Getting started with the IPython Notebook

A beginner's guide to using the IPython Notebook for a powerful programming experience.
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  • Lectures 5
  • Contents Video: 1 hour
  • Skill Level All Levels
  • Languages English
  • Includes Lifetime access
    30 day money back guarantee!
    Available on iOS and Android
    Certificate of Completion
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About This Course

Published 3/2014 English

Course Description

This course, the first of many on computational math, takes you on a beginner's tour through the IPython Notebook, a powerful tool for mixing code, models, text, plots, graphics and a lot more. We'll look at getting started with running a notebook server on the cloud, familiarizing oneself with the Notebook UI, as well as running code in it, taking advantage of IPython's rich magic functions, as well as its powerful display library.

The course includes about 5 videos, along with two quizzes, towards the end of the course. Further, since the course is about using the notebook, all course content consumers will get free accounts on MathHarbor for running notebook servers on the cloud - no strings attached.

The course should take approximately 3-4 hours to complete, depending on the time individual students might put into experimenting and playing with the notebook, while working on a module. The first section is about how the notebook works, and a tour through its user interface. The second section goes deeper, and talks about various magic functions available in the notebook, to do all sorts of things - timing code execution, running code in other interpreters, and so on - as well as a tour of the rich display system offered, which allows you to mix models, code, as well as rich media like plots, images, videos, audio and a lot more, in the notebook. The last video talks about the various things you can use the notebook for, as well as a short walkthrough of other math modeling tools and packages which can be used with the notebook, and which we intend to do future courses on.

If you're a programmer looking for a more intuitive environment to use, or a math nerd looking for a powerful medium to use for working on your models, this course should be a great jumping board. It'll help you quickly get started with the notebook, and let you rapidly move on to using it in a more serious manner.

What are the requirements?

  • While some understanding of basic Python is beneficial, it's not strictly necessary.
  • A working Internet connection - notebook servers shall run in the cloud.

What am I going to get from this course?

  • In this course, you will learn how the Notebook is a great tool for computational mathematics and statistics.
  • By the end of this course, you will be able to use the IPython Notebook with a great degree of comfort, and move on to more advanced topics such as using the notebook for linear algebra, machine learning, and a lot more.

What is the target audience?

  • Math students

What you get with this course?

Not for you? No problem.
30 day money back guarantee.

Forever yours.
Lifetime access.

Learn on the go.
Desktop, iOS and Android.

Get rewarded.
Certificate of completion.


Section 1: Introduction to IPython
Navigating around the Notebook UI
Section 2: IPython for power users
IPython Magic Functions
IPython Display System
7 questions

A short quiz on the IPython Magic functions lecture.

10 questions

A short quiz on the IPython Display System lecture.

Next Steps

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Instructor Biography

Rudraksh MK, Computational science professional

I'm a programmer who's been working on computational mathematics for much of his professional career. I've worked for companies such as IBM, Cvent, as well as news corporations, helping them analyze large-scale datasets using mathematical techniques. I also managed to start up three times, including a startup named MathHarbor - the idea is to build a cloud platform for numerical modeling, as well as a hub for math nerds, that would feature course content, discussions, and a lot more. I'm currently an evangelist with Wingify, a company that specializes in easy A/B testing, and I moonlight as a freelance computational science pro.

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