Train and Deploy Machine Learning Models with Vertex AI
This instructor led one day course provides practical, hands on experience with Google Vertex AI for engineers and data scientists who want to build, train, deploy, and monitor custom machine learning models.
Why get trained: Learn how to use Vertex AI Custom Training, Hyperparameter Tuning, Model Registry, Endpoints, Pipelines, and model monitoring to optimize and operationalize ML workflows.
Why it matters: Vertex AI helps organizations streamline machine learning workflows, improve model performance, and efficiently deploy and monitor models at scale.
Who should attend: Machine Learning Engineers, Data Scientists, and professionals familiar with machine learning models.
Gain practical skills to manage end to end machine learning workflows with Vertex AI and improve the efficiency and scalability of your ML projects. HRD Corp Claimable.
Overview
This instructor-led one-day course is designed for engineers and data scientists familiar with machine learning models who want to become proficient in using Vertex AI for custom model workflows.
This practical, hands-on course will provide you with a deep dive into the core functionalities of Vertex AI, enabling you to effectively leverage its tools and capabilities for your ML projects.
Skills Covered
By the end of the course, learners will be able to:
- Understand the key components of Vertex AI and how they work together to support your ML workflows.
- Configure and launch Vertex AI Custom Training and Hyperparameter Tuning Jobs to optimize model performance.
- Organize and version your models using Vertex AI Model Registry for easy access and tracking.
- Configure serving clusters and deploy models for online predictions with Vertex AI Endpoints.
- Operationalize and orchestrate end-to-end ML workflows with Vertex AI Pipelines for increased efficiency and scalability.
- Configure and set up monitoring on deployed models.
Prerequisites
- Experience building and training custom ML models.
- Familiar with Docker.
Target Audience
Machine Learning, Engineers, Data Scientists
Dates & Locations
January 18, 2027 - January 18, 2027
January 18, 2027 - January 18, 2027
April 30, 2027 - April 30, 2027
April 30, 2027 - April 30, 2027
July 26, 2027 - July 26, 2027
July 26, 2027 - July 26, 2027
October 29, 2027 - October 29, 2027
October 29, 2027 - October 29, 2027
Exam & Certification
Note:Â There is no exam directly associated with this course. However, Google Cloud offers an extensive portfolio of industry-recognized certifications that can help you stand out as a tech professional in 2025 and beyond. Obtaining a Google Cloud certified credential is one of the most effective ways to validate your skills and accelerate your career.
With our expert-led training, you’ll be prepared to:
- Master in-demand capabilities across Cloud, Data & AI, and Cybersecurity — areas driving global digital transformation.
- Prove your expertise with a globally respected credential recognized by employers worldwide.
- Advance your career by enhancing your credibility, increasing your earning potential, and opening doors to new opportunities.
Explore our full range of Google Cloud certifications and start building the skills that matter today.
Training & Certification Guide
Frequently Asked Questions
Speak to a Training Consultant
All courses are HRD Claimable.
Get in touch with our team via the form or WhatsApp us on +6011-5119 6631
