Managing ML Features in Vertex AI
Master MLOps with Vertex AI: Learn to manage features, containerize ML workflows, and scale operations on Google Cloud.
Master MLOps with Vertex AI: Learn to manage features, containerize ML workflows, and scale operations on Google Cloud.
This course introduces MLOps tools and best practices for deploying, evaluating, monitoring, and operating production ML systems on Google Cloud. Focusing on Vertex AI Feature Store, participants learn to efficiently share, discover, and reuse ML features at scale while conducting reproducible ML experiments. The course covers containerization of ML workflows for reproducibility, reuse, and scalable training and inference. Through hands-on practice with Vertex AI Feature Store's streaming ingestion at the SDK layer, learners gain practical experience in managing features for MLOps workflows.
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What you'll learn
Understand the role of MLOps in managing production ML systems
Explore Vertex AI and its capabilities in the MLOps workflow
Master the use of Vertex AI Feature Store for efficient feature management
Learn to containerize ML workflows for reproducibility and scalability
Gain hands-on experience with streaming ingestion in Vertex AI Feature Store
Understand the data model in Vertex AI Feature Store
Skills you'll gain
This course includes:
33 Minutes PreRecorded video
1 hands-on lab
Access on Mobile, Tablet, Desktop
FullTime access
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There are 4 modules in this course
This course provides a comprehensive introduction to Machine Learning Operations (MLOps) using Google Cloud's Vertex AI platform, with a specific focus on feature management. The curriculum is structured into four modules, covering the fundamentals of MLOps, Vertex AI capabilities, and in-depth exploration of Vertex AI Feature Store. Learners will understand the challenges related to data in ML workflows and learn how to mitigate them using Vertex AI tools. The course emphasizes hands-on experience, including a lab on Feature Store's streaming ingestion SDK. By the end of the course, participants will be equipped with the knowledge and skills to effectively manage features in MLOps workflows, containerize ML processes for scalability, and implement best practices for production ML systems on Google Cloud.
Welcome to the Machine Learning Operations (MLOps) with Vertex AI: Manage Features
Module 1 · 2 Minutes to complete
Introduction to Vertex AI Feature Store
Module 2 · 9 Minutes to complete
Machine Learning Operations (MLOps) with Vertex AI: Manage Features An in depth look
Module 3 · 60 Minutes to complete
Summary
Module 4 · 2 Minutes to complete
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Instructor
Empowering Businesses with Expert Training from Google Cloud
The Google Cloud Training team is tasked with developing, delivering, and evaluating training programs that enable our enterprise customers and partners to effectively utilize our products and solutions. Google Cloud empowers millions of organizations to enhance employee capabilities, improve customer service, and innovate for the future using cutting-edge technology built specifically for the cloud. Our products are designed with a focus on security, reliability, and scalability, covering everything from infrastructure to applications, devices, and hardware. Our dedicated teams are committed to helping customers successfully leverage our technologies to drive their success.
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