Welcome to the most comprehensive prep course for the NEW AWS Certified Generative AI Developer – Professional exam. This course is meticulously designed for experienced developers who want to validate their advanced skills in designing, developing, deploying, managing, and securing Generative AI applications on the AWS cloud. This is a new, challenging, and highly in-demand certification, and this course will give you the knowledge and confidence you need to pass. We go far beyond just theory. This course provides a deep dive into the critical services and concepts you must know for this professional-level certification.
[What You Will Master]
In this course, you will gain hands-on expertise and deep technical knowledge across all exam domains:
- Core Generative AI Services: Master Amazon Bedrock, including foundational model selection, advanced prompt engineering, Retrieval Augmented Generation (RAG), agents, and fine-tuning. We also cover Amazon SageMaker in-depth, including SageMaker JumpStart, training, inference, and endpoints.
- Data Lifecycle & Pipelines: Learn to integrate essential data processing services (like AWS Lambda, AWS Glue), feature stores (Amazon SageMaker Feature Store), and specialized databases (like vector stores for OpenSearch or Amazon Aurora) to build robust data pipelines for your GenAI models.
- Security & Governance: Implement rock-solid security using IAM roles and policies, network isolation with VPCs, and data encryption with AWS KMS, ensuring your GenAI applications are secure and compliant.
- DevOps & Automation: Master the automation of your GenAI workflows using AWS CI/CD tools (like AWS CodePipeline and AWS CodeBuild) for seamless integration, deployment, and monitoring.
[Course Agenda]
This course is logically structured to build your knowledge from the ground up:
- Section 1: AWS Certification and Exam Preparation
- Get a complete overview of the AWS certification landscape, the specifics of the Generative AI Professional exam, and how to set up your AWS account for hands-on learning.
- Build a solid foundation by reviewing the basic terminology and core concepts of AI, ML, and Generative AI, including the complete ML pipeline.
- This is the core of the course. We will review all essential AWS services, category by category, as they relate to the exam.
- 1. AI/ML: SageMaker, Bedrock, and other fully-managed services.
- 2. Management & Governance: Organizations, Systems Manager, CloudWatch, Config, CloudTrail, CloudFormation.
- 3. Security, Identity, Compliance: IAM, KMS, Secrets Manager, Macie.
- 4. Storage: S3, EFS, EBS, Storage Gateway.
- 5. Compute & Container: EC2, AutoScaling, ECS, EKS, Lambda, AWS Batch.
- 6. Networking & Content Delivery: VPC, Firewall, CloudFront, DirectConnect.
- 7. Database: RDS, Aurora, Redshift, DynamoDB, ElastiCache.
- 8. Application Integration: API Gateway, SQS, SNS, EventBridge, StepFunctions, MWSS.
- 9. Analysis: Lake Formation, Glue, Kinesis, Data Firehose, Apache Flink, Athena, EMR, OpenSearch, QuickSight.
- 10. Developer: CodeBuild, CodeDeploy, CodePipeline.
- Test your knowledge with a complete, original 75-question practice exam designed to simulate the real test environment.
- We’ll wrap up the course with key takeaways and final tips for exam day.
