Granted, that's not enough to actually find work doing anything ML-related, as there are now plenty of experts with years of experience out there on the job market, but hey, I like learning stuff for the sake of it. I'm thinking of taking one of the follow-up courses on NN.
In any case, it's on the resume. No idea if it looks good or not.
Of course, if I were really serious about it, maybe I ought to go for a PhD in CS. But at 37 years old, I'm approaching the end of my useful life as a software engineer. I understand I have to report to something called "Caoursel" on my 40th birthday, whatever that is.
EDIT: Allright, I took it because at the time I was working as a software development "SME" on a program in which AI, ML and data science terms were being bandied about by the PhDs and I wanted to be able to sit in on meetings and at least follow the conversation (And not look completely stupid. Adopting a stern look and nodding along will only get you so far, occasionally you have to speak). The course largely fulfilled its purpose on that score.
For your case of staying current in newer tech I can see the market reason for taking it. People like Knuth who're well into their 70's still seem to find ways to remain relevant as well. What is the "Caoursel" you're referring to?
I am a 35 year old who has done development, and may do it again in the future. I have kept my skillset updated by taking several AI courses during a sabbatical.
If you are competing against a group that competes for roles that select for what you think is silly, you'll never win. This does not describe most startups; it may be an indicator of bad startups.
There is age discrimination, for sure. In the startup cohort study of the future, I am quite confident those exhibiting this discrimination will not be on the successful side.
Younger devs focus on their skills. Older devs focus on the value they bring to the company. Companies that focus on the latter will do better.
YMMV, we live in a probabilistic world.
Also, I've worked with non-degree holders. If they were good, they managed to find employment. Though, often employers will use the lack of a degree as an excuse to pay less, which isn't right.
And Logan's Run looks like a neat movie, in my city we have a monthly mash-up of old films that play at an independent theater, so I'll check it out sometime.
In reply to your Knuth comment...Tom Brady is 40 years old but you're not going to find many football players who are 40 and still playing in Super Bowls.
I hope that’s not the case. 45 and still going strong...
I hope you are just trying to be darkly humorous about ageism because this reads like a plot point from a dystopian sci-fi horror movie.
I should probably update the post to say that...
Even areas in which my company can potentially benefit from Machine Learning, we don't have access to vast troves of data to use as training sets. So our brainstorming sessions have gone nowhere.
For finding a use case or at work just think of any normal problem like UI or ux design, or showing someone an enjoyable loading screen or funny picture, anyone can make something okay but to solve a problem close to optimally you start to need to gather data and do ml/ai
Where would I start with this? Is this even an ML problem?
Consider looking into traditional forecasting methods as a baseline. AR(I)MA based approaches with seasonality might actually be fine for you.
However, it all changes if there are structural breaks in your dataset. Look into Rob Hyndman's free online book (https://otexts.org/fpp2/) for an excellent introduction into timeseries forecasting.
Oh wow, this is right in the wheelhouse of my site... have you written anywhere about the process of setting it up / the progress you’ve made?