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Jupyter Notebook overview for all Python developers
Rating: 4.3 out of 5(222 ratings)
4,093 students

Jupyter Notebook overview for all Python developers

Introduction, Installation, walkthrough, Cell types, Modes, Magic Commands, Shortcuts, Publishing and Sharing
Created byMuhammad Omer
Last updated 12/2020
English

What you'll learn

  • Anaconda Installation
  • Jupyter Notebook Introduction
  • Jupyter Notebook Interface Walkthrough
  • Cell Types & Modes
  • Shortcuts & Magic commands
  • Publishing & Sharing Jupyter Notebook

Course content

1 section8 lectures31m total length
  • Introduction1:27
  • Course Overview0:57

    Explore how the Anakonda distribution installs Python, Jupiter Notebook, and Spider to write Python code, bundles hundreds of libraries, and includes a Gondar package manager.

  • Anaconda Installation2:59
  • Jupyter Notebook Interface Walkthrough9:09
  • Cell Types & Modes3:58
  • Shortcuts & Magic Commands7:41
  • Publishing & Sharing Jupyter notebook2:19
  • Jupyter Notebook Extentions2:57

Requirements

  • There are no requirements or prerequisites for this course

Description

This course is designed for all python developers who are eager to learn different features and functions of Jupyter notebook. This course will provide you complete knowledge and understanding of frequently used Jupyter notebook features. With the help of this course, your productivity and coding skills will reach the next level.

This course is for all the developers from beginners to advance, if you are a new Python developer or an experienced one, you will definitely learn something new in this course.

We'll start our course with an introduction to Anaconda and Jupyter notebook. After the introduction, Anaconda installation will be performed and I will show you how to start writing code in Jupyter Notebook. Our next step will be to go through Menu tabs and all options inside each tab to get familiar with their functions. We'll also look at Cell types, Modes, Shortcuts and Magic Commands. At the end we'll see how can we publish the Jupyter notebook file on a website or blog and how can we share it with other team members.

Who this course is for:

  • Python Developers
  • Data Scientists
  • Data Analysis