Gen AI Dev- Implement data validation & processing pipelines

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Gen AI Dev- Implement data validation & processing pipelines

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

Build effective data validation and processing pipelines for foundation models
Identify required and optional JSON fields for different foundation models
Design synchronized audio-visual workflows using Amazon Transcribe

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There are 6 modules in this course

In this module, you will learn how to do the following:Build effective data validation and processing pipelines for foundation models, ensuring optimal AI performance through high-quality inputs.This module focuses on implementing data validation and processing pipelines for foundation models, covering essential techniques to ensure high-quality data inputs for optimal AI model performance. You will gain comprehensive guidance on data quality management, validation workflows, multimodal processi

What's included

2 readings

What's included

36 readings

36 readingsTotal 40 minutes

Introduction1 minute
Multi-turn dialog formatting fundamentals1 minute
Input quality impact on model outputs1 minute
Consistency and reliability considerations1 minute
Introduction1 minute
Data quality for foundation models1 minute
Common data quality challenges1 minute
Key quality dimensions1 minute
Impact on foundation model performance1 minute
Building a data quality mindset1 minute
Introduction1 minute
Real-time and custom validation with AWS Lambda3 minutes
DQDL implementation in AWS Glue1 minute
Text data validation1 minute
Interactive and automated validation with Data Wrangler2 minutes
Integration and monitoring1 minute
Introduction1 minute
Amazon CloudWatch metrics for data quality tracking1 minute
Monitoring for foundation model data validation pipelines1 minute
Automated remediation workflows1 minute
Proactive issue detection and response1 minute
Advanced data quality monitoring techniques1 minute
Amazon Bedrock AgentCore for data quality management1 minute
Integration with remediation systems2 minutes
AWS Security Hub for data pipeline security1 minute
Introduction1 minute
Pipeline architecture patterns1 minute
Designing effective data validation pipeline architecture1 minute
Orchestration with Step Functions1 minute
Amazon Nova Act for automated data workflows1 minute
Data validation pipelines with step functions1 minute
Quality gates and conditional processing1 minute
Feedback loops and continuous improvement1 minute
Designing effective data validation pipeline architecture1 minute
Real-world implementation example1 minute
Enhanced storage capabilities for data pipelines1 minute

What's included

17 readings

17 readingsTotal 17 minutes

Introduction1 minute
Amazon Bedrock API request structure1 minute
Universal JSON fields1 minute
Model-specific JSON formatting1 minute
Advanced JSON configuration1 minute
Error handling and debugging1 minute
JSON schema validation1 minute
API testing and validation tools1 minute
Best practices for JSON formatting1 minute
Introduction1 minute
SageMaker endpoint input requirements1 minute
Data preprocessing pipelines1 minute
Performance optimization strategies1 minute
Introduction1 minute
Multi-turn dialog formatting fundamentals1 minute
Model-specific formatting schemas1 minute
Context window management strategies1 minute

What's included

8 readings

8 readingsTotal 10 minutes

Introduction1 minute
Text reformatting with Amazon Bedrock1 minute
Amazon Nova models for text preprocessing1 minute
Text standardization techniques1 minute
Entity extraction with Amazon Comprehend and Amazon Bedrock3 minutes
Data normalization with Lambda1 minute
Healthcare data pipeline example1 minute
Custom model development for specialized processing1 minute

What's included

18 readings

18 readingsTotal 21 minutes

Introduction1 minute
Understanding multimodal data types1 minute
Multimodal data characteristics1 minute
AWS services for multimodal processing1 minute
Amazon Bedrock multimodal models1 minute
Common multimodal use cases2 minutes
Systematic framework for implementing multimodal AI solutions1 minute
Processing workflow fundamentals1 minute
Introduction1 minute
Bedrock foundation model integration1 minute
Optimizing Amazon Bedrock foundation model integration1 minute
SageMaker custom processing2 minutes
Leveraging SageMaker for custom multimodal processing1 minute
Audio-visual processing with Amazon Transcribe1 minute
Amazon Bedrock Multimodal Models1 minute
Optimizing audio-visual content processing with Amazon Transcribe1 minute
Advanced processing patterns2 minutes
Orchestrating complex workflows1 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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