Press.
  • Several gifts will be given away to the top students finishing the course, check the FAQ page for more details.

Best final projects will be invited to expand their results and submit them to the journal Complex Systems, the first journal in the field founded by Stephen Wolfram in 1987.

About the Instructor(s):

Hector Zenil has a PhD in Computer Science from the University of Lille 1 and a PhD in Philosophy and Epistemology from the Pantheon-Sorbonne University of Paris. He co-leads the Algorithmic Dynamics Lab at the Science for Life Laboratory (SciLifeLab), Unit of Computational Medicine, Center for Molecular Medicine at the Karolinska Institute in Stockholm, Sweden. He is also the head of the Algorithmic Nature Group at LABoRES, the Paris-based lab that started the Online Algorithmic Complexity Calculator and the Human Randomness Perception and Generation Project. Previously, he was a Research Associate at the Behavioural and Evolutionary Theory Lab at the Department of Computer Science at the University of Sheffield in the UK before joining the Department of Computer Science, University of Oxford as a faculty member and senior researcher.

Narsis Kiani has a PhD in Mathematics and has been a postdoctoral researcher at Dresden University of Technology and at the University of Heidelberg in Germany. She has been a VINNOVA Marie Curie Fellow and Assistant Professor in Sweden. She co-leads the Algorithmic Dynamics Lab at the Science for Life Laboratory (SciLifeLab), Unit of Computational Medicine, Center for Molecular Medicine at the Karolinska Institute in Stockholm, Sweden. Narsis is also a member of the Algorithmic Nature Group, LABoRES.

Hector and Narsis are the leaders of the Algorithmic Dynamics Lab at the Unit of Computational Medicine at Karolinska Institute.

Alyssa Adams has a PhD in Physics from Arizona State University and studies what makes living systems different from non-living ones. She currently works at Veda Data Solutions as a data scientist and researcher in social complex systems that are represented by large datasets. She completed an internship at Microsoft Research, Cambridge, UK studying machine learning agents in Minecraft, which is an excellent arena for simple and advanced tasks related to living and social activity. Alyssa is also a member of the Algorithmic Nature Group, LABoRES.

The development of the course and material offered has been supported by: 

  • The Foundational Questions Institute (FQXi)
  • Wolfram Research
  • John Templeton Foundation
  • Santa Fe Institute
  • Swedish Research Council (Vetenskapsrådet)
  • Algorithmic Nature Group, LABoRES for the Natural and Digital Sciences
  • Living Systems Lab, King Abdullah University of Science and Technology.
  • Department of Computer Science, Oxford University
  • Cambridge University Press
  • London Mathematical Society
  • Springer Verlag
  • ItBit for the Natural and Computational Sciences and, of course,
  • the Algorithmic Dynamics lab, Unit of Computational Medicine, SciLifeLab, Center for Molecular Medicine, The Karolinska Institute

Class Introduction:Class IntroductionHow to use Complexity Explorer:How to use Complexity Explorer

Course dates: 11 Jun 2018 9pm PDT to 03 Sep 2018 10pm PDT


  1. A Computational Approach to Causality
  2. A Brief Introduction to Graph Theory and Biological Networks
  3. Elements of Information Theory and Computability
  4. Randomness and Algorithmic Complexity
  5. Dynamical Systems as Models of the World
  6. Practice, Technical Skills and Selected Topics
  7. Algorithmic Information Dynamics and Reprogrammability
  8. Applications to Behavioural, Evolutionary and Molecular Biology


Another interesting course from the SFI. Looks like an interesting way to spend the summer.

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Reply to A (very) gentle comment on Algebraic Geometry for the faint-hearted | Ilyas Khan

Replied to A (very) gentle comment on Algebraic Geometry for the faint-hearted by Ilyas KhanIlyas Khan (LinkedIn)
This short article is the result of various conversations over the course of the past year or so that arose on the back of two articles/blog pieces that I have previously written about Category Theory (here and here). One of my objectives with such articles, whether they be on aspects of quantum computing or about aspects of maths, is to try and de-mystify as much of the associated jargon as possible, and bring some of the stunning beauty and wonder of the subject to as wide an audience as possible. Whilst it is clearly not possible to become an expert overnight, and it is certainly not my objective to try and provide more than an introduction (hopefully stimulating further research and study), I remain convinced that with a little effort, non-specialists and even self confessed math-phobes can grasp some of the core concepts. In the case of my articles on Category Theory, I felt that even if I could generate one small gasp of excited comprehension where there was previously only confusion, then the articles were worth writing.

