Gen AI Dev- Design and Implement Vector Store Solutions

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Gen AI Dev- Design and Implement Vector Store Solutions

Instructor: AWS Instructor

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6 modules

Gain insight into a topic and learn the fundamentals.

Advanced level

Recommended experience

2 hours to complete

Flexible schedule

Learn at your own pace

6 modules

Gain insight into a topic and learn the fundamentals.

Advanced level

Recommended experience

2 hours to complete

Flexible schedule

Learn at your own pace

What you'll learn

Design and implement vector store solutions
Create workflows that automatically sync source data with vector stores
Evaluate governance strategies to implement effective version control and deployment practices

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There are 6 modules in this course

In this module, you will learn how to do the following:Design and implement vector store solutions.

What's included

2 readings

What's included

17 readings

17 readingsTotal 20 minutes

Introduction1 minute
Understanding vector embeddings1 minute
Vector distance metrics1 minute
Database architecture comparison1 minute
Foundation model augmentation1 minute
AWS vector database services2 minutes
Introduction1 minute
Vector database solutions on AWS1 minute
Amazon Bedrock Knowledge Bases1 minute
Vector storage options for Bedrock Knowledge Bases2 minutes
Knowledge organization strategies1 minute
Hierarchical knowledge organization1 minute
Topic-based segmentation1 minute
Combining organizational approaches1 minute
Storage architectures for knowledge organization2 minutes
Implementation considerations1 minute
Architectural patterns1 minute

What's included

32 readings

32 readingsTotal 33 minutes

Introduction1 minute
Understanding data freshness in vector stores1 minute
Core components and architecture patterns1 minute
Core components of maintenance architecture1 minute
Maintenance architecture patterns1 minute
Evaluation metrics for maintenance systems1 minute
Real-world maintenance challenges1 minute
Introduction1 minute
Delta-based update strategies1 minute
Vector store synchronization strategies1 minute
Real-time synchronization implementation1 minute
Automated workflow orchestration1 minute
Scheduled refresh pipeline design2 minutes
Real-world synchronization challenges1 minute
Introduction1 minute
Vector database fundamentals1 minute
Vector representation and performance trade-offs1 minute
Core concepts for semantic search operations1 minute
Advanced sharding strategies1 minute
Domain-based and size-based sharding approaches1 minute
Cross-shard optimization and query routing1 minute
Multi-index design for specialized domains1 minute
Domain segmentation and customized indexing1 minute
Vector dimension optimization for domain-specific data1 minute
Hierarchical indexing techniques1 minute
HNSW and multi-level retrieval pipelines1 minute
Coarse-to-fine search and semantic filtering layers1 minute
Performance optimization at scale1 minute
Benchmarking, resource tuning, and monitoring1 minute
Scaling strategies for high-volume vector operations1 minute
Real-world implementation example1 minute
Amazon S3 Vectors performance optimization1 minute

What's included

29 readings

29 readingsTotal 29 minutes

Introduction1 minute
Document timestamp implementation1 minute
Timestamp types and formats1 minute
Comparing created and modified timestamps1 minute
ISO-8601 formatting and standards1 minute
Custom attribute development1 minute
Authorship metadata schema1 minute
Creator, contributor, and editor roles1 minute
Tagging systems for domain classification1 minute
Designing effective tag structures1 minute
Comparing hierarchical and flat tag structures1 minute
Best practices for metadata implementation1 minute
Automated metadata generation1 minute
Metadata governance and quality assurance1 minute
Introduction1 minute
Amazon S3 metadata types1 minute
System-defined metadata overview1 minute
User-defined metadata with x-amz-meta prefix1 minute
Custom key-value metadata for foundation models1 minute
Optimizing foundation models with strategic metadata1 minute
Metadata for contextual enrichment1 minute
Confirming alignment between storage structure and AI retrieval1 minute
Metadata framework design patterns1 minute
Hierarchical classification systems1 minute
Standardized attribute schemas1 minute
Best practices for metadata implementation1 minute
Naming conventions and standards1 minute
Metadata validation and quality assurance1 minute
Amazon S3 metadata capabilities for vector applications1 minute

What's included

41 readings

41 readingsTotal 41 minutes

Introduction1 minute
Building production-ready AI solutions1 minute
Understanding the data landscape1 minute
Data source evaluation1 minute
Integration assessment framework1 minute
Choosing integration patterns1 minute
Comparing event-driven and scheduled integrations1 minute
Comparing push and pull models1 minute
Selecting AWS services1 minute
Key services for integration1 minute
Service architecture patterns1 minute
Real-world implementation1 minute
Implementation overview1 minute
The results1 minute
Ensuring production readiness1 minute
Integration testing and validation1 minute
Operational excellence framework1 minute
Introduction1 minute
Document management system integration1 minute
Storage and search architecture1 minute
Amazon S3 document storage implementation1 minute
Amazon Kendra for indexing and querying1 minute
Connector configuration1 minute
Platform integration1 minute
Data extraction techniques1 minute
Knowledge base and wiki Integration1 minute
Secure API connectivity1 minute
API Gateway security implementation1 minute
Access management with IAM and Amazon Cognito1 minute
Query execution and transformation1 minute
Synchronization patterns1 minute
Comparing real-time and batch synchronization1 minute
Event-driven architecture implementation1 minute
Real-world implementation1 minute
Implementation overview1 minute
The results1 minute
Introduction1 minute
Amazon Titan Embeddings guide1 minute
Model capabilities and comparison1 minute
Enterprise implementation strategies1 minute
Governance and lifecycle management1 minute

What's included

4 readings1 assignment

Instructor

AWS Instructor

Amazon Web Services

168 Courses365,088 learners

Offered by

Amazon Web Services

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