- 提示:
- 課程詳情以機構網站為準。
課程資料
時間表*
- 2026年11月30日(週一) 上午 9:30 - 下午 5:00
報名日期*
2026年9月4日(週五) - 2026年11月29日(週日)
價錢
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)
課程級別
學習模式
修業期
1 日
教學語言
廣東話
地點
HKPC Building 78 Tat Chee Avenue Kowloon
*提示: 以上時間表僅供參考，以機構網站為準。
課程簡介
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.
課程內容
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
