What you will learn in Vertex AI Search for Retail Specialization Course
Implement and configure Vertex AI Search for Retail to enhance retail search capabilities.
Build data pipelines using Apache Beam and Dataflow for efficient data processing.
Ingest and manage product catalog and user event data for search and recommendation models.
Design and deploy machine learning models tailored for retail search applications.
Program Overview
Serverless Data Processing with Dataflow: Foundations
⏳ 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.
Vertex AI Search for Commerce
⏳ 5 hours
Overview of the Vertex AI Search for Commerce workflow.
Hands-on experience with data ingestion methods for product catalogs and user events.
Evaluation and selection of appropriate data ingestion strategies.
Serverless Data Processing with Dataflow: Develop Pipelines
⏳ 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.
Serverless Data Processing with Dataflow: Operations
⏳ 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.
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Job Outlook
- Proficiency in Vertex AI Search for Retail is valuable for roles such as Machine Learning Engineer, Data Engineer, and Retail Solutions Architect.
- Skills acquired in this specialization are applicable across various industries, especially in e-commerce and retail sectors.
- Completing this specialization can enhance your qualifications for positions that require expertise in building and deploying AI-driven retail search solutions.
Specification: Vertex AI Search for Retail Specialization
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FAQs
- Focuses on AI-powered search and recommendation systems
- Covers integration of Vertex AI into retail platforms
- Explains personalization and customer engagement strategies
- Demonstrates real-world retail use cases with AI
- Retail business owners and product managers
- Data scientists working in e-commerce
- Cloud engineers integrating AI into retail systems
- Professionals seeking skills in AI-driven personalization
- Setting up and configuring Vertex AI Search
- Creating personalized product recommendations
- Improving customer experience with AI tools
- Applying machine learning models to retail datasets
- Helpful to know Google Cloud fundamentals
- Familiarity with retail or e-commerce concepts is useful
- Some understanding of AI/ML basics supports learning
- Step-by-step guidance makes it accessible to non-experts
- Opens opportunities in e-commerce and retail analytics
- Enhances expertise in applied AI on Google Cloud
- Strengthens qualifications for data and cloud roles
- Adds specialized AI-for-retail credentials to your resume
