Artificial Intelligence & Data Science
Star icon
Most Popular
Hands on Training icon
Hands On Training
Star icon
Hands on Training icon

MLOps (Machine Learning Operations) Fundamentals

Course Cover
compare button icon

Course Features

icon

Duration

16 hours

icon

Delivery Method

Online

icon

Available on

Limited Access

icon

Accessibility

Desktop, Laptop

icon

Language

English

icon

Subtitles

English

icon

Level

Intermediate

icon

Teaching Type

Self Paced

icon

Video Content

16 hours

Course Description

This course introduces participants the MLOps tools, best practices, and MLOps methods for deploying, evaluating and monitoring production ML systems on Google Cloud. MLOps refers to the testing, monitoring and automation of ML systems in manufacturing. Machine Learning Engineering professionals employ tools to continuously improve and evaluate the models they have deployed. They can work with Data Scientists (or could be), who create models to allow speed and rigor when deploying the most performant models.

This course is intended for Data Scientists who want to rapidly move from prototype to production and deliver business impact. Software Engineers who want to learn Machine Learning Engineering skills. ML Engineers looking to adopt Google Cloud in their ML production projects.

Course Overview

projects-img

International Faculty

projects-img

Post Course Interactions

projects-img

Instructor-Moderated Discussions

Skills You Will Gain

What You Will Learn

Adopt the best CI/CD practices in the context of ML systems.

Configure and provision Google Cloud architectures for reliable and effective MLOps environments.

Implement reliable and repeatable training and inference workflows.

Identify and use core technologies required to support effective MLOps.

Course Accreditations

Course Cover