Course Information
Schedules
- 16 Dec 2025 (Tue) 9:30 AM - 5:00 PM
Registration period
15 Oct 2025 (Wed) - 15 Dec 2025 (Mon)
Price
HKD 3,000
(HK$3,000/ HK$2,700*
*Group discount for 2 participants or more)
(HK$3,000/ HK$2,700*
*Group discount for 2 participants or more)
Course Level
Study Mode
Duration
1 Day(s)
Language
Cantonese
Location
-
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Course Overview
Programme Highlights
- Want a 10x productivity boost? AI agents are the key.
- Our hands-on workshop teaches you to build AI agents that automate complex tasks—from data analysis and inquiry handling to research, HR and marketing.
- Designed for all backgrounds – no coding needed! Enrol now!
Course Objectives
- Distinguish AI agents from traditional AI automation.
- Build functional AI agents using low-code platforms to automate key business processes.
- Evaluate implementation considerations for AI agents, including data security, risk management, and cost-performance trade-offs.
- Develop a strategic framework for integrating AI agents into workflows.
What You’ll Learn
Course Outline
- 1. Agentic AI Fundamentals
A. Difference between AI Agents and Traditional AI
B. Introduction to technical concepts: Generative AI, AI workflow & Agentic AI
C. Business cases/ relevant news for inspiration
- 2. Guided Hands-on AI Agent Creation
A. Generative AI/ LLM application and prompt framework [Hands-on]
B. Platform Introduction (such as N8N, Dify.ai, Make.com) and Setup
C. Building AI Agent (I) – Hands-on
- • Intelligent Helpdesk Agent –
o Automate responses to internal policy Q&A for staff and external FAQs
o Implement escalation rules and knowledge base queries
- • Data Analyst Agent – Automate transformation of raw data into reports and actionable insights
- • Research Architect Agent – Synthesise complex information into structured proposals and briefs
D. Building AI Agent (II) – Instructor-led Demo
• Recruitment Automator Agent – Automate resume screening and intelligent interview scheduling
• Communications/Marketing Agent – Generate and schedule social media content and public announcements
- E. Group Testing and Review
Pair and test agents within groups
Peer feedback and optimization suggestions
- 3. Implementation Tips and Considerations
A. Analysis of AI Agent pros and cons
B. Data Security: Anonymization techniques and secure API usage
C. Risk Management: Human oversight protocols and failsafe mechanisms
D. Technical considerations
o Understanding platforms/tools: On-premise vs Cloud-based solutions
o Cost vs Performance trade-offs
- 4. Course Summary and Q&A
A. Recap of key skills and concepts learned
B. Open discussion to address various needs
C. Resource recommendations for further learning and development