I just finished a course on Algebraic Geometry through UCLA Extension, which was geared toward non-traditional math students and professionals, and wish I had known about Smith’s textbook when I’d started. I did spend some time with Cox, Little, and O’Shea’s Ideals, Varieties, and Algorithms which is a pretty good introduction to the area, but written a bit more for computer scientists and engineers in mind rather than the pure mathematician, which might recommend it more toward your audience here as well. It’s certainly more accessible than Hartshorne for the faint-of-heart.

I’ve enjoyed your prior articles on category theory which have spurred me to delve deeper into the area. For others who are interested, I thought I’d also mention that physicist and information theorist John Carlos Baez at UCR has recently started an applied category theory online course which I suspect is a bit more accessible than most of the higher graduate level texts and courses currently out. For more details, I’d suggest starting here: https://johncarlosbaez.wordpress.com/2018/03/26/seven-sketches-in-compositionality/

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🔖 Quantum Information Science II

Bookmarked Quantum Information Science II (edX)
Learn about quantum computation and quantum information in this advanced graduate level course from MIT.

About this course

Already know something about quantum mechanics, quantum bits and quantum logic gates, but want to design new quantum algorithms, and explore multi-party quantum protocols? This is the course for you!

In this advanced graduate physics course on quantum computation and quantum information, we will cover:

  • The formalism of quantum errors (density matrices, operator sum representations)
  • Quantum error correction codes (stabilizers, graph states)
  • Fault-tolerant quantum computation (normalizers, Clifford group operations, the Gottesman-Knill Theorem)
  • Models of quantum computation (teleportation, cluster, measurement-based)
  • Quantum Fourier transform-based algorithms (factoring, simulation)
  • Quantum communication (noiseless and noisy coding)
  • Quantum protocols (games, communication complexity)

Research problem ideas are presented along the journey.

What you’ll learn

  • Formalisms for describing errors in quantum states and systems
  • Quantum error correction theory
  • Fault-tolerant quantum procedure constructions
  • Models of quantum computation beyond gates
  • Structures of exponentially-fast quantum algorithms
  • Multi-party quantum communication protocols

Meet the instructor

bio for Isaac ChuangIsaac Chuang Professor of Electrical Engineering and Computer Science, and Professor of Physics MIT

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Introduction to Information Theory | SFI’s Complexity Explorer

The Santa Fe Institute's free online course "Introduction to Information Theory" taught by Seth Lloyd via Complexity Explorer.

Many readers often ask me for resources for delving into the basics of information theory. I hadn’t posted it before, but the Santa Fe Institute recently had an online course Introduction to Information Theory through their Complexity Explorer, which has some other excellent offerings. It included videos, fora, and other resources and was taught by the esteemed physicist and professor Seth Lloyd. There are a number of currently active students still learning and posting there.

Introduction to Information Theory

About the Tutorial:

This tutorial introduces fundamental concepts in information theory. Information theory has made considerable impact in complex systems, and has in part co-evolved with complexity science. Research areas ranging from ecology and biology to aerospace and information technology have all seen benefits from the growth of information theory.

In this tutorial, students will follow the development of information theory from bits to modern application in computing and communication. Along the way Seth Lloyd introduces valuable topics in information theory such as mutual information, boolean logic, channel capacity, and the natural relationship between information and entropy.

Lloyd coherently covers a substantial amount of material while limiting discussion of the mathematics involved. When formulas or derivations are considered, Lloyd describes the mathematics such that less advanced math students will find the tutorial accessible. Prerequisites for this tutorial are an understanding of logarithms, and at least a year of high-school algebra.

About the Instructor(s):

Professor Seth Lloyd is a principal investigator in the Research Laboratory of Electronics (RLE) at the Massachusetts Institute of Technology (MIT). He received his A.B. from Harvard College in 1982, the Certificate of Advanced Study in Mathematics (Part III) and an M. Phil. in Philosophy of Science from Cambridge University in 1983 and 1984 under a Marshall Fellowship, and a Ph.D. in Physics in 1988 from Rockefeller University under the supervision of Professor Heinz Pagels.

From 1988 to 1991, Professor Lloyd was a postdoctoral fellow in the High Energy Physics Department at the California Institute of Technology, where he worked with Professor Murray Gell-Mann on applications of information to quantum-mechanical systems. From 1991 to 1994, he was a postdoctoral fellow at Los Alamos National Laboratory, where he worked at the Center for Nonlinear Systems on quantum computation. In 1994, he joined the faculty of the Department of Mechanical Engineering at MIT. Since 1988, Professor Lloyd has also been an adjunct faculty member at the Sante Fe Institute.

