ML Engineer - Monitor Model Inference

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ML Engineer - Monitor Model Inference

This course is part of AWS ML Engineer Associate Professional Certificate

Instructor: AWS Instructor

Included with Learn more

4 modules

Gain insight into a topic and learn the fundamentals.

Advanced level

Recommended experience

1 hour to complete

Flexible schedule

Learn at your own pace

4 modules

Gain insight into a topic and learn the fundamentals.

Advanced level

Recommended experience

1 hour to complete

Flexible schedule

Learn at your own pace

What you'll learn

Differentiate appropriate monitoring strategies for model performance, data quality, drift detection, agent behavior, and FM quality.
Describe how to monitor model performance and data quality in production using Amazon CloudWatch and Amazon Bedrock evaluations.
Explain how to detect anomalies or errors in data processing and model inference workflows.

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Build your Machine Learning expertise

This course is part of the AWS ML Engineer Associate Professional Certificate

When you enroll in this course, you'll also be enrolled in this Professional Certificate.

Learn new concepts from industry experts
Gain a foundational understanding of a subject or tool
Develop job-relevant skills with hands-on projects
Earn a shareable career certificate from Amazon Web Services

There are 4 modules in this course

This course covers part of the monitoring phase of the machine learning (ML) lifecycle. In this course, you will learn how to monitor a deployed model's performance and data quality so that you can continuously improve your ML solutions. This course covers detecting drift, establishing baselines, and publishing metrics, alarms, and notifications with Amazon CloudWatch and Amazon Simple Notification Service (Amazon SNS). You will learn to automate remediation with Amazon EventBridge and evaluate models with A/B testing. For generative AI, you will monitor agent performance and foundation model quality with Amazon Bedrock.

What's included

1 video4 readings

What's included

19 readings4 assignments

19 readingsTotal 19 minutes

What drift is1 minute
Four types of drift1 minute
How to monitor for each type of drift1 minute
Check your understanding1 minute
Capture, compare, alert1 minute
The monitoring loop in practice1 minute
Tuning when an alarm fires1 minute
Monitoring FM output quality with Amazon Bedrock evaluations1 minute
Check your understanding1 minute
Where problems surface1 minute
Detecting anomalies and errors1 minute
Automating the response1 minute
When humans must intervene, and the tools that help1 minute
Check your understanding1 minute
Why test in production1 minute
Production variants1 minute
When to use it, and what it buys you1 minute
Benefits1 minute
Check your understanding1 minute

4 assignmentsTotal 8 minutes

Knowledge Check2 minutes
Knowledge Check2 minutes
Knowledge Check2 minutes
Knowledge Check2 minutes

What's included

9 readings2 assignments

9 readingsTotal 9 minutes

Why agent monitoring is different1 minute
Observing agents with Amazon Bedrock AgentCore Observability1 minute
Behavioral metrics across sessions1 minute
Managing on the signals1 minute
Check your understanding1 minute
Two layers of FM monitoring1 minute
The operational layer: Amazon Bedrock metrics in CloudWatch1 minute
The quality layer: dimensions worth tracking1 minute
Check your understanding1 minute

2 assignmentsTotal 4 minutes

Knowledge Check2 minutes
Knowledge Check2 minutes

What's included

1 video5 readings1 assignment

Earn a career certificate

Add this credential to your LinkedIn profile, resume, or CV. Share it on social media and in your performance review.

Instructor

AWS Instructor

Amazon Web Services

233 Courses394,596 learners

Offered by

Amazon Web Services

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