Learning Path

Jupyter: Learn Jupyter Skills from Scratch

Instructor Carol Quadros
Time to complete: 4h 15m

Published byPackt Publishing

CreatedNovember 2017

Conquer the world of interactive computing with Jupyter

In Detail

Jupyter Notebook is a web-based environment that enables interactive computing in notebook documents. It allows you to create and share documents that contain live code, equations, visualizations, and explanatory text. It is extensively used in domains such as data cleaning and transformation, numerical simulation, statistical modeling, machine learning, and much more. It supports a number of languages via plugins ("kernels"), such as Python, Ruby, Haskell, R, Scala and Julia. So, if you're interested to learn interactive computing with Jupyter, then go for this Learning Path.

Packt’s Video Learning Paths are a series of individual video products put together in a logical and stepwise manner such that each video builds on the skills learned in the video before it.

The highlights of this Learning Path are:

  • Implement programming languages such as R, Python, Julia, and JavaScript with Jupyter Notebook
  • Access big data in Jupyter

Let’s take a quick look at your learning journey. This Learning Path starts with a detailed overview of the Jupyter Notebook system and its installation in different environments. You’ll learn to integrate the Jupyter system with different programming languages such as R, Python, JavaScript, and Julia You’ll then explore the various versions and packages that are compatible with the Notebook system. Moving ahead, you'll master interactive widgets, namespaces, and working with Jupyter in multiuser mode. The Learning Path will walk you through the core modules and standard capabilities of the console, client, and notebook server. Finally, you will be able to build dashboards in a Jupyter notebook to report back information about the project and the status of various Jupyter components.

Towards the end of this Learning Path, you’ll have an in-depth knowledge on Jupyter Notebook and know how to integrate different programming languages such as R, Python, Julia, and JavaScript with it.

Prerequisites: Basic understanding on programming languages (preferably JavaScript, Python, R, Julia, Scala, and Spark) is needed.

Resources: Code downloads and errata:


This path navigates across the following products (in sequential order):