Overview
As the capabilities of Generative AI mature, the industry focus is shifting from simple prompt engineering toward the development of autonomous, goal-driven AI agents. These agentic systems combine large language models (LLMs) with reasoning, memory, planning, and tool execution to perform complex tasks independently — from enterprise automation to customer support and domain-specific decision-making.
However, while interest in agentic AI grows, most practitioners lack the expertise to architect scalable, resilient, and secure agentic AI systems. Current LLM-focused training often emphasizes model usage and tuning, but not system design or deployment at scale — creating a significant talent gap.
This course is designed to bridge that gap by equipping participants with advanced skills in:
- Designing logical and physical architectures for full-stack agent-based systems.
- Implementing multi-agent collaboration strategies and real-time system interoperability.
- Selecting and applying appropriate agentic AI frameworks - such as LangChain, AutoGen, OpenAI assistants, and Claude - for building and integrating intelligent agents into enterprise systems.
By combining hands-on experience with system-level thinking, this course prepares professionals to lead the architecture, design and implementation of next-generation AI solutions driven by autonomous, multi-agent systems.
This course is part of the Software Systems series and Graduate Certificate in Architecting AI Systems series offered by NUS-ISS.