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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
8h
Updated yesterday
Join 2.9 million developers at
Join 2.9 million developers at
LEARNING OBJECTIVES
- Learn to design production-ready GenAI architectures on AWS using Amazon Bedrock and SageMaker.
- Learn to select, evaluate, and integrate foundation models (FMs) based on business and technical requirements.
- Gain experience building scalable RAG systems using OpenSearch, Aurora (pgvector), and Bedrock Knowledge Bases.
- Learn to deploy and manage customized foundation models using SageMaker and Bedrock.
- Implement secure, governed, and responsible AI systems aligned with AWS best practices.
- Get familiar with optimizing AI workloads for cost, performance, and reliability.
- Design and orchestrate agentic workflows with memory, tools, and human-in-the-loop controls.
Learning Roadmap
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.
Complete more lessons to unlock your certificate
Developed by MAANG Engineers
ABOUT THIS COURSE
The AWS Certified Generative AI Developer - Professional certification validates your knowledge of building production-ready generative AI applications on AWS. It focuses on designing, securing, deploying, and optimizing applications built on foundation models using Bedrock, RAG, agents, and SageMaker.
ABOUT THE AUTHOR
Naeem ul Haq
Educative co-founder and CTO. Ex-Microsoft (Azure). Full-Stack, Cloud, Product & Engineering Leadership.
Trusted by 2.9 million developers working at companies
A
Anthony Walker
@_webarchitect_
E
Evan Dunbar
ML Engineer
S
Software Developer
Carlos Matias La Borde
S
Souvik Kundu
Front-end Developer
V
Vinay Krishnaiah
Software Developer
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