Course
digicode: VERTML
Vertex AI for Machine Learning Practitioners
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.
Duration
1 day
Price
850.–
exkl. 8.1% MWST
Course facts
- Understanding the key components of Vertex AI and how they work together to support your ML workflows
- Configuring and launching Vertex AI Custom Training and Hyperparameter Tuning Jobs to optimize model performance
- Organizing and versioning your models using Vertex AI Model Registry for easy access and tracking
- Configuring serving clusters and deploying models for online predictions with Vertex AI Endpoints
- Operationalizing and orchestrating end-to-end ML workflows with Vertex AI Pipelines for increased efficiency and scalability
- Configuring and setting up monitoring on deployed models
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.
1 Training, Tuning, and Deploying Models on Vertex AI
- Understand Containerized Training Applications
- Understand Vertex AI Custom Training and Tuning Jobs
- Understand how to track and version your trained models in Vertex AI Model Registry
- Understand Online Deployment with Vertex AI Endpoints
2 Orchestrating end-to-end Workflows with Vertex AI Pipelines
- Understand Kubeflow
- Understand pre-built and lightweight Python components
- Understand how to compile and execute pipelines on Vertex AI
3 Model Monitoring on Vertex AI
- Understand Feature Drift and Skew
- Understand Model Monitoring for models deployed to Vertex AI Endpoints
Machine Learning Engineers, Data Scientists
- Experience building and training custom ML models
- Familiarity with Docker