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Jupyter Notebook Server with AWS EC2 and AWS VPC

  • Build a Cloud Server to run your Jupyter Notebooks
  • Free tutorial
  • Rating: 4.7 out of 54.7 (227 ratings)
  • 20,984 students
  • 1hr 21min of on-demand video
  • Created by Justin Mitchel
  • English

What you’ll learn

  • Launching a live Jupyter Server on an AWS EC2 instance
  • Building a custom AWS VPC from Scratch
  • Setup an Ubuntu server to run a Jupyter Notebook
  • Securely run Jupyter in the Cloud

Requirements

  • Some Python and/or Command Line experience
  • Interest in cloud computing

Description

One of the challenges of writing programs is having the ability to pick up where you left off. Jupyter Notebooks do this very well because they allow for interactive running of code, keep results in memory, and empower data scientists and programmers everywhere to build interesting things.

Jupyter is an interactive notebook which allows you to run code right inside the notebook. This is good for many reasons:

  1. Notebooks, like actual books, can be shared easily
  2. While running a notebook, the “state”, is remembered: run some code and it’ remembers the results of that code
  3. Notebooks easily layout the process of a given program into a story-like progression that anyone can pick up and use.

If you’ve never worked with Jupyter Notebooks before, I highly recommend that you do.

This course is about bringing Jupyter Notebooks to the AWS Cloud. We’ll be preparing a AWS Virtual Private Cloud, Subnets, Internet Gateways, Route Tables, and more so that we can provision AWS EC2 instances securely and effectively.

Read Also -->   Computational and Complexity Theory

Once we have an EC2 instance, we can configure nginx, supervisor, and Jupyter so we can run it automatically on a public IP address… check out the first video for more on this.

Who this course is for:

  • Data Scientists looking to control their Jupyter notebook experience
  • Data Scientists looking for “pick up where you left off” usage of a jupyter notebook
  • Pythonistas looking to get into Data Science.

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Course content

4 sections • 14 lectures • 1h 20m total lengthCollapse all sections

Introduction2 lectures • 7min

  • What we’re going to build05:20
  • Getting Started01:43

AWS VPC5 lectures • 21min

  • A first step02:16
  • Your new VPC04:49
  • Create a Public Subnet05:24
  • Our First EC2 Instance04:41
  • An Internet Connect VPC04:02

AWS EC2 & Jupyter Configuration5 lectures • 34min

  • Provision the EC2 Instance09:06
  • SSH into EC2 Instance04:43
  • Jupyter Configuration07:48
  • Nginx Configuration07:34
  • Setup Supervisor04:47

Final Steps2 lectures • 18min

  • Elastic IP08:25
  • Reusability with AMI and Wrap up09:57

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