Vertex AI Training Course

Introduction to Vertex AI and Machine Learning Platforms

• An overview of AI and machine learning workflows
• An introduction to Google Cloud Vertex AI
• An examination of Vertex AI's architecture and core components
• A look at Vertex AI's role in facilitating ML development and deployment

Configuring the Vertex AI Environment

• Setting up a Google Cloud project for Vertex AI
• A deep dive into workspaces, resources, and access permissions
• Preparing datasets and configuring development environments
• Navigating the various Vertex AI tools and interfaces

Core Machine Learning Concepts with Vertex AI

• An understanding of supervised learning principles
• An overview of regression and classification models
• Strategies for preparing data for machine learning pipelines
• Techniques for evaluating model performance and accuracy

Natural Language Processing (NLP) within Vertex AI

• An introduction to fundamental NLP concepts
• Understanding the application of text-based machine learning
• Methods for preparing and processing text data
• Exploring the NLP features integrated within Vertex AI

Developing and Training Machine Learning Models

• Preparing training code optimized for Vertex AI
• Containerizing machine learning training applications
• Configuring training jobs effectively
• Executing and monitoring model training processes

Deployment of Machine Learning Models

• Understanding the workflow for model deployment
• Creating and managing model endpoints
• Deploying trained models for predictive tasks
• Managing deployed models and associated resources

Monitoring and Troubleshooting Vertex AI Solutions

• Monitoring activities across training and deployment phases
• Identifying and resolving common configuration issues
• Troubleshooting problems related to model execution
• Implementing best practices for reliable ML workflows

Practical Workshop and Course Summary

• Constructing a complete machine learning workflow using Vertex AI
• Training and deploying a sample model in a practical scenario
• A review of key Vertex AI features and capabilities
• Discussion on next steps for advanced machine learning development