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Development Data Science Docker

Docker Masterclass for Machine Learning and Data Science

Learn how to use Docker!
Rating: 4.4 out of 54.4 (357 ratings)
31,161 students
Created by Jordan Sauchuk, Ligency Team
Last updated 2/2021
English
English [Auto]
30-Day Money-Back Guarantee

What you'll learn

  • Use Docker in order to build containers to deploy applications.
  • Learn the intuition behind Docker and understand how it works.
  • Learn the ins and outs of working with Docker
  • Understand how to create and deploy Docker containers from scratch.
  • You will also learn about Docker Images, Docker Hub, security with Docker, and much more so that you can implement Docker as needed throughout your career.
Curated for the Udemy for Business collection

Course content

15 sections • 81 lectures • 4h 19m total length

  • Preview03:30

  • Study Tips For Success
    00:48
  • Your Shortcut To Becoming A Better Data Scientist
    02:03
  • Community Note
    00:19
  • Preview02:24
  • What is a Container?
    04:33
  • Useful Docker Info
    02:19
  • Installing Docker
    04:23
  • Installing Docker for Linux
    00:22
  • How Docker Is Useful For Data Science
    01:31
  • Installing Anaconda
    02:24
  • Why Anaconda?
    01:27
  • Virtual Environment
    03:26
  • Downloadables
    00:07

  • Download The Files
    00:07
  • Set Up A Simple Flask App
    02:51
  • Preview04:33
  • Requirements.txt
    03:09
  • Build A Docker Image and Container
    05:05
  • What Ports To Use?
    00:46
  • Common Docker Commands
    06:23
  • Docker Commands Cheatsheet
    00:06
  • Quiz
    5 questions

  • Sign Up
    01:43
  • Docker Hub Push Image
    05:22
  • Docker Hub Pull Image
    06:01
  • Updating Image
    02:19
  • Section Recap Notes
    00:44
  • Extra - Extending An Image
    05:38
  • Volumes
    03:23
  • Testing a Volume
    09:28
  • Section Quiz
    5 questions

  • Challenge Intro
    02:47
  • Solution Files
    00:07
  • Challenge Solution
    06:34
  • Quick Notes!
    00:28

  • Obtain The Files Here
    00:13
  • Git Tips & Tricks
    00:46
  • NGINX & Automation
    01:35
  • NGINX & Automation P1
    05:09
  • NGINX & Automation P2
    04:31
  • NGINX & Automation P3
    05:29
  • NGINX & Automation P4
    01:44
  • NGINX & Automation P5
    09:04
  • NGINX & Automation P6
    04:06

  • File Challenge Introduction & Github Classroom Link
    00:33
  • File Challenge Part One
    03:04
  • File Challenge Solution
    08:10

  • Obtain The Docker Compose Resources Here
    00:12
  • Docker Compose
    03:29
  • Docker Compose - Jupyter
    06:30
  • Docker Compose Challenge
    04:05
  • Docker Compose Challenge - Part 1
    06:20
  • Docker Compose Challenge - Part 2
    03:06
  • Compose Building Cheatsheet
    01:05
  • Docker Extra - Simple Jupyter Command
    03:28

  • Swarm Section Files
    00:05
  • Swarm Intro
    04:29
  • Swarm Deploy
    05:48
  • Swarm Tips
    00:48

  • AWS EC2 Setup Tips
    00:18
  • AWS Part One
    02:31
  • AWS Part Two
    05:32
  • AWS Part Three
    06:06
  • AWS Part Four
    03:20
  • AWS Extras
    03:07

Requirements

  • The requirements for this course is simple. We will be using Docker desktop (available on Windows, Mac, Linux) and other Docker services that we will walk through the sign up process, or related information for. We will also be using Python, and any related libraries. You can use any IDE that you would like, but we will use Spyder as an example in the course when needing to write our code, and the terminal or shell/prompt.

Description

Every data scientist is aware that, sometime or another, they'll need to show off their progress and results. And there couldn't be a bigger fear than not having your algorithm run on another computer for reasons you can't define.


Enter Docker Masterclass for Machine Learning and Data Science.  Led by Docker evangelist and Cybersecurity expert Jordan Sauchuk, this course is designed to get you up and running with Docker, so you will always be prepared to ship your content no matter the situation.


Your Docker path will cover the following steps:

  • A Comprehensive Introduction to Docker

  • Getting the Docker basics down

  • Using Dockerhub

  • Docker Challenges


Embedded in each section you'll not only find great video lessons, but also enriching articles and quizzes designed to take you to Docker heaven!


So, are you ready to become an excellent data scientist? Enroll now!


See you in the classroom.


Who this course is for:

  • Anyone interested in advancing their careers and obtaining a skill that not only is highly relevant now, but will only continue to grow.

Instructors

Jordan Sauchuk
Senior AI Advisor & Cybersecurity Engineer
Jordan Sauchuk
  • 4.4 Instructor Rating
  • 652 Reviews
  • 43,133 Students
  • 2 Courses

I'm a Senior AI Advisor, AI & Cybersecurity Engineer and also the CEO of Global Pioneers. My goal is to help provide my experiences and expertise that has been obtained through extensive research, many late nights, and cups of coffee.

I have been fortunate enough to work on a range of challenging projects worldwide and I have extensive experience specializing in technologies such as Python, R, JavaScript, C++, PHP, Tensorflow, Pytorch, Scikit-Learn, Keras, ReactJS, NodeJS, SQL, Plotly, Tesseract, Seaborn, and much more.

Recently, I have launched the Threat Intelligence Group as a means of providing cybersecurity awareness, integrating AI into the security domain, and also providing consulting services.

For more information please feel free to reach out to me on LinkedIn and Twitter. 

Ligency Team
Helping Data Scientists Succeed
Ligency Team
  • 4.5 Instructor Rating
  • 469,133 Reviews
  • 1,685,932 Students
  • 109 Courses

Hi there,

We are the Ligency PR and Marketing team. You will be hearing from us when new courses are released, when we publish new podcasts, blogs, share cheatsheets and more!

We are here to help you stay on the cutting edge of Data Science and Technology.

See you in class,

Sincerely,

The Real People at Ligency

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