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Grokking the AWS Certified Generative AI Developer - Professional

Lead the GenAI revolution with an AWS Certified Generative AI Developer – Professional exam. Build skills in advanced AI techniques, cloud integration, and innovative AI-driven solutions.

4.7
75 lessons
15 cloud labs
1 AI mock interview
1 breakout session
20h
Created by Naeem ul Haq
Grokking the AWS Certified Generative AI Developer - Professional
What's included
  • 75 lessons across 14 modules
  • 11 quizzes with instant feedback
  • 15 cloud labs with no setup required
  • 1 AI mock interview with scoring rubrics
  • 1 breakout session with a virtual coach
Why this course
  • Ace the AWS Generative AI ExamDemonstrate your expertise in AWS generative AI applications and confidently pass the AWS Certified Generative AI Developer exam.
  • Design Production-Ready AI SystemsArchitect and deploy reliable, scalable generative AI systems on AWS that meet real-world business needs and compliance requirements.
  • Optimize AI Workflows for PerformanceImplement cost-effective strategies and performance optimizations in generative AI applications to enhance operational efficiency.
  • Lead AI Governance InitiativesEstablish and enforce governance frameworks for generative AI systems, ensuring compliance, security, and ethical AI practices.
Who wrote it
Naeem ul Haq
Educative co-founder and CTO. Ex-Microsoft (Azure). Full-Stack, Cloud, Product & Engineering Leadership.

Naeem ul Haq is the co-founder and CTO of Educative, a hands-on learning platform for software engineers. Before co-founding Educative, he spent seven years as a software engineer at Microsoft, where he worked on the Windows Azure Fabric Controller, a core component of what became Microsoft Azure, and on Remote Desktop for Windows Server. Naeem co-founded Educative in 2015 alongside his brother Fahim to make developer education more interactive and accessible. His courses on Educative cover cloud technologies and full-stack web development, drawing directly from his experience building production infrastructure at Microsoft.

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What You'll Learn

  • Design scalable generative AI architectures using AWS services and make informed architectural decisions under constraints.
  • Implement retrieval-augmented generation (RAG) workflows and manage agents to build cohesive generative AI applications.
  • Deploy and optimize generative AI systems using AWS-native tools, focusing on security, cost, and performance considerations.
  • Evaluate and fine-tune foundation models in AWS to ensure high-quality outputs and compliance with governance standards.
  • Analyze business requirements and apply architectural patterns to create effective generative AI solutions on AWS.

Learning Roadmap

75 Lessons11 Quizzes15 Cloud Labs1 Assessment

1.

Introduction

Introduction

Master AWS generative AI application architecture and exam preparation strategies.

2.

AWS Core Services for AIP Exam

AWS Core Services for AIP Exam

Explore AWS services for building scalable and efficient generative AI applications.

3.

Generative AI Fundamentals

Generative AI Fundamentals

4 Lessons

4 Lessons

Explore generative AI's capabilities, prompt engineering, and effective management techniques.

4.

Introducing Amazon Bedrock

Introducing Amazon Bedrock

6 Lessons

6 Lessons

Master foundation models, deployment strategies, and architecture design for generative AI on AWS.

5.

Data Engineering and Retrieval-Augmented Generation (RAG)

Data Engineering and Retrieval-Augmented Generation (RAG)

8 Lessons

8 Lessons

Learn how data engineering and retrieval design power accurate GenAI systems, from clean data and embeddings to advanced RAG patterns.

6.

Agentic AI Systems

Agentic AI Systems

7 Lessons

7 Lessons

Explore agentic AI systems, focusing on autonomy, multi-agent coordination, and effective safeguards.

7.

Model Deployment with SageMaker AI

Model Deployment with SageMaker AI

8 Lessons

8 Lessons

Master deployment strategies for generative AI using SageMaker’s comprehensive tools and services.

8.

AI Safety and Content Moderation

AI Safety and Content Moderation

5 Lessons

5 Lessons

Learn how AWS secures generative AI using guardrails, grounding, threat detection, and data protection to enforce safety, hallucinations, and detect misuse.

9.

AI Governance and Compliance

AI Governance and Compliance

5 Lessons

5 Lessons

Learn to design GenAI systems on AWS using responsible AI principles, model and data governance, auditability, continuous monitoring, and automated enforcement.

10.

Operational Efficiency for AI Systems

Operational Efficiency for AI Systems

4 Lessons

4 Lessons

Optimize costs, enhance performance, and monitor generative AI systems effectively.

11.

Model Evaluation and Troubleshooting

Model Evaluation and Troubleshooting

5 Lessons

5 Lessons

Master evaluation, feedback, and troubleshooting to build reliable production GenAI systems on AWS.

13.

Practice Exam Solution: AWS Certified GenAI Developer

Practice Exam Solution: AWS Certified GenAI Developer

15 Lessons

15 Lessons

Explore advanced strategies for integrating and optimizing Generative AI applications across various industries.
Certificate of Completion
Showcase your accomplishment by sharing your certificate of completion.
Fahim Ul HaqGrokking the AWS CertifiedGenerative AI Developer -ProfessionalFounder & CEO
About this course
WHY I WROTE THIS COURSE
Generative AI is moving from experimentation to production. Companies are building real applications powered by foundation models, RAG pipelines, and intelligent agents. The AWS Certified Generative AI Developer - Professional certification reflects this shift, focusing on engineers who can design and deploy reliable, secure generative AI systems at scale. I built this course based on a pattern I’ve seen across developers transitioning into this space. Many understand the concepts behind LLMs, but struggle to translate them into production-ready systems on AWS. Preparing for the AWS Certified Generative AI Developer exam requires more than theory. It requires knowing how to combine services like Bedrock, SageMaker, and retrieval pipelines into cohesive applications. This course focuses on that integration. You’ll learn how to design generative AI workflows using RAG, build and manage agents, and deploy scalable applications using AWS-native tools. Security, optimization, and cost considerations are treated as first-class concerns throughout the course. If you’re aiming to become a generative AI developer and pass the AWS Certified Generative AI Developer - Professional exam, this course provides a clear, practical path to building and shipping real-world AI systems on AWS.
ABOUT THE AUTHOR

Naeem ul Haq

Educative co-founder and CTO. Ex-Microsoft (Azure). Full-Stack, Cloud, Product & Engineering Leadership.

Learn more about Naeem

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