edX
MOOC / Non-credit
0
Machine Learning Operations (MLOps): Getting Started
About this course
In Machine Learning Operations (MLOps): Getting Started, you will build a foundation in the tools, practices, and Google Cloud architectures used to deploy, monitor, and manage machine learning systems in production environments.
C
59/100
CourseAsk score
- What the provider tells you
- 23/45
- Who stands behind it
- 20/35
- How complete the listing is
- 16/20
Scores how much the provider publishes and who stands behind it — not how well it is taught.
What you'll learn
- Identify and use key MLOps tools for model deployment and monitoring
- Design and implement ML pipelines on Google Cloud
- Containerize models with Docker and orchestrate them with Kubernetes
- Apply CI/CD principles to automate ML workflow updates
Course objectives
- Explain the components of an MLOps stack
- Build a reproducible deployment pipeline for a machine‑learning model
- Set up monitoring and alerting for production models on Google Cloud
Machine Learning
Cloud Computing
DevOps
#google cloud
#machine learning
#mlops
#cloud architecture
#deployment
#monitoring
#devops
#production systems
#system management
#kubernetes
#docker
#model deployment
#model monitoring
#ci/cd
#data pipelines
#cloud ai platform
#logging
$29.00
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