Official AWS Course

Generative AI Essentials on AWS Training

Build practical generative AI skills on AWS with hands-on labs in Amazon Bedrock and Guardrails. 1-day course covering use cases, prompt engineering, responsible AI, and project planning. No coding needed.

👥 1827 Enrolled ⏱️ 1 Day 💼 Beginner Level ⭐ 4.9 ( 173 ) Reviews

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Course Overview

Most organizations have moved past asking whether generative AI matters. The harder question is which problems it should actually solve, and how to deploy it without creating a security, compliance, or reputational mess. This one-day AWS course is built for the people who have to answer that.

You will learn what generative AI is and how foundation models work, then move quickly to the practical part: identifying use cases worth pursuing, writing prompts that produce usable output, and applying responsible AI principles before something goes into production. The course covers the security, governance, and compliance layer that turns a promising pilot into something an enterprise can actually run, and it closes with project planning, how to define a use case, choose a model, improve and evaluate results, and take an application to deployment.

The work happens in the AWS Console with hands-on labs on Amazon Bedrock, Bedrock Guardrails, and Amazon Q Business, plus a capstone lab where you build a complete generative AI project plan. There is no coding requirement. This is a course about making good decisions with generative AI, not about building models.

Mode of Training

🏫 Classroom 💻 Live Online 🧪 Blended 👨‍👩‍👧‍👦 Private Group

Upcoming Schedules

Start Date	Time	Duration	Mode	Price
Sep 04, 2026	9:00 am - 5:00 pm	1 Day	online	$599	GTR
Sep 18, 2026	9:00 am - 5:00 pm	1 Day	online	$599	GTR
Oct 09, 2026	9:00 am - 5:00 pm	1 Day	online	$599	GTR
Oct 23, 2026	9:00 am - 5:00 pm	1 Day	online	$599	GTR
Nov 06, 2026	9:00 am - 5:00 pm	1 Day	online	$599	GTR

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What you will learn

Summarize generative AI concepts, methods, and strategies
Judge when generative AI and machine learning are the right tools, and when they are not
Identify and evaluate generative AI use cases for your organization
Apply prompt engineering best practices and advanced prompting strategies
Use generative AI responsibly and safely, with guardrails for content filtering and PII protection
Explain the security, governance, and compliance considerations behind enterprise AI
Plan and scope a generative AI project from use case definition through deployment

Who Should Attend This Course?

This is a business-oriented course, not an engineering one. It suits:

Business analysts and product or project managers
Line-of-business and IT managers
Marketing and sales professionals working with AI-driven tools
IT support and operations staff supporting AI initiatives
Anyone expected to contribute to, evaluate, or lead a generative AI initiative

Prerequisites

Basic familiarity with AWS and general cloud concepts is helpful, and an awareness of machine learning terminology will make the first module easier. No programming experience is required, and you do not need prior hands-on work with Bedrock or SageMaker to attend.

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Certification

This course does not map to a specific certification exam. However, the concepts it covers, foundation models, prompt engineering, responsible AI, and AWS AI services, overlap substantially with the knowledge domains of the AWS Certified AI Practitioner (AIF-C01) exam, which makes it a useful foundation for candidates planning to sit that exam later.

📘 Generative AI Essentials on AWS Outline

What generative AI is and how it differs from traditional machine learning
Foundation models explained
The AWS generative AI service landscape
Demo: a working generative AI solution

How to identify use cases worth pursuing
Generative AI applications across business functions
Working through use case scenarios
Selecting the use case the class will build on

Introduction to prompt engineering
Prompt design best practices
Advanced prompting strategies
Model settings and parameters, and what they change
Hands-on lab: optimizing slogan generation with Amazon Bedrock

What responsible AI means in practice
The core dimensions of responsible AI
Generative AI specific considerations and risks
Hands-on lab: implementing responsible AI principles with Amazon Bedrock Guardrails

Security overview for generative AI workloads
Adverse prompts and how to defend against them
AWS security services relevant to generative AI
Governance frameworks
Compliance considerations

Anatomy of a generative AI application
Defining the use case
Selecting a foundation model
Improving model performance
Evaluating results
Deploying the application
Demo: Amazon Q Business

Where generative AI fits alongside existing delivery processes
Capstone lab: building a complete generative AI project plan

Course summary
Next steps and further learning resources

❓ Frequently Asked Questions

No. There is no programming in this course. The labs run in the AWS Console, and the work involves configuring services, writing prompts, and making design decisions. It is aimed squarely at business and non-engineering audiences.

It builds relevant foundation, but it is not an exam preparation course. AIF-C01 covers a broader syllabus than a single day allows, so treat this as a strong starting point and plan additional study before booking the exam.

For what this course sets out to do, yes. It aims to make you competent at identifying use cases, prompting effectively, and understanding the risk and governance picture, not at building production AI systems. If you want to develop generative AI applications on AWS, the appropriate next step is a developer-level course covering Bedrock application architecture, RAG, and SageMaker.

Amazon Bedrock is the centrepiece, including Bedrock Guardrails for content filtering and PII protection. You will also see Amazon Q Business demonstrated, and cover the broader AWS generative AI and security service landscape.

That course is longer, advanced, and built for engineers who will construct applications with Bedrock, SageMaker, and Lambda. This one is fundamental level and built for the people who decide what gets built, why, and under what controls. Many organizations send both audiences, to different courses.

Still have questions?

Reach out to our learning advisors for personalized guidance on choosing the right course, group training, or enterprise packages.

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What You Get with Microtek Learning

Instructor-Led Excellence

✓ Certified Instructor-led Training
✓ Top Industry Trainers
✓ Official Student Handbooks

Measurable Learning Outcomes

✓ Pre- & Post-Training Assessments
✓ Practice Tests
✓ Exam-Oriented Curriculum

Real-World Skill Building

✓ Hands-on Activities & Scenarios
✓ Interactive Online Courses
✓ Peer Collaboration (Not in self-paced)

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