Udemy

Python in Containers

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  • 5,101 Students
  • Updated 6/2020
4.5
(545 Ratings)
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Course Information

Registration period
Year-round Recruitment
Course Level
Study Mode
Duration
23 Hour(s) 49 Minute(s)
Language
English
Taught by
Kris Celmer
Rating
4.5
(545 Ratings)
2 views

Course Overview

Python in Containers

All about Containers, Docker and Kubernetes for Python Engineers

Important Disclaimer: This course requires you to download Anaconda software from anaconda[.]com website, as well as Docker software from docker[.]com website. If you are a Udemy Business user, please check with your employer before downloading software.


Docker and Kubernetes are the Must-Have Skills for Python Enginner these days.

Whether your focus is in Machine Learning & Data Science, or you use Python as General Programming Language, you must understand Docker & Kubernetes. Both form a basis of Modern Cloud Native Applications built in Microservices Architecture.

Quotes from selected course reviews:

  • "It covers pretty much everything you'd expect from enterprise project" Abbi1680

  • "This course is absolute gold for data science and machine learning people because all Docker and Kubernetes courses out there focus on nothing but web applications. Thanks to the instructor for handling the concept of virtualization from a much needed different perspective. There are a lot of sources for learning ML and DS but skills taught in this course are what will make you stand out from the crowd." Mertkan Alacahan

  • "Spot on. Great depth yet very concise." Toby Patterson

  • "This is a deep deep deep dive in Docker with python. It is the complete course. Thanks for putting this together it is more than enough for what a need. I think watching the basic lectures and some selected topics I get what I needed and this became my docker reference guide if I need to solve a specific scenario. Thanks for putting this together. Highly recommend the course if you are a python developer." Pedro

In this Course you learn how to:


  • Develop and Explore Machine Learning & Data Science Jupyter Notebooks in Docker

  • Run Machine Learning Models in Production with Kubernetes and Docker Swarm

  • package your Python Code into Containers

  • publish your Containers in Image Registries

  • deploy Containers in Production

  • build highly modular Container-based Services in Micro-Services fashion

  • monitor and maintain Containerized Apps


You are going to become fluent and confident in using Docker Tools to create top-class Containers running your Python Code. You master Docker Runtime Tools like Compose and Swarm to run them. The Course also gives you sound knowledge and deep understanding of Kubernetes as the Application Platform. You gain confidence in Designing your Application to run on Kubernetes, as well as get deep knowledge of writing Kubernetes Object Declarations.

The Course is full of practical Exercises. There are over 40 GitHub Repositories full of Code Samples for the Course.

You can use the Course in two ways:

  1. If you use Python for Machine Learning & Data Science, go Top-Down: start with Section 7 to quickly gain practical Docker skills and use Sections 2 to 6 to dig deeper into specific Container Topics.

  2. If you want to use Python for Web Apps & Microservices, try Bottom-Up: use the Course in linear manner.

Start building Containers today!


Course Content

  • 7 section(s)
  • 115 lecture(s)
  • Section 1 Introduction
  • Section 2 Docker Deep Dive
  • Section 3 Build Container Images
  • Section 4 Ship Containers
  • Section 5 Run Containers in Docker
  • Section 6 Run Containers in Kubernetes
  • Section 7 Data Science & Machine Learning in Containers

What You’ll Learn

  • Build Container Image with Python Application in it
  • Ship Container Images to Docker Hub and other Container Image Registries
  • Run Jupyter Notebooks in Docker
  • Use Docker Desktop for Windows Pro and MacOS
  • Use Docker Toolbox for Windows Home
  • Use Docker Machine to create Virtual Machines with Docker Software
  • Master Dockerfile to Automate Container Image Build
  • Create Custom Container Images from Scratch
  • Use Python Official Images
  • Design Flask and Django Multi-Container Deployments
  • Automate Multi-Container Deployments with Docker Compose
  • Containerize TensorFlow Models into Microservices
  • Deploy Complex, Multi-Container Applications in Docker Swarm
  • Deploy Complex, Multi-Container Application in Kubernetes
  • Use Kubernetes with Minikube on a Development Host
  • Use Kubernetes in Public Cloud (using example of Google Kubernetes Engine)
  • Kubernetes Objects: Pods, Pod Controllers: ReplicaSet, Deployment, Job, CronJob, Services, Ingress, Persistent Volumes
  • Writing Kubernetes Object Template Files
  • Monitor and Manage Application in Kubernetes
  • Execute Containers with NVIDIA GPU Acceleration


Reviews

  • K
    Kevin Kinser
    5.0

    I'm from an IBM midrange computing background 40+ years & no little about developing cloud software, dabbled in Python a couple years ago & am supposed to learn how to manage software with GKE. but I felt I need to understand more basics around how to port software into a container, what is a container & how to progress in my learning. I signed up for a different GKE course first, but it was beyond my grasp within the first 20 min. This one so far seems spot on. so, thanks.

  • G
    Giulia C
    5.0

    Clear explanations

  • O
    Oscar Fernando Flores
    5.0

    Is a really complete course, might get a bit repetitive in certain instances but you will learn a lot by doing.

  • M
    Malinga Tembo
    4.5

    great high level introduction

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