Build production-ready generative AI systems in 2026.
This advanced three-day AWS Generative AI training equips developers with hands-on skills to design, build and integrate generative AI applications using foundation models, enterprise patterns, retrieval augmentation and agentic approaches on AWS.
- Why get trained: Gain practical expertise in building and deploying production-ready generative AI solutions using AWS services such as foundation models, vector search, agent frameworks and integration patterns.
- Why it matters: Advanced generative AI capabilities help professionals deliver AI solutions that power innovation, automate complex tasks and support strategic business outcomes in cloud environments.
- Who should attend: Software developers, cloud engineers and AI practitioners with development experience who want to expand their skills in advanced generative AI architectures on AWS.
Advance your AI development skills and build scalable generative AI systems – HRDC Claimable.Â
Overview
Master the implementation of production-ready generative AI solutions on AWS.
The Advanced Generative AI Development on AWS course addresses the needs of organizations embarking on their generative AI journey and how to build comprehensive generative AI strategies that align with broader business objectives.
This advanced 3-day instructor-led training builds expertise across the entire generative AI stack – from foundation models to enterprise integration patterns. In addition, you will learn about advanced data processing techniques, vector database implementation and retrieval augmentation, sophisticated prompt engineering and governance, agentic AI systems and tool integration, AI safety and security measures, performance optimization and cost management strategies, comprehensive monitoring and observability solutions, testing and validation frameworks.
The course structure follows AWS’s proven model for generative AI adoption, progressing from experimentation to production-ready implementations.
Skills Covered
In this course, you will learn to:
- Develop production-ready generative AI solutions on AWS that meet enterprise requirements for security, scalability, and reliability
- Evaluate and select appropriate foundation models for specific business use cases, including benchmarking performance and implementing dynamic model-selection architectures
- Design and implement foundation-model systems with circuit breakers, cross-region deployment, and degradation strategies
- Build comprehensive data-processing pipelines for multi-modal inputs, including validation workflows and optimization techniques
- Implement sophisticated vector-database solutions using Amazon Bedrock Knowledge Bases, OpenSearch, and hybrid approaches for effective retrieval augmentation
- Create and manage advanced prompt-engineering frameworks, including chain-of-thought reasoning and enterprise-wide prompt-governance systems
- Explain components of Agentic AI frameworks and Amazon Bedrock AgentCore
- Implement comprehensive AI safety and security controls, including content filtering, privacy preservation, and adversarial testing mechanisms
- Optimize performance and manage costs through token-efficiency strategies, batching implementations, and intelligent caching systems
- Design and implement comprehensive monitoring and observability solutions for foundation-model applications
- Create systematic testing and validation frameworks for continuous quality assurance of AI applications
- Integrate generative AI solutions within enterprise environments using secure, compliant, and scalable architectural patterns
Prerequisites
We recommend that attendees of this course have:
- AWS Technical Essentials
- Generative AI Essentials on AWS
- 2 or more years of experience building production grade applications on AWS or with opensource technologies, general AI/ML or data engineering experience
- 1 year of hands-on experience implementing generative AI solutions
Target Audience
This course is intended for those with:
- Software developers
- Technical Professionals
Module 1: Foundation Model Selection and Configuration
- Enterprise foundation model evaluation framework
- Dynamic model-selection architecture patterns
- Resilient foundation-model system designs
- Cost optimization and economic modeling
- Comprehensive data validation and quality assurance
- Multi-modal data processing pipelines
- Input optimization and performance enhancement
Module 3: Vector Databases and Retrieval Augmentation
- Enterprise vector database architecture
- Advanced document processing and chunking strategies
- Sophisticated retrieval system implementation
- Hands-on Lab: Develop Retrieval Augmented Generation (RAG) applications with Amazon Bedrock Knowledge Bases
- Advanced prompt-engineering frameworks
- Complex prompt-orchestration systems
- Enterprise prompt governance and management
- Hands-on Lab: Develop conversation patterns with Amazon Bedrock APIs
- Agentic AI Frameworks
- Amazon Bedrock AgentCore
Module 6: AI Safety and Security
- Comprehensive content safety implementation
- Privacy-preserving AI architecture
- AI governance and compliance frameworks
Module 7: Performance Optimization and Cost Management
- Token efficiency and cost optimization
- High-performance system architecture
- Intelligent caching systems implementation
- Hands-on Lab: Building Secure and Responsible Gen AI with Guardrails for Amazon Bedrock
- Foundation model monitoring systems
- Business impact and value management
- AI-specific troubleshooting and diagnostics
- Comprehensive AI evaluation frameworks
- Quality assurance and continuous improvement
- RAG system evaluation and optimization
Module 10: Enterprise Integration Patterns
- Enterprise connectivity and integration architecture
- Secure access and identity management
- Cross-environment and hybrid deployments
Module 11: Course wrap-up
- Next steps and additional resources
- Course summary
Dates & Locations
August 10, 2026 - August 12, 2026
August 10, 2026 - August 12, 2026
November 16, 2026 - November 18, 2026
November 16, 2026 - November 18, 2026
Exam & Certification
AWS Certified Generative AI Developer – Professional showcases advanced technical expertise in building and deploying production-ready AI solutions using AWS Services like Bedrock. Perfect for developers with 2+ years of cloud experience looking to advance their careers.
For organizations investing in AI initiatives, this certification provides a reliable way to identify and verify developers who can move beyond proofs-of-concept to build production-grade generative AI solutions that deliver tangible business results while maintaining security and cost efficiency.
Training & Certification Guide
Frequently Asked Questions
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All courses are HRD Claimable.
Get in touch with our team via the form or WhatsApp us on +6011-5119 6631
