[MUSIC] 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. [MUSIC]