Vertex AI Search for Retail Specialization Syllabus

This specialization provides a comprehensive, hands-on learning path for building AI-driven retail search solutions using Google's Vertex AI Search for Retail. Through a series of four technical courses and a final project, learners will gain practical experience in serverless data processing with Dataflow, data ingestion for product and user data, and deploying machine learning models tailored for commerce. The program blends foundational concepts with real-world implementation, requiring approximately 49 hours to complete, and prepares learners for roles in retail technology and AI engineering.

Module 1: Serverless Data Processing with Dataflow: Foundations

Estimated time: 3 hours

• Introduction to Apache Beam and its integration with Dataflow
• Understanding the Beam Portability framework and its benefits
• Implementing security models within Dataflow pipelines

Module 2: Vertex AI Search for Commerce

Estimated time: 5 hours

• Overview of the Vertex AI Search for Commerce workflow
• Hands-on experience with data ingestion methods for product catalogs
• Hands-on experience with user event data ingestion
• Evaluation and selection of appropriate data ingestion strategies

Module 3: Serverless Data Processing with Dataflow: Develop Pipelines

Estimated time: 27 hours

• Review of core streaming concepts and Apache Beam principles
• Selection and tuning of I/O for Dataflow pipelines
• Utilization of schemas to enhance Beam code performance

Module 4: Serverless Data Processing with Dataflow: Operations

Estimated time: 9 hours

• Monitoring, troubleshooting, and testing of Dataflow pipelines
• Deployment strategies to ensure pipeline stability and reliability
• Implementation of CI/CD practices for Dataflow pipelines

Module 5: Final Project

Estimated time: 5 hours

• Design and deploy a retail search solution using Vertex AI Search
• Ingest and manage a sample product catalog and user event data
• Evaluate model performance and refine search relevance

Prerequisites

• Familiarity with Google Cloud Platform
• Basic knowledge of data processing and machine learning concepts
• Experience with Python and command-line tools

What You'll Be Able to Do After

• Implement and configure Vertex AI Search for Retail to enhance search capabilities
• Build scalable data pipelines using Apache Beam and Google Cloud Dataflow
• Ingest and manage product catalog and user event data for AI models
• Design and deploy machine learning models for retail search applications
• Monitor, troubleshoot, and optimize data pipelines in production environments