Jupyter Notebook is a web application where you can text, code, create and share your live documents, etc. and because of the mixed variety of the rich text elements, codes, other functionalities, this web application is an ideal one for a data science enthusiast. In this article, we list down five resources where you can learn the basics, features and many more of this prominent notebook.
Opensource Tools For Data Science By Coursera
This is a beginner level course offered in Coursera where you will learn about the various data science tools and their features. You will learn about the uses of tools, the suitable programming language that they can execute, limitations and many more. It is basically a part of the 9 courses provided by IBM Data Science Professional Certificate Specialisation. The course shed lights into basics of Jupyter Notebook, its features, etc. along with a 30 min practice session.
The enrolling will start from 27th Feb 2019, you can also audit this course for free where you can access the course materials without graded assignments or the ability to earn a certificate.
Jupyter Notebook Courses By Udemy
There are several courses offered in Jupyter Notebook by Udemy. Two such courses are Learning Path: Jupyter: Interactive Computing with Jupyter and the other is the Jupyter in Depth. The first one dives deep to enhance your expertise into interactive computing, sharing and integrating using Jupyter. Here you can learn about the basics like installation, run, implement programming languages such as R, Python, Julia, etc. and also you will learn to use the interactive widgets to manipulate and visualise data in real time. The second course will help you learn to configure Jupyter, Console, Client and core modules, how to access the Logger and use widgets, building data dashboards, monitoring application directories, etc.
Getting Started with Jupyter Notebook And Python By Pluralsight
This is a beginner level course provided with a duration of 2h 14 min. The course will help you learn how to install, create and managing Groups of cells, shell commands and special objects, styling cell output in the notebook. You will also learn the applications to data analysis, visualisations, extending the Notebook User Interface, etc. and by the end of this course, you will have the skills necessary to assemble Jupyter notebooks.
Jupyter Notebook Tutorial: The Definitive Guide By Datacamp
This tutorial on Jupyter Notebook will help to learn install, run, and the basic overview of the Notebook. You will learn to run the Notebook with Anaconda Python Distribution, Pip, in Docker containers, etc.along with sharing your Jupyter Notebooks.
This tutorial will guide you through the process of installing and the basic functionality of the Jupyter Notebook. You will get to learn how to set up and create a new Notebook, working on it including the exporting methods.
Resources From Leading Tech Companies
The articles will help you to learn how to set up a Jupyter notebook server on Amazon EC2 using a web browser and running the Jupyter notebook. The topic of setting up notebook includes configuring the notebook on deep learning AMI, custom SSL, and server configuration, starting the notebook server, configure the client to connect to the Jupyter server, etc. After setting up the notebook server, the next article will help you to learn to navigate the installed tutorials, switching environments, etc.
This article describes how to set up the Intel Distribution for Python-development environment. There are two typical development environments are described in this article, they are Jupyter notebook and Pycharm. Here, you will learn to install Anaconda, run commands in Jupyter for IDP2 and IDP3, etc.
Video Tutorials On YouTube
In this Python Tutorial, we will be learning how to install, setup, and use Jupyter Notebooks. You will also learn to create and share documents that contain live code, equations, visualizations, and markdown text.
This tutorial is a total of 10 videos where you can learn the basics as well as other functionalities of Jupyter Notebook such as markdown and latex, plotting charts, learning widgets and much more.
This PDF includes a bunch of useful notes for using the notebook starting from the basics like the introduction, creating, opening notebooks, understanding the user interface components, changelog, configuration overview, security in notebook server, contributing, and many more.
This pdf includes the workflow of the notebook and shows how to text, code and use kernels as well as conversion and embedding methods in the notebook.