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[MUSIC]

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Hi, I'm Kenneth.

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If you find yourself interested in using
Python for scientific pursuits, data

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analysis, data science, computer vision,
or any of a number of other fields,

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you're going to come across a bit
of software named Anaconda.

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Besides being a clever pun on Python,
Anaconda is a large and

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powerful platform that's heavily used by
science and data-oriented Pythonistas.

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And it provides a ton of the tools
you'll use in those areas like Pandas,

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Jupyter Notebook, and more.

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In fact, that's why people
use the Anaconda platform.

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It makes it faster and
easier to set up and install the tools and

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libraries that you need
to do your science.

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Another benefit of using a platform like
Anaconda comes out when you're working

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with a team or need to share your
results with others in the community.

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Using a standardized platform lets you
all easily replicate an environment and

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set up quickly and reliably.

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That means less time spent setting
things up and tweaking libraries and

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more time for your science.

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Beyond that though, Anaconda also
brings with it easier manipulation and

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use of data sources,
a community of experts, and a lot more.

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In fact, I won't even be able to scratch
the surface of all of the powers and

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benefits that Anaconda can give you.

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Luckily, you won't need all
of these to start with.

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You'll just need to get
Anaconda installed.

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And that's exactly what
this workshop is about.

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We're going to look at how to
install the Anaconda platform.

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How to use it to install packages and

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libraries and
a smaller alternative version of Anaconda

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that might be more useful to you if
you're not a day to day data scientist.

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I'm gonna show you all the steps
you needed to do on a Mac, but

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they'll be similar enough on another
platforms that you shouldn't have any

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issues getting things running.

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Let's get started