Generative AI Essentials on AWS

Length 1 day
Price NZD 850 exc GST

Course overview

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Why study this course

This is a comprehensive one-day, instructor-led training course designed for professionals with limited prior knowledge of generative AI.

The course covers foundational concepts in responsible AI, provides practical experience with AWS generative AI services (Amazon Bedrock, Amazon Nova 2, Amazon Bedrock Knowledge Bases, and Amazon Bedrock AgentCore). Participants gain hands-on implementation experience with responsible AI principles through Amazon Bedrock Guardrails. Responsible AI serves as a foundational theme throughout all modules, connecting ethical principles to technical implementation. Participants progress from understanding AI fundamentals through implementing solutions, exploring agentic AI capabilities, understanding security and governance considerations, and describing project planning components.

Approximately 40% of course time is dedicated to hands-on labs and demonstrations.

Aligns to certification

AWS Certified AI Practitioner

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What you’ll learn

In this course, students will learn to do the following:

Explain responsible AI foundations
Describe multimodal AI capabilities
Implement generative AI solutions using Amazon Bedrock and Amazon Nova 2
Explain how retrieval-augmented generation (RAG) enhances AI responses by connecting agents to organisational knowledge sources
Describe Amazon Bedrock AgentCore capabilities
Apply responsible AI practices using Amazon Bedrock Guardrails
Explain security and governance considerations
Describe key components of generative AI project planning

AWS at Lumify Work

Lumify Work is an official AWS Training Partner for Australia, New Zealand, and the Philippines. Through our Authorised AWS Instructors, we can provide you with a learning path that’s relevant to you and your organisation, so you can get more out of the cloud. We offer virtual and face-to-face classroom-based training to help you build your cloud skills and enable you to achieve industry-recognised AWS Certification.

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Who is the course for?

This course is intended for those with limited prior knowledge of generative AI:

Business Analysts
IT Support Professionals
Marketing Professionals
Product or Project Managers
Line-of-Business or IT Managers
Sales Professionals

Course subjects

Module 0: Course Introduction

Course structure/schedule
Five-phase learning journey
Responsible AI foundational theme

Module 1: Responsible AI Foundations

AI evolution: from traditional to generative
Eight dimensions of responsible AI
AWS commitment to responsible AI

Module 2: Introducing Generative AI

Generative AI Foundation
Foundation models and embeddings deep dive
Amazon Bedrock and Amazon Nova 2 models
Comparing models

Module 3: Multi-Modal AI and Use Cases

Multimodal AI capabilities
Industry applications and use cases
Use case evaluation framework

Module 4: Essentials of Prompt Engineering

Prompt engineering fundamentals
Prompting strategies
Prompt security and attack vectors
Lab 1: Optimising Slogan Generation with Amazon Bedrock

Module 5: Implementing Responsible AI with Amazon Bedrock Guardrails

Amazon Bedrock Guardrails overview and configuration
Lab 2: Implementing Responsible AI Principles with Amazon Bedrock Guardrails

Module 6: Introduction to Amazon Agents

Agentic AI concepts
Amazon Bedrock capabilities
Amazon Bedrock AgentCore overview
RAG and Knowledge Bases

Module 7: Introduction to Security, Governance, and Compliance

From security principles to organisational accountability
Governance frameworks
Compliance requirements

Module 8: Implementing Generative AI Projects

Project planning fundamentals
Lab 3: Building an HR Assistant with Amazon Bedrock

Module 9: Summary

Learning journey recap
Next steps

Please note: This is an emerging technology course. Course outline is subject to change as needed.

Prerequisites

None

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Terms & Conditions

The supply of this course by Lumify Work is governed by the booking terms and conditions. Please read the terms and conditions carefully before enrolling in this course, as enrolment in the course is conditional on acceptance of these terms and conditions.