[syllabus.01] Methodology & Categorization

I've just published the list of topics and projects that I'll like to address on this space. Here are some thoughts going forward:

Criteria & Methodology

  • I can choose 12 topics/projects and execute one per month.
  • I can choose 52 exercises and try to execute one per week, more on a sprint mode.
  • I can choose 4 topics and spend 3 months on each one.
  • The last option is to choose 3 topics and spend 4 months on each one.

Categorization

Here's the topics list:

  • P5.JS
  • Two.JS
  • Swift
  • Pure Data
  • After Effects
  • Origami
  • Unity
  • Data mining [see Python]
  • Python [see Data mining]
  • Blender
  • Hardware hacking (learn to use the Raspberry Pi, Arduino or any other HH board)
  • Urban farming
  • RoR / [build an] APIs
  • Openframe
  • Cellphone
  • Raspberry Pi / [how to set up a] server
  • Art / installation [see RPi]

Once organized and categorized it looks like this

1. Programming

  • P5.JS
  • Two.JS
  • Swift
  • Python
  • RoR

2. Softwares & Frameworks

  • Unity
  • Blender
  • Pure Data
  • Origami
  • After Effects

3. Projects

  • Openframe
  • Cellphone
  • Hardware Hacking
  • How to grow food in the city/ Urban farming
  • Build an API

This is the same list by ranking:

  1. P5.JS
  2. Swift
  3. Origami
  4. After Effects
  5. Unity
  6. Cellphone
  7. Build an API
  8. Raspberry Pi / Arduino
  9. Openframe
  10. Python ^
  11. Urban farming
  12. Data mining
  13. Pure Data
  14. Blender
  15. TwoJS

Some other observations and after thoughts:

  • Probably between P5.JS and Swift I have barely the same interest.
  • Origami and After Effects will serve the same purpose: communicate my design and software ideas
  • Learn how to use a Raspberry Pi and/or an Arduino are tied to Openframe and "how to build a Cellphone".
  • Python is an interest just to manipulate data (data mining) but there's no intrinsic interest on learn to do python.
  • Urban farming is something I'm interested in the long term.

That's all for now. See you later.