Step into the world of Vertex AI with a course built for seasoned Data Scientists and Machine Learning practitioners ready to level up their workflow.
Whether you're already developing machine learning models or just starting to explore custom pipelines, this hands-on session will equip you with the skills to navigate Vertex AI's powerful suite of tools.
Expect practical insights, real-world applications, and the confidence to scale your projects using Google Cloud’s robust Machine Learning infrastructure.
Our Vertex AI for Machine Learning Practitioners course is offered as a private training session that can be delivered virtually or at a location of your choice in the UK.
Course overview
Who should attend:
This course is suitable for:
- Machine Learning engineers
- Data scientists
What you'll learn:
By the end of this course, you 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 optimise model performance
- Organise 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
- Operationalise 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
To get the most out of this course, you should have completed our Application Development with LLMs on Google Cloud course or have equivalent knowledge.
Course agenda
- Understand containerised 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
- Understand Kubeow
- Understand pre-built and lightweight Python components
- Understand how to compile and execute pipelines on Vertex AI
- Understand feature drift and skew
- Understand model monitoring for models deployed to Vertex AI endpoints