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Coursera

Enterprise AIOps with Amazon Q Business

Pragmatic AI Labs via Coursera

Overview

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Learn to deploy and manage enterprise AI operations on AWS using Amazon Q Business, CloudShell, and Amazon Bedrock. You will explore Amazon Q Business as an enterprise AI assistant built on Bedrock with enterprise-grade security, natural language processing for conversational interactions, and data source connectors for organizational knowledge. The course covers AI-assisted CLI operations using CloudShell with Amazon Q, foundational CloudShell scripting patterns for Bedrock API exploration, and programmatic management of AI resources. You will implement cost control strategies using AWS cost anomaly detection to identify spending spikes, manage SageMaker resources efficiently, and understand diminishing returns in LLM scaling to guide cost-effective model selection. The enterprise MLOps framework module covers operationalizing machine learning pipelines with governance and repeatability. In the final module, you build enterprise AIOps patterns with Bedrock, design RAG workflows using knowledge bases backed by S3 data sources, and prototype models rapidly in the Bedrock console. By completing this course, you will be able to deploy Amazon Q Business for enterprise knowledge access, manage AI costs with CloudShell automation, and implement production AIOps workflows with Bedrock.

Syllabus

  • Enterprise AI and Amazon Q
    • Covers enterprise, AIOps, operations, Amazon Q, and business.
  • CloudShell, MLOps, and Cost Control
    • Covers Bedrock, API, CloudShell, AWS, and cost.
  • AIOps Implementation
    • Covers AIOps, Bedrock, production, RAG, and workflows.

Taught by

Alfredo Deza and Noah Gift

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