Cloud Data Security in 2025: Dangers, Safeguards, and More
March 13, 2025
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Instructor: Google Cloud Training
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Containerize ML workflows for reproducibility, reuse, and scalable training and inference on Google Cloud
Efficiently share, discover, and re-use ML features at scale while conducting reproducible ML experiments with Vertex AI Feature Store
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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.
Learners will get hands-on practice using Vertex AI Feature Store's streaming ingestion at the SDK layer.
Introduction to the course.
Vertex AI and its MLOps capabilities. Main challenges related to data and potential solutions to mitigate them.
3 videos
Key capabilities of Vertex AI Feature Store
4 videos1 app item
Summary of the course
We help millions of organizations empower their employees, serve their customers, and build what’s next for their businesses with innovative technology created in—and for—the cloud. Our products are engineered for security, reliability, and scalability, running the full stack from infrastructure to applications to devices and hardware. Our teams are dedicated to helping customers apply our technologies to create success.
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The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
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Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.
Financial aid available,