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APPLICATIONS FOR THE 2020 PROGRAMME ARE NOW CLOSED

Applications for the 2020 Masters in Applied Cybernetics are now closed. 
Thank you to all applicants for your interest, and best wishes for the application process. 

So, you're thinking of applying for the 2020 Masters in Applied Cybernetics at the 3Ai in Canberra?

Have you read the application information? That's the Getting Started guide.

If you already have, and we've piqued your curiosity, well, fist bump.

We've written this in case you're a techie and checked out our GitHub - and wanted to learn more about the type of technologies we use and explore.

If you have more questions, we'll also accept Issues on this Repo. That's how we roll.

You're looking for people from all disciplines. I'm a techie. Is this course for me?

Well, that depends. If you care about humans, technology, and the planet, then it might be.

If you're not so interested in the human side of AI, and are not attracted to a collaborative, collective experience that will challenge you personally and professionally, then it may not be a good fit for you.

We have a couple of techies in our 2019 cohort and they'd be happy to chat / keybase / gitter with you.

What sort of tech do you work with? Do you have a lab?

We have a small Makerspace just for 3Ai students. It's fully equipped with bench space, soldering equipment, screwdrivers, chisels, woodworking tools, vices, a whole bunch of Arduino, Google Coral and other electronics, and even a sewing machine. You get 24 hour Makerspace access, so if you're a night owl and splicing some cables at 3am is your thing, well, we understand.

The network at ANU is backboned on to AARNet, and is generally gigabit to the desktop.

During your course, you'll have a lot of freedom over the technologies you get to explore, but the coursework itself uses a lot of:

  • git and GitLab
  • python and some basic bash
  • Advanced python such as nltk and scikit-learn for machine learning
  • Arduino and the Arduino IDE for working with electronics

What is the gender ratio?

The first cohort (check out #3AiFirstCohort on the Twitters) had a gender ratio of 50% male-identifying and 50% female-identifying. We welcome you if you're enby, trans or cis, and wherever you fall on the red-purple scale.

How do I know that you're pretty technical? Show me some ASCII art.

No worries. We can also discuss favourite *nix distributions too if that's more your jam ;-) Or multivariate calculus. Some of us also speak additional languages. Maj'qa!

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