Gonna keep this short. My biggest moment was when I finally learned and understood how artificial neural networks (ANNs) - and specifically back-propagation -

Gonna keep this short. My biggest moment was when I finally learned and understood how artificial neural networks (ANNs) - and specifically back-propagation - actually worked. It happened in the fall of 2011 - I took on the challenge of the Stanford University sponsored AI Class (Thrun, et al) and ML Class (Andrew Ng). I wasn't able to complete the AI Class due to personal issues, but I did complete the ML Class. In 2012 I took Udacity's CS 373 Self-Driving Vehicle course (and completed it) to "make up" missing the rest of the AI Class. But it was the ML Class that really drove things home; learning and using Octave was a revelation for me (vectors as a primitive? COOL!) - and learning to think on how to parallelize problems for that (and then later learning that an ANN was just such an application) - woke up a lot in me. Finally - a practical use for a home Beowulf cluster! These experiences have led me to this year, where starting on November 28th, I'll be participating in Udacity's Self-Driving Car Engineer nanodegree program. I believe that as we move forward in the future as software engineers, knowing and understanding ML and AI algorithms, etc will be something employers will increasingly want and expect of developers. I'm keeping my skills current - you should too. /43 years old, been professionally coding since I was 18 - and coding in some manner or another since I was 11 (yep - TRS-80 Color Computer w/ 16k FTW!)