Okay okay.
So now you've got a little idea between the difference of Anaconda and mini Condor.
Hopefully you're not sick of snakes yet because we've got one more Condor to cover and that's Condor
itself.
If Anaconda and many Conda are like the hardware store and workbench and data scientists conduct is
like a data scientists personal assistant.
It can help you set up your workbench or the new tools when you need making a copy of what tools you're
using to share with someone else and more formally Anaconda and many condemn are known as software distributions
and Conda is known as a package manager remember how a package is a collection of code someone else's
written which you can use.
Well kinda helps you download install and manage these packages when you download Anaconda or mini Conda
and install it to your computer.
Contact comes with them but because we're using many Conda many kind of comes with the essentials to
get started like Python not the entire hardware store of data science tools like Anaconda but many kind
of also comes with Kondo so I know this can seem confusing to begin with and trust me it took me a while
to understand this but what Condor allows us to do is install other tools so got many conduct which
is like the base got Python to get started.
That's on our computer and then we use Conda the package manager to install these other packages
you might be thinking.
Daniel why do we do it this way.
This seems so confusing There's so many steps that I already have my computer in telling me you have
to download many condo many that comes with condo colors like some personal assistant that helps me
install packages packages a code.
Other people have written and I totally get you.
I was the same when I first started but after working different teams I started to see how important
it was to get this type of setup for each kind of project you're working on.
Up next we're going to see how Conda our personal assistant for our data science tools can help us to
create an environment which contains different packages that we can use to work on different projects.
Now again I can understand you if you are a bit confused at the moment.
This concept took me a little while to understand too.
We're gonna see it in practice throughout a bunch of different examples throughout the course.