Whizlabs

AWS: Generative AI Fundamentals

Whizlabs

AWS: Generative AI Fundamentals

Whizlabs Instructor

Instructor: Whizlabs Instructor

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

Recommended experience

6 hours to complete
Flexible schedule
Learn at your own pace
Gain insight into a topic and learn the fundamentals.
Beginner level

Recommended experience

6 hours to complete
Flexible schedule
Learn at your own pace

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Recently updated!

May 2026

Assessments

5 assignments

Taught in English

91%

of learners achieved a positive career outcome

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There are 2 modules in this course

Module details

In this module, you’ll be introduced to the foundational concepts of generative AI and foundation models used across modern enterprise AI applications. You’ll begin by exploring what generative AI is, key terminology used in AI systems, and how organizations identify business use cases for generative AI solutions. Next, you’ll learn about the challenges of generative AI, core components of generative AI systems, the lifecycle of foundation models, and different types of foundation models used across industries. The module also introduces business metrics for generative AI and explains how organizations evaluate the impact, performance, and value of AI-driven solutions. Additionally, you’ll gain foundational knowledge of modern generative AI architectures and understand how organizations apply AI technologies to improve automation, productivity, innovation, and customer experiences. By the end of this module, you’ll have a strong understanding of generative AI fundamentals, foundation models, enterprise AI use cases, and the foundational concepts required to understand modern AI systems.

What's included

8 videos3 readings2 assignments1 discussion prompt

In this module, the focus shifts to Amazon Bedrock, foundation model selection, RAG architectures, AI application development, and enterprise generative AI implementation concepts. You’ll explore Amazon Bedrock fundamentals and understand how organizations use Bedrock to access and deploy foundation models for generative AI applications. Next, you’ll learn how to choose foundation models, understand finetuning concepts, evaluate foundation model performance, and explore practical demos related to Amazon Bedrock. The module also introduces Retrieval-Augmented Generation (RAG) architectures, vector embeddings, knowledge bases, and enterprise AI integration concepts used to build intelligent AI-powered applications. Additionally, you’ll explore Amazon Bedrock Guardrails, Bedrock Agents, integrations with AWS services such as CloudWatch and Amazon S3, PartyRock playground environments, and Amazon Bedrock pricing considerations. Through conceptual explanations, demos, and real-world AI scenarios, you’ll learn how organizations build secure, scalable, and enterprise-ready generative AI solutions using AWS services. By the end of this module, you’ll have a strong understanding of Amazon Bedrock capabilities, AI application architectures, RAG implementations, AI governance concepts, and enterprise generative AI best practices.

What's included

15 videos3 readings3 assignments

Instructor

Whizlabs Instructor
Whizlabs
160 Courses122,096 learners

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