Before we jump into Python,
I want to show you a couple of features of the Coursera platform.
Here is our course that I have logged in to.
You see that there is three weeks.
When we click on a week we have built in Jupyter notebooks.
Now these are a great way to learn data science and
it's something new that the Coursarians have added to the platform for us.
When you see one of the notebooks you can click on it,
you can open the notebook into a new window and
you can actually follow along exactly with everything that we talk about.
So you could actually run this code yourself just by selecting
the code and hitting Shift+Enter, and
just run through it actually testing all of the different pieces of code.
And so I think a lot of people will use this in a split screen mode.
So you take this window out and you watch the video in one window
while you actually walk through the code in another.
I think it's a great addition.
Jumping back, we also have assignments that are built in.
Jumping back to the course home page, we'll go to week two.
In week two we have an assignment built right into the jupiter notebook and
this is great.
So you can open the jupyter notebook for assignment two.
You get all of the questions provided to you directly.
You can open up the assignment, you can directly see the questions.
There's stub code for your answers here.
So for instance for
question one where you have to figure out how many gold medals there are.
There's a function written, answer one, and
you just write in what your response is here.
You can of course write any python that you would like, in here, and so forth.
So this is a great way to do your assignments.
When you've done your assignment you just submit it,
by clicking the submit button at the top.
You can follow that URL to see details about your submission.
In addition you can go to the course page, click on the programming
assignment, And look at your previous submissions.
You can see here I've got a lot of submissions because I've been
testing these notebooks.
But you can actually create a custom solution of your own,
offline if you want to do all the work with the Jupyter Notebooks on your PC,
just upload that file as appropriate and submit it for grading.
So those are some of the features that Coursera has added to the platform for us.
Some of the other features are in-video-quizzes that allow you to change the code
as you're watching the video.
So we'll see an example of that here.
When you're viewing the video you can see a number of the IPython notebooks.
You'll see these yellow little marker on the video timeline.
These are in video quizzes.
Something Coursera's added for us for this course are, live code in-video-quizzes
where you can actually try out what we're talking about directly in a quiz.
So here's an example of that.
If you want to run the code you just hit the Run button and
it actually fires up Python on one of Coursera's remote machines and tries it.
And you can fool around with the method parameters for instance.
And rerun the code and explore the question that's been presented to you.
And you just continue with the video by hitting the Continue button.
These are some of the new features,
Coursera has added to the platform to help people learn data science.
And I hope you'll tell us what you think of the Jupyter notebooks, and
the new in-video quizzes.
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