Course details

DevOps for Data Scientists: Containers for Data Science

DevOps for Data Scientists: Containers for Data Science


Overview/Description
Expected Duration
Lesson Objectives
Course Number
Expertise Level



Overview/Description

In this 16-video course, explore the use of containers in deploying data science solutions by using Docker with R, Python, Jupyter, and Anaconda. Begin with an introduction to containers and their use for deployment and data science. Then examine approaches to infrastructure as code for data deployment, and concepts behind Ansible and Vagrant approaches to data science deployment. Explore the main features of provisioning tools used in data science. You will learn how to use Docker to build data models, then use it to perform model testing for deployment, to manage R deployments, and for a PostgreSQL deployment. Also, discover how to use Docker for persistent volumes. Next, learners look at using Jupyter Docker Stacks to get up and running with Jupyter and using the Anaconda Distribution to run a Jupyter Notebook. This leads into using Jupyter Notebooks with a Cookiecutter data science project. Then learn about using Docker Compose with PostgreSQL and Jupyter Notebook, and using a container deployment for Jupyter Notebooks with R. The concluding exercise involves deploying Jupyter.



Expected Duration (hours)
1.0

Lesson Objectives

DevOps for Data Scientists: Containers for Data Science

  • discover the key concepts covered in this course
  • describe the use of containers for data science
  • describe approaches to infrastructure as code for data deployment
  • describe Ansible and Vagrant approaches to data science deployment
  • describe provisioning tools used in data science
  • use Docker to build a data model
  • use Docker to perform model testing for deployment
  • use Docker to manage R deployments
  • use Docker for a PostgreSQL deployment
  • create a Docker persistent volume
  • use Jupyter Docker Stacks to get up and running with Jupyter
  • use the Anaconda distribution to run a Jupyter Notebook
  • use Jupyter Notebooks with a Cookiecutter data science project
  • use Docker Compose with PostgreSQL and Jupyter Notebooks
  • use a container deployment for Jupyter Notebooks with R
  • use a container strategy for a Jupyter deployment
  • Course Number:
    it_dsdods_04_enus

    Expertise Level
    Intermediate