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[MUSIC]

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Let's take a little pause and

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spend some time talking about who
the specialization is geared for.

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Well, the first thing I want to emphasize
is the level of the specialization.

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And what we're going to do here
is we're going to teach you

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really important machine learning methods,
but we're going to ground them in

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real world applications like
we saw with our case studies.

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So a model that we have here is tough
concepts made intuitive and applicable.

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So this course isn't going
to be about theorem proving.

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It's going to be about understanding
at a very intuitive and

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practical level some very important
machine learning algorithms and

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thinking about ways in which to
deploy them in new problems.

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And when we're going about this, our
goals here are to minimize the amount of

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prerequisite knowledge that you have to
have to understand what we're presenting,

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while maximizing the ability for
you to actually develop and

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deploy these methods on new problems
that are of interest to you.

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And when we're thinking about this,
we're going to be presenting concepts

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at this very intuitive level that's
grounded in these case studies.

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So who might you be?

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Well, when we're thinking
about the target audience,

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we're thinking about software engineers
who are interested in machine learning.

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We're thinking about scientists who
might want to become data scientists.

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And we're thinking about lots and lots and
lots of other people who have some math,

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some programming experience, and
want to be able to analyze data and

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do fun things with it, so just data
enthusiasts who want to learn more about

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machine learning and
how to derive intelligence from data.

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Okay.

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So I said that we're assuming
you have some math and

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some programming background, so let's talk
about this in a little bit more detail.

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In terms of the math background,

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we're assuming that you have
some basic calculus knowledge.

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So that's understanding
the notion of derivatives and

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how they're computed and
basic linear algebra.

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So you guys should know what a vector is,
what a matrix is, and

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how to multiply matrices.

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But in these cases, we're really as

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often as possible going to present
things at the most intuitive level.

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Even if we could write down an equation in
terms of matrices and matrix multiplies,

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we're going to try and add as many visual
aids as possible to provide you with that

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intuition, so that if you're only
marginally comfortable with these ideas,

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I do suggest that you go
brush up on these concepts.

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But, again, we're going to try and

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provide the intuition that we
described as part of our motto.

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And in terms of programming experience,

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in this specialization we're going to
be using Basic Python for programing.

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But if you're not familiar with Python,
it would, of course,

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be helpful if you were
familiar with Basic Python.

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But we think that you can pick up on
the important tools that you'll need

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if you have some other knowledge
of some other language.

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Okay.
So finally,

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what are your computing needs for
this course?

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Well, we're going to assume that you
have some basic desktop or laptop or

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access to one where you
can access the Internet.

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Of course, that's important so
you can watch these lovely videos, but

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beyond that so
you can do your assignments.

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And to do your assignments, you're
going to need to be able to install and

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run Python.

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And in addition, you're going to be able,

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you're going to have to be able
to store a few gigabytes of data.

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Okay.
So

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that basically summarizes what we have in
mind for who this specialization is for.

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And we hope that fits your case.

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[MUSIC]