Deploy all the Things!

Most data science platforms have about a million moving pieces. Installing them to your own computer is not even always possible AND a major pain when you need to move to production.

In this (FREE!) course I will show you how to find Docker images out in the wild, customize them for your own nefarious purposes, wire them together with Docker Compose, and finally scale for world domination with Docker Swarm!

Check out the course in action with the Apache Airflow template in the video below.

Free Docker for Data Scientists Course

Build, deploy and scale ALL THE THINGS!

Here's What We'll Cover

This course will teach you the nitty gritty of getting your Python or R application off of your computer and onto a Docker container. Then you'll learn how to string together your application with databases such as MySQL, Mongo, PostgreSQL, and  Message Queues, and other applications.

When you learn these base skill sets you can take your application and deploy it anywhere, including a remote server or any cloud provider such as AWS or GCP.

Then, when you understand how to string your applications together you can scale to have multiple instances of a single application behind a load balancer with Docker Swarm and Traefik. 

Docker Foundations

  1. What is Docker?
  2. Why should you use Docker
  3. Where to find ready made Docker Images
  4. The Dockerfile
  5. Build a custom docker image
  6. Run an interactive shell
  7. And more!

Leveraging Docker Compose

  1. Dockerfile to Docker Compose Mapping
  2. Getting started with docker compose
  3. Bring up an interactive shell with Docker Compose
  4. Add an image from DockerHub to your Docker Compose services
  5. Logging in docker compose
  6. Getting your services to talk to one another - Python + MySQL Example
  7. Get your services to talk to one another - Python + MongoDB Example
  8. Upload an image from Docker Compose to, Dockerhub, etc.

Docker Swarm

  1. Docker Swarm Intro
  2. Create a Docker Swarm Cluster from Scratch
  3. Deploy a stack with Nginx and HaProxy
  4. Deploy a minimal Flask Application
  5. Deploy a Celery Job Queue with Traefik and Swarm
  6. Use Portainer to Uplevel your Awesomeness!

Deploy your Docker Apps with Kubernetes

  1. Kubernetes Hello World
  2. Kompose your NGINX service
  3. Deploy your Flask App with Kubernetes using kompose and kubectl
  4. Make your URLs pretty with an Ingress

Here's a Preview

Check out a preview of the Build Apache Airflow with Docker Lesson. 


Free Resource Library

When sign up for this course you also get access to my Free Resource library and Docker for Data Scientists course. 

In the library there are project templates for Python, R, Flask, Apache Airflow, Celery Job Queue, and more advanced templates when you need to scale out your deployments.

Sign Up

About the Instructor

Hi! I'm Jillian. I've been working in Bioinformatics on the Infrastructure side of things for the last 10 years. The first half of that was spent building and deploying oodles of applications for High Performance Computing Clusters. Then there was a lot of building applications with Conda. Now I build and deploy data science applications on AWS such as RShiny, Dash, Dask, and Flask, and clusters such as HPC, AWS Batch, and Kubernetes.