Gen AI Dev- Model Deployment Strategies

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Gen AI Dev- Model Deployment Strategies

Instructor: AWS Instructor

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6 modules

Gain insight into a topic and learn the fundamentals.

Advanced level

Recommended experience

1 hour to complete

Flexible schedule

Learn at your own pace

6 modules

Gain insight into a topic and learn the fundamentals.

Advanced level

Recommended experience

1 hour to complete

Flexible schedule

Learn at your own pace

What you'll learn

Describe the benefits and use cases for model deployment strategies
Design model selection frameworks for generative AI applications
Develop safeguarding mechanisms to protect your AI workflows

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There are 6 modules in this course

Deploying generative AI models in production environments requires strategic planning and careful consideration of performance, scalability, and cost requirements. Modern AI applications demand flexible deployment approaches that can handle varying workloads while maintaining reliability and security.In this lesson, you will learn how to do the following:Describe the benefits and use cases for model deployment strategies in generative AI applications

What's included

3 readings

What's included

13 readings

13 readingsTotal 14 minutes

Introduction1 minute
Approach 1: On-Demand Invocation with AWS Lambda Functions1 minute
Key Characteristics and Use Cases1 minute
Implementation Architecture2 minutes
Approach 2: Provisioned Throughput with Amazon Bedrock1 minute
Key Benefits and Use Cases1 minute
Implementation Architecture1 minute
Approach 3: Hybrid Solutions with Amazon SageMaker AI Endpoints1 minute
Key Advantages and Capabilities1 minute
Implementation Architecture1 minute
Using Your Own Frontier Model Trained In Nova Forge1 minute
Strategy Selection and Comparison1 minute
AWS AI Factories1 minute

What's included

7 readings

What's included

17 readings

17 readingsTotal 27 minutes

Introduction1 minute
Introduction to Multi-Model Orchestrations1 minute
Key Advantages of Multi-Model Orchestration1 minute
Multi-Model Use Cases and Applications1 minute
Model Selection and Aggregation Strategies1 minute
Introduction1 minute
Core Capabilities of Model Selection Frameworks1 minute
Framework Architecture and Components1 minute
Example Workflow: Model Selection6 minutes
Selection Criteria and Optimization Strategies1 minute
Advanced Selection Techniques1 minute
Introduction1 minute
Model Chaining for Complex Tasks1 minute
Model Chaining Types1 minute
Model Chaining Implementation Example6 minutes
Model Collections with Custom Aggregation Logic1 minute
Advanced Orchestration Patterns1 minute

What's included

10 readings

10 readingsTotal 13 minutes

Introduction1 minute
Safeguarding Mechanisms1 minute
Resource optimization benefits1 minute
Failure mitigation and resilience1 minute
Controlling model behavior1 minute
Introduction1 minute
AWS Step Functions for Stopping Conditions2 minutes
AWS Lambda Functions for Timeout Mechanisms3 minutes
IAM Policies for Resource Boundaries1 minute
Circuit Breakers for Failure Mitigation1 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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