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⇱ Generative AI for AWS Cloud Engineers | Coursera


Generative AI for AWS Cloud Engineers

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Generative AI for AWS Cloud Engineers

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Gain insight into a topic and learn the fundamentals.
Intermediate level

Recommended experience

7 hours to complete
Flexible schedule
Learn at your own pace

Gain insight into a topic and learn the fundamentals.
Intermediate level

Recommended experience

7 hours to complete
Flexible schedule
Learn at your own pace

What you'll learn

  • Evaluate and optimize Foundation Model performance using RAG and Guardrails.

  • Evaluate key principles and legal risks of Responsible AI.

  • Implement security and privacy controls within the AWS Shared Responsibility Model.

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Recently updated!

February 2026

Assessments

5 assignments

Taught in English

There are 2 modules in this course

Generative AI for AWS Cloud Engineers course is designed for technical professionals aiming to master the integration, deployment, and optimization of large language models (LLMs) within the AWS cloud infrastructure. It aims to bridge the gap between traditional cloud engineering and the rapidly evolving landscape of generative AI.

This course facilitates learners with approximately 4:00–5:00 Hours of Video lectures that provide a deep dive into both architectural theory and hands-on implementation. The course is structured into 3 Comprehensive Modules, with each module further split into technical lessons. To test the practical understanding of learners, every module includes Quizzes, and In-Video Knowledge Checks. Enroll in our β€œGenerative AI for AWS Cloud Engineers” course to lead the next generation of cloud-native AI innovation. - Module 1: Gen AI on AWS - Amazon Bedrock - Module 2: Security and Governance of AI Solutions This course is specifically designed for technical professionals and cloud practitioners who aim to bridge the gap between core infrastructure and modern AI implementation. By the end of this course, a learner will be able to: - Understand foundational concepts, methods, and strategies related to artificial intelligence (AI), machine learning (ML), and generative AI (Gen AI) within the AWS ecosystem. - Identify appropriate AI/ML and generative AI technologies to address specific organizational use cases effectively. - Apply responsible practices in the utilization of AI, ML, and Generative AI technologies.

Welcome to the Generative AI for AWS Cloud Engineers course. In this course, we will explore the Amazon Bedrock, starting with a comprehensive overview and hands-on demos to understand how to leverage FMs within the AWS ecosystem. You will learn how to customize models through Fine-tuning and implement advanced architectures like Retrieval-Augmented Generation (RAG) to enhance model accuracy with external data. By the end of this module, you will be able to configure Guardrails to ensure responsible AI usage, orchestrate complex tasks with Amazon Bedrock Agents, and navigate the Pricing structures to build cost-effective Generative AI solutions.

What's included

15 videos2 readings2 assignments

15 videosβ€’Total 105 minutes
  • What is a Generative AI Model?β€’4 minutes
  • Types of Foundation Modelsβ€’5 minutes
  • Business Metrics for Generative AIβ€’8 minutes
  • Amazon Bedrock - Overviewβ€’9 minutes
  • Amazon Bedrock - Demoβ€’6 minutes
  • Foundation Models on Amazon Bedrockβ€’6 minutes
  • Finetuning Foundation Models - Demoβ€’7 minutes
  • Evaluation Metrics of Foundation modelsβ€’9 minutes
  • Understanding RAG Architecture of LLMβ€’6 minutes
  • AWS Services for Storage of Vector Embeddingsβ€’9 minutes
  • Amazon Bedrock RAG & Knowledge Base - Demoβ€’9 minutes
  • Amazon Bedrock - GuardRailsβ€’6 minutes
  • Amazon Bedrock - GuardRails - Demoβ€’14 minutes
  • Amazon Bedrock Agentsβ€’4 minutes
  • Amazon Bedrock - Pricingβ€’5 minutes
2 readingsβ€’Total 25 minutes
  • Welcome to the Courseβ€’15 minutes
  • Overview of Gen AI on AWS - Amazon Bedrockβ€’10 minutes
2 assignmentsβ€’Total 80 minutes
  • Gen AI on AWS - Amazon Bedrock - Assessmentβ€’45 minutes
  • Amazon Bedrock and its features - Knowledge Checkβ€’35 minutes

Welcome to the Generative AI for AWS Cloud Engineers course. In this course, we will explore the foundational principles and ethical practices required to build and deploy Responsible AI systems. We will learn how to select models using responsible criteria and navigate the complex legal risks associated with generative AI. Furthermore, we will dive into the AWS Shared Responsibility Model as it applies to AI, identifying specific AWS tools and services designed to secure AI systems and ensure robust governance. By the end of this week, you will be able to implement security and privacy considerations effectively to manage and protect your AI applications within the AWS ecosystem.

What's included

11 videos2 readings3 assignments

11 videosβ€’Total 46 minutes
  • Key Principles of Responsible AIβ€’4 minutes
  • Responsible practices to select a modelβ€’5 minutes
  • Legal risks of working with generative AIβ€’6 minutes
  • Best Practices for Data Collectionβ€’4 minutes
  • Data privacy and the importance of data consent.β€’4 minutes
  • AWS Tools for Responsible AIβ€’3 minutes
  • AWS Tools for Explainabe AIβ€’4 minutes
  • AWS Services for Securing AI Systemsβ€’5 minutes
  • AWS Shared Responsibility Modelβ€’4 minutes
  • Securiy and Privacy considerationβ€’4 minutes
  • AWS Services for Governance of AI Applicationsβ€’4 minutes
2 readingsβ€’Total 25 minutes
  • Overview of Security and Governance of AI Solutionsβ€’10 minutes
  • What's Next?β€’15 minutes
3 assignmentsβ€’Total 130 minutes
  • Security and Governance of AI Solutions - Assessmentβ€’25 minutes
  • Responsible AI - Knowledge Checkβ€’25 minutes
  • Project: Creating Guardrails in Amazon Bedrockβ€’80 minutes

Instructor

Whizlabs
166 Coursesβ€’125,579 learners

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