[NEW] AWS Certified Generative AI Developer - Professional

[NEW] AWS Certified Generative AI Developer – Professional – Mock Exam Practice Test Academy

Updated July 2026 – This free AWS Generative AI Udemy course equips cloud developers, architects, and security specialists with the exact skills needed to pass the AWS Certified Generative AI Developer – Professional exam on the first try. It blends high‑fidelity practice tests, detailed answer explanations, and real‑world design patterns for building production‑grade GenAI solutions on AWS. Learners walk away with a certification‑ready mindset, practical Bedrock workflows, and a solid grasp of cost‑optimization and governance best practices.

What You'll Learn

• Build end‑to‑end generative AI pipelines on AWS using Amazon Bedrock, Lambda, and Step Functions.
• Master prompt‑engineering techniques that improve model relevance and reduce hallucinations.
• Learn how to integrate foundation models into existing business applications and data stores.
• Understand compliance, governance, and data‑security controls required for GenAI workloads on AWS.
• Create semantic caching strategies that lower inference costs and latency for high‑traffic AI services.
• Implement robust testing, validation, and troubleshooting methods for reliable AI output.
• Apply cost‑optimization tactics such as provisioned throughput and vector‑store caching in real projects.
• Analyze exam‑style scenario questions and receive detailed architectural explanations for each answer.

Course Details

• Instructor: Mock Exam Practice Test Academy
• Rating: 3.0 stars
• Language: English (en‑US)
• Enrolled students: 4,567
• Last updated: July 2026
• Certificate: Yes, upon completion
• Includes: Lifetime access, mobile‑friendly content, instructor support

What This Course Covers

Domain 1 – Foundation Model Integration, Data Management, and Compliance

• Integrate foundation models into applications and orchestrate data pipelines for GenAI solutions.
• Design secure data flows that meet AWS compliance standards, including PII redaction and encryption.
• Utilize vector stores and Retrieval‑Augmented Generation (RAG) to enhance contextual relevance.
• Evaluate model quality and responsible AI criteria before production deployment.

Domain 2 – Implementation and Integration

• Deploy Amazon Bedrock services and configure Bedrock Agents for autonomous workflow execution.
• Craft effective prompts and fine‑tune them for specific business use cases.
• Build agentic AI solutions that combine Lambda, API Gateway, and other AWS services.
• Manage model versioning, scaling, and continuous delivery in a production environment.

Domain 3 – AI Safety, Security, and Governance

• Apply encryption, IAM policies, and Guardrails to protect GenAI workloads.
• Conduct risk assessments and establish governance frameworks for model usage.
• Implement responsible AI practices, including toxicity filtering and bias mitigation.
• Monitor audit logs and set up alerts for anomalous AI behavior.

Domain 4 – Operational Efficiency and Optimization

• Optimize inference cost using provisioned throughput and semantic caching techniques.
• Scale GenAI workloads with appropriate compute options such as EC2, SageMaker, or Serverless.
• Leverage CloudWatch metrics and logs to track performance and detect bottlenecks.
• Tune model parameters and caching policies to achieve low‑latency responses.

Domain 5 – Testing, Validation, and Troubleshooting

• Validate model outputs against predefined quality criteria and business rules.
• Perform functional, load, and stress testing for scalable AI applications.
• Diagnose integration issues between Bedrock, Lambda, and downstream services.
• Implement continuous monitoring, alerting, and automated remediation workflows.

Who Should Take This Course

• Cloud developers who need to demonstrate advanced expertise in integrating foundation models.
• Software engineers tasked with building agentic AI services and Retrieval‑Augmented Generation pipelines.
• Security and compliance specialists responsible for governance and data‑privacy in AI workloads.
• Cloud architects focused on cost‑effective scaling and operational efficiency of GenAI applications.
• QA engineers and test developers who validate model outputs and troubleshoot AI systems.

Prerequisites

• Basic familiarity with core AWS services such as IAM, Lambda, S3, and CloudWatch.
• No prior generative AI experience required — the course is beginner‑friendly but fast‑paced.
• Recommended: Understanding of REST APIs and basic scripting (Python or JavaScript) to follow labs.

Why Enroll in This Course

This practice‑test‑driven Udemy course delivers the exact exam‑level scenarios you will face on the AWS Certified Generative AI Developer – Professional exam. A free coupon provides 100 % off for a limited time, so you can access the full question bank without any cost. The detailed answer explanations teach the reasoning behind each architectural choice, giving you confidence that extends beyond the certification. Compared with generic AI tutorials, this course focuses exclusively on AWS‑specific services, governance, and cost‑optimization, making it the most targeted preparation available today.

Course Highlights

• Lifetime access to all practice exams and explanations, allowing unlimited review.
• Mobile‑compatible lessons let you study on the Udemy app wherever you are.
• Instructor support ensures you can ask questions and receive clarification on complex topics.
• Real‑world scenario questions mirror the difficulty and format of the official AWS exam.
• Comprehensive answer breakdowns teach both the correct solution and why alternatives fail.
• Certificate of completion that can be added to LinkedIn or a professional portfolio.

Frequently Asked Questions

Q: Is this course really free?
A: Yes. A free coupon grants 100 % off the regular price for a limited period, giving you full access without any payment required.