Containerization ★★★ Expert Level
This two-day course will provide a way of thinking and best practices for containerization. Containers provide a consistent environment for your AI applications from your local machine to a server on the other side of the world to the laptop of your colleague. Machine learning models will have a higher reproducibility.
Course Badge
2 days
Recommended Level
Upcoming courses
Currently there are no scheduled dates for this course. To be notified about upcoming dates, please choose "Reserve a seat".
Select tickets
We're sorry, but all tickets sales have ended because the event is expired.

*If you are a group of 5 or more, we are happy to accommodate a date for the training that suits you best. If so, please choose the "Reserve a seat" option.


About the course

Creating an environment in which software tasks such as building, running or testing remain predictable can be a challenging task. There are multiple boundary conditions that might change such as the operating system the application is running on or the available packages for the application to consume to name a few. This two day course will start at the basics of what containers are and how they differ from traditional alternative techniques. You will learn how to write a file that can create an image (one of the building blocks of containers) where you can define the dependencies of your application, use your own source code and define the environment. Additionally, you will learn creating configurations where multiple containers work together such as a backend and corresponding database.  

Why this is for you

Do you have inconsistent test results when testing your software. Don’t you know anymore what dependencies you application relies on? Do you want to easily share your applications to colleagues? This course will teach you how to resolve all these problems.  

For whom

This course is designed for AI Engineers, Data Engineers, and Data Scientists who have experience with building AI applications and operationalizing models. Expert programming in Python is also required as a prerequisite.  

What you’ll learn

  1. Writing build files for containers
  2. Running build images to start containers
  3. Running multiple containers as a single service
Theory and practical use All trainings in the GAIn portfolio combine high-quality standardized training material with theory sessions from experts and hands-on experience where you directly apply the material to real-life cases. Each training is developed by top of the field practitioners which means they are full of industry examples along with practical challenges and know-how, fueling the interactive discussions during training. We believe this multi-level approach creates the ideal learning environment for participants to thrive.