(SCTP Module) Designing and Deploying Intelligent AI Systems: From Assistants to Multi-Agent Architectures
About This Course
This course provides a structured, end-to-end learning journey — from understanding how a single Artificial Intelligence (AI) assistant is built, to analysing how multiple agents collaborate to solve complex enterprise problems.
Learners explore the building blocks of intelligent AI assistants: how prompts are orchestrated into repeatable workflows, how Python constructs underpin AI task logic, and how to evaluate the reliability and correctness of assistant systems. No prior programming experience is required — the focus is on structured reasoning and workflow interpretation, not software development.
As a next step, learners scale that thinking to multi-agent systems — examining how task decomposition, agent role allocation, coordination logic, and memory management enable AI to tackle complex, multi-step processes. The course addresses the real-world challenges of enterprise deployment: monitoring, error recovery, human-in-the-loop design, performance considerations, and governance alignment.
What You'll Learn
2. Interpret basic Python constructs including variables, functions, and conditional logic as used in structured AI assistant workflows and task orchestration scripts.
3. Evaluate AI assistant logic for correctness, output reliability, and operational suitability within a given business context.
4. Differentiate between single-agent and multi-agent AI system designs, and explain the principles underlying multi-agent architectures.
5. Analyse task decomposition, agent role allocation, coordination logic, and memory and state management within complex multi-agent workflows.
6. Evaluate multi-agent systems for reliability, monitoring needs, error handling, and performance considerations in enterprise environments.
7. Identify human-in-the-loop design requirements and governance constraints affecting the responsible deployment of agentic AI solutions.
8. Apply a structured evaluation framework to assess multi-agent AI architectures against enterprise deployment and operational risk criteria.
Entry Requirements
1. Diploma / GCE A Level qualification or relevant work experience
2. Basic digital literacy and familiarity with workplace applications
3. Prior exposure to Generative Artificial Intelligence (AI) concepts and Prompt Engineering at a foundational level