Professor Lloyd has performed seminal work in the fields of quantum computation and quantum communications, including proposing the first technologically feasible design for a quantum computer, demonstrating the viability of quantum analog computation, proving quantum analogs of Shannon’s noisy channel theorem, and designing novel methods for quantum error correction and noise reduction.

Professor Lloyd is a member of the American Physical Society and the Amercian Society of Mechanical Engineers.

Tutorial Team:

Yoav Kallus is an Omidyar Fellow at the Santa Fe Institute. His research at the boundary of statistical physics and geometry looks at how and when simple interactions lead to the formation of complex order in materials and when preferred local order leads to system-wide disorder. Yoav holds a B.Sc. in physics from Rice University and a Ph.D. in physics from Cornell University. Before joining the Santa Fe Institute, Yoav was a postdoctoral fellow at the Princeton Center for Theoretical Science in Princeton University.

How to use Complexity Explorer: How to use Complexity Explore
Prerequisites: At least one year of high-school algebra
Like this tutorial? 


  1. Introduction
  2. Forms of Information
  3. Information and Probability
  4. Fundamental Formula of Information
  5. Computation and Logic: Information Processing
  6. Mutual Information
  7. Communication Capacity
  8. Shannon’s Coding Theorem
  9. The Manifold Things Information Measures
  10. Homework
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The Teaching Company and The Great Courses versus MOOCs

Robert Greenberg recently wrote a Facebook post relating to a New York Times review article entitled “For This Class, Professors Pass Screen Test“. It’s substantively about The Teaching Company and their series The Great Courses (TGC); for convenience I’ll excerpt his comments in their entirety below:

A most interesting article on The Great Courses (TGC) appeared in the New York Times on Saturday. TGC has been featured in newspaper articles before: scads of articles, in fact, over the last 20-plus years. But those articles (at least the ones I’m aware of and I am aware of most of them) have always focused on the content of TGC offerings: that they are academic courses offered up on audio/video media. This article, written by the Times’ TV critic Neil Genzlinger, is different. It focuses on TGC as a video production company and on TGC courses as slick, professional, high-end television programs.

My goodness, how times have changed.

Long-time readers of this blog will recall my descriptions of TGC in its early days. I would rehash a bit of that if only to highlight the incredible evolution of the company from a startup to the polished gem it is today.

I made my first course back in May of 1993: the first edition of “How to Listen to and Understand Great Music”. We had no “set”; I worked in front of a blue screen (or a “traveling matte”). The halogen lighting created an unbelievable amount of heat and glare. The stage was only about 6 feet deep but about 20 feet wide. With my sheaf of yellow note paper clutched in my left hand, I roamed back-and-forth, in constant motion, teaching exactly the way I did in the classroom. I made no concessions to the medium; to tell the truth, it never occurred to me or my director at the time that we should do anything but reproduce what I did in the classroom. (My constant lateral movement did, however, cause great consternation among the camera people, who were accustomed to filming stationary pundits at CNN and gasbags at C-span. One of our camera-dudes, a bearded stoner who will remain nameless kept telling me “Man . . . I cannot follow you, man. Please, man, please!” He was a good guy though, and offered to “take my edge off” by lighting me up during our breaks. I wisely declined.)

We worked with a studio audience in those days: mostly retirees who were free to attend such recording sessions, many of whom fell asleep in their chairs after lunch or jingled change in their pockets or whose hearing aids started screaming sounds that they could not hear but I most certainly did. Most distracting were the white Styrofoam coffee cups; in the darkened studio their constant (if irregular) up-and-down motion reminded me of the “bouncing ball” from the musical cartoons of the 1930s, ‘40s, and ‘50s.

I could go on (and I will, at some other time), though the point is made: in its earliest days TGC was simply recording more-or-less what you would hear in a classroom or lecture hall. I am reminded of the early days of TV, during which pre-existing modes of entertainment – the variety show, theatrical productions, puppet shows – were simply filmed and broadcast. In its earliest permutation, the video medium did not create a new paradigm so much as record old ones. But this changed soon enough, and the same is true for TGC. Within a few years TGC became a genuine production company, in which style, look, and mode of delivery became as important as the content being delivered. And this is exactly as it should be. Audio and video media demand clarity and precision; the “ahs” and “ums” and garbled pronunciations and mismatched tenses that we tolerate in a live lecture are intolerable in media, because we are aware of the fact that in making media they can (and should) be corrected.

