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.

Generative AI for AWS Cloud Engineers

Empfohlene Erfahrung
Was Sie lernen werden
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.
Kompetenzen, die Sie erwerben
- Kategorie: Cloud Engineering
- Kategorie: Model Evaluation
- Kategorie: AI Enablement
- Kategorie: AI Security
- Kategorie: Responsible AI
- Kategorie: Natural Language Processing
- Kategorie: Retrieval-Augmented Generation
- Kategorie: Large Language Modeling
- Kategorie: Cloud Security
- Kategorie: Data Ethics
Werkzeuge, die Sie lernen werden
- Kategorie: Model Deployment
- Kategorie: Prompt Engineering
- Kategorie: Amazon Web Services
- Kategorie: Amazon Bedrock
- Kategorie: AWS Identity and Access Management (IAM)
- Kategorie: Generative AI
Wichtige Details

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Februar 2026
5 Aufgaben
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In diesem Kurs gibt es 2 Module
Welcome to Week 1 of the Generative AI for AWS Cloud Engineers course. This week, 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.
Das ist alles enthalten
15 Videos2 Lektüren2 Aufgaben
Welcome to Week 2. This week, 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.
Das ist alles enthalten
10 Videos2 Lektüren3 Aufgaben
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Status: Kostenloser TestzeitraumAmazon Web Services

Amazon Web Services
Status: Vorschau
Status: Vorschau
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Häufig gestellte Fragen
To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
When you purchase a Certificate you get access to all course materials, including graded assignments. Upon completing the course, your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.
Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.
Weitere Fragen
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