Docker-izing Data Science Applications by Daniel Whitenack

Docker-izing Data Science Applications

Easily deploy your data science apps anywhere!

Overview

In this course, we will learn how to put your data science applications in Docker images and run those as containers on any infrastructure. These skills will help you maintain reproducibility and increase efficiency as you deploy your applications, and they will help you standardize your code to better fit into modern infrastructures, CI/CD tools, and DevOps practices.

We will cover:
  1. Why Docker, gettings started with Docker
  2. Docker-izing model training
  3. Docker-izing inference, services
  4. Managing and scaling Docker-ized data science apps

What's included?

Contents

Level up your data, AI/ML, and infra skills!

Data Dan (Daniel Whitenack) is a PhD-trained data scientist with over ten years of experience developing ML/AI applications in industry. Through his courses and workshops, Dan has helped hundreds of students learn the theory and practice of machine learning, AI, data engineering, and analytics.