Enough. Read the article. Then buy another TGC course; preferably one of mine. And while watching and/or listening, let us be aware, as best as we can, of the tens-of-thousands of hours that go into making these courses – these productions – the little masterworks that they indeed are.


My response to his post with some thoughts of my own follows:

This is an interesting, but very germane, review. As someone who’s both worked in the entertainment industry and followed the MOOC (massively open online courseware) revolution over the past decade, I very often consider the physical production value of TGCs offerings and have been generally pleased at their steady improvement over time. Not only do they offer some generally excellent content, but they’re entertaining and pleasing to watch. From a multimedia perspective, I’m always amazed at what they offer and that generally the difference between the video versus the audio only versions isn’t as drastic as one might otherwise expect. Though there are times that I think that TGC might include some additional graphics, maps, etc. either in the course itself or in the booklets, I’m impressed that they still function exceptionally well without them.

Within the MOOC revolution, Sue Alcott’s Coursera course Archaeology’s Dirty Little Secrets is still by far the best produced multi-media course I’ve come across. It’s going to take a lot of serious effort for other courses to come up to this level of production however. It’s one of the few courses which I think rivals that of The Teaching Company’s offerings thus far. Unfortunately, the increased competition in the MOOC space is going to eventually encroach on the business model of TGC, and I’m curious to see how that will evolve and how it will benefit students. Will TGC be forced to offer online fora for students to interact with each other the way most MOOCs do? Will MOOCs be forced to drastically increase their production quality to the level of TGC? Will certificates or diplomas be offered for courseware? Will the subsequent models be free (like most MOOCs now), paid like TGC, or some mixture of the two?

One area which neither platform seems to be doing very well at present is offering more advanced coursework. Naturally the primary difficulty is in having enough audience to justify the production effort. The audience for a graduate level topology class is simply far smaller than introductory courses in history or music appreciation, but those types of courses will eventually have to exist to make the enterprises sustainable – in addition to the fact that they add real value to society. Another difficulty is that advanced coursework usually requires some significant work outside of the lecture environment – readings, homework, etc. MOOCs seem to have a slight upper hand here while TGC has generally relied on all of the significant material being offered in a lecture with the suggestion of reading their accompanying booklets and possibly offering supplementary bibliographies. When are we going to start seeing course work at the upper-level undergraduate or graduate level?

The nice part is that with evolving technology and capabilities, there are potentially new pedagogic methods that will allow easier teaching of some material that may not have been possible previously. (For some brief examples, see this post I wrote last week on Latin and the digital humanities.) In particular, I’m sure many of us have been astounded and pleased at how Dr. Greenberg managed the supreme gymnastics of offering of “Understanding the Fundamentals of Music” without delving into traditional music theory and written notation, but will he be able to actually offer that in new and exciting ways to increase our levels of understanding of music and then spawn off another 618 lectures that take us all further and deeper into his exciting world? Perhaps it comes in the form of a multimedia mobile app? We’re all waiting with bated breath, because regardless of how he pulls it off, we know it’s going to be educational, entertaining and truly awe inspiring.

Following my commentary, Scott Ableman, the Chief Marketing Officer for TGC, responded with the following, which I find very interesting:

Chris, all excellent observations (and I agree re Alcott’s course). I hope you’ll be please to learn that the impact of MOOCs, if any, on The Great Courses has been positive, in that there is a rapidly growing awareness and interest in the notion that lifelong learning is possible via digital media. As for differentiating vs. MOOCs, people who know about The Great Courses generally find the differences to be self-evident:

  1. Curation: TGC scours the globe to find the world’s greatest professors;
  2. Formats: The ability to enjoy a course in your car or at home on your TV or on your smartphone, etc.;
  3. Lack of pressure: Having no set schedule and doing things at your own pace with no homework or exams (to be sure, there are some for whom sitting at a keyboard at a scheduled time and taking tests and getting a certificate is quite valuable, but that’s a different audience).

The Great Courses once were the sole claimant to a fourth differentiator, which is depth. Obviously, the proliferation of fairly narrow MOOCs provides as much depth on many topics, and in some cases addresses your desire for higher level courses. Still TGC offers significant depth when compared to the alternatives on TV or audio books. I must say that I was disappointed that Genzlinger chose to focus on this notion that professors these days “don’t know how to lecture.” He suggests that TGC is in the business of teaching bad lecturers how to look good in front of a camera. This of course couldn’t be further from the truth. Anybody familiar with The Great Course knows that among its greatest strengths is its academic recruiting team, which finds professors like Robert Greenberg and introduces them to lifelong learners around the world.