More than 50 videos to help you get started with the Jupyter Notebook
In Detail
Are you looking forward to write, execute, and comment your live code and formulae all under one roof? Or do you want an application that will let you forget your worries in scientific application development? If yes, then this Learning Path is just right for you! This Learning Path is a one-stop solution on Project Jupyter and will teach you everything you need to know to perform scientific computation with ease.
The Jupyter Notebook is an open-source web application and has support for more than 40 programming languages including those popular in data science such as Python, R, Julia, and Scala.
This Learning Path starts with a brief on the Jupyter Notebook and its installation in different environments. You will learn how to write code, mathematics, graphics, and output, all in a single document and in a web browser, using Jupyter. Next, you will see how to integrate the Jupyter system with different programming languages such as R, Python, JavaScript, and Julia. Moving ahead, you will master interactive widgets, namespaces, and working with Jupyter in multiuser mode. You will also see how to share your Notebook with colleagues. Finally, you will learn to access Big Data using Jupyter.
By the end of the Learning Path, you will be able to write code, mathematics, graphics, and output, all in a single document and web browser, using the Jupyter Notebook.
Prerequisites: Basic programming knowledge of Python, R, Julia, Scala, and Spark.
Resources: Code downloads and errata:
Jupyter Notebook for All – Part I
Jupyter Notebook for All – Part II
PATH PRODUCTS
This path navigates across the following products (in sequential order):
Jupyter Notebook for All – Part I (1h 23m)
Jupyter Notebook for All – Part II (1h 14m)