Build a Human–AI Workforce with Autonomous AI Agents
About This Course
Build a Human–AI Workforce with Autonomous AI Agents equips participants with practical skills to develop, deploy, and manage autonomous AI agents that collaborate with people and other agents in a digital workforce.
Participants will begin by building LLM-powered applications with Hermes Agent. They will learn how to configure autonomous agents, connect tools and APIs, define agent skills, and design intelligent workflows for business and operational tasks.
The course then explores Retrieval-Augmented Generation (RAG) and context engineering with OpenClaw. Participants will learn to provide agents with relevant knowledge, persistent memory, user preferences, and task context. They will apply contextual retrieval and memory-driven techniques to improve the accuracy, continuity, and usefulness of agent responses.
Finally, participants will use Paperclip to manage multi-agent teams. They will learn how to define agent roles, delegate tasks, coordinate workflows, monitor progress, and facilitate effective collaboration between human users and AI agents.
By the end of the course, participants will be able to build LLM applications, develop context-aware autonomous agents, and manage multi-agent systems that support workflow automation, business operations, customer engagement, software development, and organisational digital transformation.
What You'll Learn
LO1: Analyze LLM applications across a range of industries to identify their capabilities and limitations.
LO2: Establish the relationship between LLM design and Chatbot efficiency
LO3: Evaluate and improve RAG application effectiveness in product.
Topic 1: LLM applicatoins with Hermes Agent
Topic 2: RAG and Context Engineering with Openclaw
Toicic 3: Mullti Agent Management with Paperclip
Entry Requirements
Knowledge and Skills
• Able to operate computer functions with minimum Computer Literacy Level 2 based on ICAS Computer Skills Assessment Framework
• Minimum 3 GCE ‘O’ Levels Passes including English or WPL Level 5 (Average of Reading, Listening, Speaking & Writing Scores)
Attitude
• Positive Learning Attitude
• Enthusiastic Learner
Experience
• Minimum of 1 year of working experience.
Target Age Group: 21 to 65 years old