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Let's take a little pause and
spend some time talking about who the specialization is geared for.
Well, the first thing I want to emphasize is the level of the specialization.
And what we're going to do here is we're going to teach you
really important machine learning methods, but we're going to ground them in
real world applications like we saw with our case studies.
So a model that we have here is tough concepts made intuitive and applicable.
So this course isn't going to be about theorem proving.
It's going to be about understanding at a very intuitive and
practical level some very important machine learning algorithms and
thinking about ways in which to deploy them in new problems.
And when we're going about this, our goals here are to minimize the amount of
prerequisite knowledge that you have to have to understand what we're presenting,
while maximizing the ability for you to actually develop and
deploy these methods on new problems that are of interest to you.
And when we're thinking about this, we're going to be presenting concepts
at this very intuitive level that's grounded in these case studies.
So who might you be?
Well, when we're thinking about the target audience,
we're thinking about software engineers who are interested in machine learning.
We're thinking about scientists who might want to become data scientists.
And we're thinking about lots and lots and lots of other people who have some math,
some programming experience, and want to be able to analyze data and
do fun things with it, so just data enthusiasts who want to learn more about
machine learning and how to derive intelligence from data.
Okay.
So I said that we're assuming you have some math and
some programming background, so let's talk about this in a little bit more detail.
In terms of the math background,
we're assuming that you have some basic calculus knowledge.
So that's understanding the notion of derivatives and
how they're computed and basic linear algebra.
So you guys should know what a vector is, what a matrix is, and
how to multiply matrices.
But in these cases, we're really as
often as possible going to present things at the most intuitive level.
Even if we could write down an equation in terms of matrices and matrix multiplies,
we're going to try and add as many visual aids as possible to provide you with that
intuition, so that if you're only marginally comfortable with these ideas,
I do suggest that you go brush up on these concepts.
But, again, we're going to try and
provide the intuition that we described as part of our motto.
And in terms of programming experience,
in this specialization we're going to be using Basic Python for programing.
But if you're not familiar with Python, it would, of course,
be helpful if you were familiar with Basic Python.
But we think that you can pick up on the important tools that you'll need
if you have some other knowledge of some other language.
Okay. So finally,
what are your computing needs for this course?
Well, we're going to assume that you have some basic desktop or laptop or
access to one where you can access the Internet.
Of course, that's important so you can watch these lovely videos, but
beyond that so you can do your assignments.
And to do your assignments, you're going to need to be able to install and
run Python.
And in addition, you're going to be able,
you're going to have to be able to store a few gigabytes of data.
Okay. So
that basically summarizes what we have in mind for who this specialization is for.
And we hope that fits your case.
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