Gen AI Dev- Select and Configure Foundation Models

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Gen AI Dev- Select and Configure Foundation Models

Instructor: AWS Instructor

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5 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

5 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

Implement model evaluation frameworks
Design flexible routing strategies
Build resilient AI systems with AWS services

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There are 5 modules in this course

In this module, you will learn how to do the following:Implement model evaluation frameworks.Design flexible routing strategies.Build resilient AI systems with AWS services.Foundation models are transforming how organizations build AI applications, but selecting and configuring the right models requires systematic evaluation and resilient architecture design. This module covers how to assess model capabilities, implement flexible routing strategies, and build resilient AI systems that maintain a

What's included

2 readings

What's included

23 readings

23 readingsTotal 23 minutes

Introduction1 minute
Foundation model landscape1 minute
Performance benchmarking fundamentals1 minute
Capability assessment framework for AI systems1 minute
Systematic capability mapping1 minute
Domain-specific evaluation1 minute
Task-specific analysis1 minute
Multimodal assessment1 minute
RAG evaluation1 minute
Bedrock evaluation tools1 minute
Amazon Bedrock AgentCore for advanced evaluation1 minute
Identifying and evaluating limitations1 minute
Business application alignment1 minute
Amazon Nova models for model selection guide1 minute
Custom model development options1 minute
Example: AI-powered customer support optimization1 minute
Introduction1 minute
Serverless AI integration patterns1 minute
AWS components overview1 minute
Infrastructure options for AI workloads1 minute
Interface and schema design1 minute
Adapter pattern implementation1 minute
Lambda structuring and error handling1 minute

What's included

14 readings

14 readingsTotal 17 minutes

Introduction1 minute
Static model routing fundamentals1 minute
Advantages and disadvantages1 minute
Static model routing use cases1 minute
Implementation examples2 minutes
Best practices1 minute
Introduction1 minute
Amazon Bedrock Intelligent Prompt Routing1 minute
Dynamic routing with Nova models1 minute
Advantages over static routing1 minute
Use cases and scenarios1 minute
Implementation approaches3 minutes
Cost-optimized routing strategies1 minute
Best practices and considerations1 minute

What's included

24 readings

24 readingsTotal 24 minutes

Introduction1 minute
Fundamentals of circuit breaker patterns1 minute
Step Functions for circuit breaker implementation1 minute
Configuring step functions for AI resilience1 minute
Implementing fallback paths1 minute
Monitoring and optimizing circuit breaker performance1 minute
Implementation best practices1 minute
Best practices for AI circuit breakers1 minute
AWS Security Hub integration for AI resilience1 minute
Introduction1 minute
Understanding cross-region inference1 minute
Assessing Amazon Bedrock regional model availability1 minute
Setting up cross-region inference1 minute
Multi-region architecture design patterns1 minute
Performance and cost considerations1 minute
Implementation best practices1 minute
Introduction1 minute
Understanding graceful degradation1 minute
Feature prioritization and core functionality1 minute
Tiered fallback architecture1 minute
Response caching strategies1 minute
User experience considerations1 minute
Implementation best practices1 minute
Implement graceful degradation1 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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