
Google AI Education Resources - killjoywashere
https://ai.google/education/
======
lawrenceyan
I really like the Introduction to Machine Learning Course that Google has put
up on their developer site [0]. It's simple enough that anyone can get into
it, while still digging deep enough into the math behind things that it isn't
just you learning how to copy and paste code.

Besides reading an actual textbook or learning from an online course like
([https://eecs189.org/](https://eecs189.org/)) which can understandably be
somewhat daunting at first, I think this is definitely the next best thing.

[0] [https://developers.google.com/machine-learning/crash-
course/](https://developers.google.com/machine-learning/crash-course/)

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DarkContinent
I think it's really cool that Google is so motivated about creating and
releasing educational content that anyone can use to become a great developer.
Their tech dev guide is also pretty helpful (although in fairness, their cloud
education does focus on GCP pretty heavily).

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pm90
Google's play seems to be to encourage more and more folks to learn CS and be
interested in learning programming and AI. Google Research, GSoC, PhD research
grants, publishing their results in leading journals, and their OSS
contributions all point to a company that is a friend of programmers and
academics. For these very reasons, the company is viewed very positively
outside of SV.

On the contrary, I don't see a similar desire to contribute back from Amazon,
Apple, Facebook or Netflix (although the last 2 do contribute a ton to OSS).

~~~
codingslave
Most of googles evangelization of tech and AI is a marketing and adoption
strategy for google compute engine. Which is fine, but it should be seen for
what it is

~~~
cameronbrown
Disclaimer: I am personally benefiting from a long-term Google educational
programme.

My response to this is: so what? Of course they're going to encourage new
developers to use their products - it's only natural they'd teach their own
stuff and not AWS/Azure. Developers aren't really influencers (sadly) in the
purchasing for cloud infra so I'm not sure that it's a straight up marketing
campaign.

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Teracotage
Here is this free course that grants a certificate for the University of
Helsinki, [https://www.elementsofai.com/](https://www.elementsofai.com/) it is
for beginners, some banks are using it for their staff too.

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yogrish
For me the biggest problem, as manager to build AI team, is everyone talks
jargons of AI/DL through these kind of courses. How do I find out who knows in
depth? Do you have any intriguing questions you have that can quickly separate
the wheat from chaff? Is there any Questionnaire on AI/DL that help select (AI
expert)/prepare (for Job interview)?

~~~
krapht
Same as you'd select any other professional where you don't know how to do
their job.

1) Work experience. 2) Educational pedigree.

There's also the idea you should hire a program lead who does have
demonstrated experience, and let them do the technical interviews of their
underlings...

At the companies I've worked for doing scientific programming work, during my
interview I had to give a presentation to the engineering team over lunch
concerning a technical problem and take questions. If a candidate was a fresh
graduate we had a requirement they have 1) a Master's and 2) they would
present on any research papers they had published, UNLESS 3) they had interned
at our company and everyone liked them, then they could skip the Master's
requirement.

~~~
commandlinefan
> research papers they had published

I wonder how academic publishers feel about this growing trend to require not
just a degree, but now peer-reviewed, published, research papers to get a job.
The sentiment behind it is, of course, if you’re really smart, you would be
published, so if we look for people who are published, we know they’re smart.
The reality, though, is that once this catches on, journals are going to be
flooded (even more than they already are) with desperate attempts to get
something, anything, with somebody’s name on it since that’s another checkbox
they have to tick before they can eat. Just like what happened with higher
education.

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distdev89
I'm a backend developer who uses Java an GoLang regularly to write back end
systems - APIs, workflows, infrastructure, deployment pipelines, etc.

I don't have any knowledge about AI or how to model problems for
recommendation systems, or when to use decision trees, versus something else.
Is this a skill that I should be actively investing in to not become a
dinosaur?

My worry is that in the next 10 or so years, I don't want to end up as a Cobol
developer in the world of today i.e., might have a job and good pay, but not
being able to work at the next big company or next big idea. What are your
thoughts?

~~~
ovi256
When databases came by, I bet people felt the same way about them. Now they're
a common tool used in most systems, and most devs and engineers will have at
least a basic understanding.

My hypothesis is that ML will follow a similar path. It seems like an exotic
skill now, but there's already a mass of undergrads familiar with it from
their education. We'll still need experienced practitioners to lead projects
and architect systems (like DB admins and architects do!). But in some 10 to
20 years, everyone will use ML where appropriate, get some value from it, and
it will have lost its hype. There will be some uniquely new capabilities that
ML enables, just like DBs enabled storing state at scale, efficiently and
cheaply.

~~~
cameronbrown
Indeed. ML won't be the be-all end-all of software engineering, but it'll be a
core skill to have significant knowledge about. Even if you're not developing
new models, knowing the best practices for using them or extending them is
going to be invaluable.

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eternal_intern
I work as a Mechatronics engineer and I have an interest in AI. I've
personally gone through a lot of the online resources out there: 1\. Andrew
Ngs Deep learning MOOC

2\. Fast AI parts 1 & 2

3\. The old Google Machine learning course

But, what next?. From my experience, this doesn't give you enough credibility
to get you a job interview at even a small sized firm, let alone Google.

Don't get me wrong, I really appreciate all the fantastic AI learning
resources out there. Its incredibly enabling, but I feel like I'm missing the
point of this - Is it to enable people to start companies using AI based tech,
and grow the google compute based ecosystem? If its to grow the number of AI
jobs and eligible people for those jobs, I have doubts whether that's actually
working, or am I missing something?

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ramblerman
Surely the easy answer is do something with your knowledge. If you feel you
can apply it, then I would say it was useful.

I couldn't imagine reading 3 books on python, and wondering will I get an
interview. The question should be, can I write a simple program. Measuring by
can I get a job interview is asking the reverse question.

I mean, would you hire you? Can you solve a potential company's problems with
your AI toolset.

~~~
eternal_intern
I get what you mean. I've been applying the skillset to Kaggle problems, each
of which I imagine contain multiple subproblems which companies might face.
But kaggle standings, in my experience, dont seem to be too convincing a
metric for job openings.

The problem with the MOOC ecosystem at the moment is there's no clear path
forward with them. I'd have imagined the MOOC certifications solving this
problem, but I feel networking plays a much bigger role in the job market
rather than credibility.

The only exception I see is Udacity, which, by its pricing has created a
limited pool of graduates, and therefore are valued much higher

~~~
ps101
Stay away from:

\- MOOCs

\- Udacity

\- Kaggle

I'm not being facetious, this is my honest advice.

