Vertex AI Model Garden Training

• Prior completion “Machine Learning on Google Cloud” course or the equivalent knowledge of TensorFlow/Keras and machine learning.
• Experience scripting in Python and working in Jupyter notebooks to create machine learning models.

Students will learn,

• Understand the model options available within Vertex AI Model Garden
• Incorporate models in Vertex AI Model Garden in your machine learning workflows
• Leverage foundation models for generative AI use cases
• Fine-tune models to meet your specific needs

Module 1: Vertex AI for ML Workloads

• Vertex AI on Google Cloud
• Options for training, tuning and deploying ML models on Vertex AI
• Generative AI options on Google Cloud and Vertex AI

Module 2: Model Garden

• Introduction to Model Garden
• Model types in Model Garden
• Connecting models from Gen AI Studio and Model Registry
• Introduction to course use cases

Module 3: Task-specific Solutions: Content Classification

• Pre-trained models for specific tasks
• VertexAI AutoML
• Using a pre-trained model via the Python SDK

Module 4: Foundation Models: Text Embeddings via PaLM

• Introduction to foundation models
• PaLM API
• GenAI Studio
• Using the Embeddings API

Module 5: Fine-tunable Models

• Fine-tunable models in Model Garden
• Vertex AI Pipelines
• Demo: Fine-tuning models for your specific use case