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Overview
This advanced course covers the infrastructure and operational aspects required for deploying and scaling machine learning models in production. Learners will explore containerization, orchestration with Kubernetes, continuous integration/continuous deployment (CI/CD), monitoring, and model management. Emphasis is placed on reliability, scalability, and automation best practices. By the end, participants will be equipped to build robust ML infrastructure pipelines that support real-world AI applications at scale.
Syllabus
- Advanced ML: ML Infrastructure
- Vertex AI: Qwik Start
- TFX on Google Cloud Vertex AI Pipelines
- Autoscaling TensorFlow Model Deployments with TF Serving and Kubernetes
- Implementing Canary Releases of TensorFlow Model Deployments with Kubernetes and Cloud Service Mesh
- Your Next Steps
- Course Badge
Instructor
cloudskillsboost.google
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