About this Course

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Shareable Certificate
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Intermediate Level

Approx. 16 hours to complete
English

What you will learn

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

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

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

  • Implement reliable and repeatable training and inference workflows.

Flexible deadlines
Reset deadlines in accordance to your schedule.
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Intermediate Level

Approx. 16 hours to complete
English

Instructor

Offered by

Placeholder

Google Cloud

Syllabus - What you will learn from this course

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Week
1

Week 1

13 minutes to complete

Welcome to MLOps Fundamentals

13 minutes to complete
1 video (Total 1 min), 2 readings
25 minutes to complete

Why and When do we need MLOps

25 minutes to complete
3 videos (Total 15 min)
7 hours to complete

Understanding the Main Kubernetes Components (Optional)

7 hours to complete
25 videos (Total 93 min)
Week
2

Week 2

2 hours to complete

Introduction to AI Platform Pipelines

2 hours to complete
7 videos (Total 46 min)
3 hours to complete

Training, Tuning and Serving on AI Platform

3 hours to complete
8 videos (Total 82 min)
Week
3

Week 3

2 hours to complete

Kubeflow Pipelines on AI Platform

2 hours to complete
8 videos (Total 71 min)
1 hour to complete

CI/CD for Kubeflow Pipelines on AI Platform

1 hour to complete
5 videos (Total 13 min)
2 minutes to complete

Summary

2 minutes to complete
1 video (Total 2 min)

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About the Preparing for Google Cloud Certification: Machine Learning Engineer Professional Certificate

Preparing for Google Cloud Certification: Machine Learning Engineer

Frequently Asked Questions

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