MLOps (Machine Learning Operations) Fundamentals
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Course overview
- Provider
- Coursera
- Course type
- Free online course
- Level
- Intermediate
- Deadline
- Flexible
- Duration
- 16 hours
- Certificate
- Paid Certificate Available
- Course author
- Google Cloud Training
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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.
Description
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.
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