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Managing ML Features in Vertex AI
Master MLOps with Vertex AI: Learn to manage features, containerize ML workflows, and scale operations on Google Cloud.
Course Cost
₹ 2,699
Intermediate
Skill Level
2 Hours
Self-paced Video lessons
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.
English
English
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
Implement best practices for sharing, discovering, and reusing ML features
Develop skills to conduct reproducible ML experiments at scale
Skills you'll gain
This course includes:
33 Minutes PreRecorded video
1 hands-on lab
Access on Mobile, Tablet, Desktop
FullTime access
Shareable certificate
Get a Completion Certificate
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Get a Completion Certificate
Share your certificate with prospective employers and your professional network on LinkedIn.
CREATED BY
PROVIDED BY
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Top companies provide this course to enhance their employees' skills, ensuring they excel in handling complex projects and drive organizational success.
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
Fee Structure
Payment options
Financial Aid
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Faculties
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Frequently asked Questions
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