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.
Language
English
Duration
2 days
Time
9:00-17:00
Certification
Yes
Lunch
Included
Recommended
Level
Expert
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Containerization
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
- Writing build files for containers
- Running build images to start containers
- Running multiple containers as a single service