Artificial Intelligence
Cloud Computing
AI/MLOps Foundation
Overview
AI/MLOps Foundation teaches attendees how to build enterprise-grade machine learning platforms and infrastructure, covering essential topics, including the principles of MLOps architecture, deployment strategies, and technologies for machine learning processes.
Attendees gain hands-on experience with Seldon Core, Kubeflow and Ray.
Duration
2 Days
Who Should Take This Course
Audience
AI/MLOps, DevOps and DataOps engineers; Data Scientists/Engineers, Developers, IT and QA Staff, Technical Managers.
Prerequisites
Participants should have some programming skills (preferably in Python), familiarity with Linux and basic command-line skills.
Why You Should Take This Course
Upon completing AI/MLOps Foundation, participants will be able to:
- Understand the fundamental concepts of incorporating machine learning into production processes
- Gain hands-on experience with frameworks for training, deploying, serving and monitoring machine learning models
- Learn how to adopt a CI/CD approach to machine learning workflows
- Become familiar with the architecture of machine learning processes and services
- Gain exposure to prevailing technologies in the rapidly developing space of MLOps
- Learn how to implement scalable solutions to support machine learning workflows
- Deploy machine learning models using various strategies, including on-premises and cloud deployment