Amazon's ML University is making its online courses available to the public

You're confusing software engineering for computer science.

Software engineering on average is indeed knowing the APIs of a few frameworks or products well.

I understand this sentiment, but I also don’t think it’s very realistic to expect this based on how much more money people make working in industry vs education.

I was once interested in teaching at a software engineering school and the money offered wasn’t even close to being competitive with what I was earning as a full-time developer.

There’s just no way education for the sake of education can compete with programs put on by these companies that have established business models and practices. Why would experts at FB/GOOG/AZN leave those opportunities to go build curriculum at public institutions for a fraction of what they make as ML experts at these companies?

Maybe that's the key to quick success?

Because I know tons of well paid frontend devs that do not understand even the most basic web technologies. They are however good in using 2-3 specific frameworks.

Remember when everyone needed a little computer knowledge, maybe even some minimal programming skills, even if you were a mathematician or a social scientist?

Well, now we have a similar situation with data sciences.

My impression is that ML is getting to the point where you can do useful ML for some businesses without needing particularly deep expertise or creativity so I could see a commoditized lower end to the market developing (just like you can get a generic mobile app from a random consultancy), but there will still be a lot of important business problems that are too hard to tackle that way, leaving a lot of room for experts in the market as well.

2) It requires data, and a lot of it, and the cleaning and maintenance of it. Very few people have access to the necessary data, and companies are protective of it.

3) AI has very few obvious applications. There are a lot of 'apps' because they do something useful for us. But how many 'AIs' have you downloaded or used, i.e. things that are mostly AI? AI is an 'approach' not a 'solution'.

So because of those things, we're not seeing a 'sea of developers' like wit iOS, rather, AI is caught up in the 'big companies'.

Because 1) AI researchers are still expensive and 3) they are generally not profitable.

Because of 2) there are few places regular people can practice AI.

So you end up with massive companies that can support major R&D operations (Google, Amazon), and a ton of secondary companies with tons of data, but can barely manage their own IT, let alone, do 'fancy AI'. Think airlines, most banks, insurance companies.

So the first real applications of AI come out of Google. We will start to see some financial products etc.. We'll some nice experimental apps, but generally not a lot of 'small companies winning hard on an AI play'.

That said - you may see startups who are 90% regular company, but who have some AI tweaks that make them differentiated.

FYI - a lot of AI is still mundane: Spotify playlists, Shopify support - we would not miss it if the AI were removed, it's mostly superficial gains.

AI is a weird subject because 'it will change the world' but mostly by providing incremental jumps in some areas, that allow bigger jumps in others, like 'self driving cars' - the improved image recognition means cars cross a treshhold whereby they can start to understand enough around them so as to actually, possibly drive on their own.

For all that is holy I hope not - speaking as a consultant who works at AWS. I held a number of AWS certifications before being hired. I used them mostly as a guided learning path to help me know what I didn’t know. I also had “enough” real world experience as both a developer and working with AWS’s fiddly bits to be useful relatively quickly when I started working here.

I saw far too many “paper tigers” when I was in the real world who have all of the certifications you could imagine but couldn’t pass my relatively simple tech screen when I was hiring operations people to take some of the load off of me so I could concentrate on some development projects.

Certifications in no way prove competency.

I think there is value in certification anyway, as per the AWS certs, but not as a “let’s skip part of the hiring process”, maybe just edges you on the CV screen perhaps.

See here for a different program with Udacity: https://www.udacity.com/scholarships/aws-machine-learning-sc...

https://github.com/aws-samples/aws-machine-learning-universi...

sklearn + mxnet ?

There was a special session offered at one point that covered how to apply what you had learned using AWS services like SageMaker, but it wasn't integrated into the curriculum. (Not sure if this is still the case; I took MLU courses in early 2019.)

Completely ignoring the educational content itself, well made educational videos bring community good will. This helps in both purchasing decisions and recruitment. Honestly, this basically can come from a PR / recruiting budget. Lecturer's aren't that expensive.

Now, for ML specifically, expanding the set of ML engineers has a dual benefit:

1) Creates more awareness and therefore demand for ML cloud services. Opensource? No problem, amazon will cheerfully sell you gpu enabled ec2 instances.

2) Expanded pool of candidates for hiring, and increased likelihood that internally, someone will propose a viable ML solution/product.

The ML sector is still growing rapidly, anything that fuels its growth is going to benefit Amazon simply by virtue that they're always going to be in the running for any business purchasing decision, and probabilistically, they'll get a percentage cut of that growth. Education helps grow it, and educational videos are pretty dang cheap.

Also, ML isn't magic. It's almost as much work as not using ML, if you want actually good results.

If you order a Rode microphone and a Sony RX cam, it might figure out that you're a Youtuber and might recommend a Zhiyun gimbal. The cluster of data points point to that.

But if you have order pattern where the data is sparse, it's not likely to come up with a good recommendation.

I think what makes them interesting is that now I have a lot of choice in which classes to take... maybe someone will set up a "Rotten Tomatoes" site to rate online classes.

I don't want to take every single NLP class, but if I take one here, and don't quite get it, perhaps the Google (or Stanford, or whoever) course will make it click for me, or offer some alternative insight or useful method.

So I'm glad they're putting them up. Thanks Amazon!