Professional Training · Generative AI & Agentic AI Track
Advanced Generative AI Development on AWS
A three-day advanced course spanning foundation models through to enterprise integration. It covers evaluating and selecting foundation models, designing systems with circuit breakers and considered deployment strategies, building multi-modal data pipelines and vector database solutions on Amazon Bedrock Knowledge Bases, advanced prompt engineering, agentic frameworks, AI safety and security controls, performance and cost optimisation, observability and validation testing.
Authorised Instructors
Hui Liang
Chief Digital Officer
- Generative AI Developer – Professional
- Security – Specialty
- Solutions Architect – Professional
- CloudOps Engineer – Associate
- +5 more
Gabriel Wong
Technical Programme Manager
- Generative AI Developer – Professional
- DevOps Engineer – Professional
- Developer – Associate
- Solutions Architect – Associate
- +2 more
Any of these AWS Authorised Instructors may deliver this class, depending on the scheduled run. Trainers confirmed on enrolment.
Who Should Attend
- Software Developers: Developers building generative AI features for production.
- Cloud Engineers: Engineers running generative AI workloads at enterprise scale.
- AI Practitioners: Practitioners with development experience deepening their architecture skills.
- Solutions Architects: Architects designing enterprise generative AI systems.
Prerequisites
This is an advanced course. To get the most from it, you should have:
Completion of AWS Technical Essentials and Generative AI Essentials on AWS, or equivalent knowledge.
Two or more years building production-grade applications on AWS or open-source technologies.
General AI, machine learning or data engineering experience.
At least one year of hands-on experience implementing generative AI solutions.
Learning Objectives
In this course, you will learn to:
Select foundation models: Evaluate and choose models that fit the business use case.
Design resilient systems: Apply circuit breakers and deployment strategies to model-backed services.
Build retrieval solutions: Implement vector databases using Amazon Bedrock Knowledge Bases.
Engineer prompts systematically: Create advanced prompt engineering frameworks.
Apply safety and security: Put AI safety controls and security guardrails in place.
Operate at scale: Optimise performance and cost, and design monitoring, observability and testing.
Certification
A MY Code Campus certificate of completion is awarded for Advanced Generative AI Development on AWS.
In-person in Kuala Lumpur or live virtual. Team & enterprise rates available.
