- Course type
- Paid course
- 24 hours
- 115 lessons
- Available on completion
- Course author
- Kris Celmer
- 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
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" [email protected]
"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:
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.
If you want to use Python for Web Apps & Microservices, try Bottom-Up: use the Course in linear manner.
Start building Containers today!