WSQ Multi AI Agents Courses

A single AI agent can only carry so much. Multi-agent systems break a large goal into roles — a researcher, a writer, a reviewer, a coder, a tester — and let specialised agents work in parallel, hand off results and check each other's output. The pattern mirrors how human teams operate, and it consistently outperforms one general-purpose agent on complex, multi-step work.

Our WSQ Multi AI Agents Courses teach how to design, build and operate these systems with the frameworks the industry has standardised on — AutoGen, CrewAI, Google Agent Development Kit and related orchestration tooling. Participants learn to decompose a goal into agent roles, define how agents communicate and hand off, manage shared memory and context, add human-in-the-loop checkpoints, and deploy the result as a running application rather than a notebook demo.

The catalogue spans practical build courses and applied workflows: content-creation pipelines where research, drafting and editing agents collaborate, autonomous agent teams that operate with minimal supervision, agent management and orchestration, and vibe-coded multi-agent systems for developers who want to assemble them quickly with AI assistance. Courses also cover the operational realities that decide whether a multi-agent deployment survives contact with production — controlling cost and token spend, preventing runaway loops, tracing failures across agents, and knowing when a simpler single-agent design is the better answer.

What you will learn

• Designing multi-agent architectures - roles, responsibilities, handoffs and communication
• Building agent teams with AutoGen, CrewAI, Google ADK and related frameworks
• Orchestrating collaborative workflows such as research, drafting, review and approval
• Managing shared context, memory and state across cooperating agents
• Adding human-in-the-loop checkpoints, guardrails and approval gates
• Deploying, monitoring, tracing and cost-controlling multi-agent systems in production

Who should attend

Developers and AI engineers building agentic applications, data and automation specialists designing intelligent workflows, technical leads evaluating agent frameworks, and product and operations managers who need to understand what multi-agent systems can realistically deliver.

Funding

These are WSQ, CASL and IBF funded courses. Eligible Singaporeans and PRs can enjoy SkillsFuture funding subsidies, and SkillsFuture Credit may be used to offset the nett course fee. Company-sponsored participants may also be eligible for SkillsFuture Enterprise Credit (SFEC) and absentee payroll. Please refer to each course page for the funding schemes that apply.