MLOps (Machine Learning Operations) Fundamentals

This course introduces participants to MLOps tools and best practices for deploying, evaluating, monitoring and operating production ML systems on Google Cloud. MLOps is a discipline focused on the deployment, testing, monitoring, and automation of ML systems in production. Machine Learning Engineering professionals use tools for continuous improvement and evaluation of deployed models. They work with (or can be) Data Scientists, who develop models, to enable velocity and rigor in deploying the best performing models.This course is primarily intended for the following participants: Data Scientists looking to quickly go from machine learning prototype to production to deliver business impact. Software Engineers looking to develop Machine Learning Engineering skills. ML Engineers who want to adopt Google Cloud for their ML production projects.

By enrolling in this course you agree to the Qwiklabs Terms of Service as set out in the FAQ and located at: https://qwiklabs.com/terms_of_service «<

• Identify and use core technologies required to support effective MLOps.

• 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.

Syllabus

Syllabus - What you will learn from this course
Week 1
Welcome to MLOps Fundamentals
Why and When do we need MLOps
Understanding the Main Kubernetes Components (Optional)
Week 2
Introduction to AI Platform Pipelines
Training, Tuning and Serving on AI Platform
Week 3
Kubeflow Pipelines on AI Platform
CI/CD for Kubeflow Pipelines on AI Platform
Summary

FAQ

When will I have access to the lectures and assignments?

Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:

What will I get if I subscribe to this Certificate?

When you enroll in the course, you get access to all of the courses in the Certificate, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.

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Last Updated: September 1, 2015

Reviews

It was good experience learning about the deployment process of ML application on GCP.

Great course to start for learning about MLOps. However, I hope there will have more videos to explain details on LABs.

The course is quite educational, yet the lab material can sometimes be confusing, especially for beginner users

course is good, but need more diagrams. Visual maps help wrapping concepts.