The promise is something else: "In this article, I'll develop Python code that will take me from an idea for a protein all the way to expression of the protein in a bacterial cell, all without touching a pipette or talking to a human." In many ways this post is super-complex and I wouldn't expect readers to work though the example provided. For one thing, it would cost some money, and for another, synthesizing your own proteins isn't exactly the easiest thing to do if you don't have any bio-engineering background. That said, this is a fantastic example of the sort of thing we can do with dynamic data-driven open educational resources (OER). Even if all you do is follow along and tweak the embedded algorithms and graphs, you're still gaining something. (From 2016, via O'Reilly - the website is getting slammed at the moment but the response on Wayback is pretty good). More tools for working in the cloud from last week.
I saw this a few days ago, didn't list it, and then needed it almost right away. That's a pretty good sign I need to list it. This summary describes how artificial intelligence is being used in education. What makes it useful are the breakdowns - differemt AI applications, different uses in education, different reasons for adoption, where AI is creating value, etc. All with colourful charts suitable for framing.
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Copyright 2019 Stephen Downes Contact: firstname.lastname@example.orgThis work is licensed under a Creative Commons License.