This unit guides students through configuring the AWS CLI and Amazon Bedrock environment, establishing the technical foundation for using generative AI services. Students will learn inference strategies, API usage for textual and multimodal models, and integrate access control and AWS services to prepare end-to-end solutions.
Learning Objectives
- Configure the AWS CLI and Amazon Bedrock environment to authenticate, manage credentials, and establish a reproducible development workspace.
- Analyze zero-, one-, and few-shot inference approaches and select appropriate prompting strategies for textual and multimodal foundational models.
- Demonstrate use of Bedrock APIs from Python to send requests to textual models, parse responses, and implement basic error handling and logging.
- Integrate access control (IAM) and AWS ecosystem services (S3, Lambda, CloudWatch) to implement and evaluate a secure end-to-end generative AI workflow.
Curriculum
- 1 Section
- 9 Lessons
- 30 hours
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- Unit 2 — Deploying Generative AI on AWS9
- 1.1Next Steps: Configuring the AWS CLI20 mins
- 1.2Tech Setup for Using Generative AI on AWS20 mins
- 1.3Learning About Zero-, One- and Few-Shot Inference20 mins
- 1.4Using Textual Models Through the API20 mins
- 1.5Creating Prompts for Multimodal Foundational Models20 mins
- 1.6Integrating Access Control Management20 mins
- 1.7Leveraging the AWS Ecosystem in an End-to-End Solution20 mins
- 1.8Amazon Bedrock Capabilities20 mins
- 1.9Configuring Your Bedrock Environment20 mins
Instructor
Free
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