Course Information
Schedules
- 24 Jul 2026 (Fri) 9:30 AM - 5:00 PM
Registration period
22 Jun 2026 (Mon) - 23 Jul 2026 (Thu)
Price
-
Course Level
Study Mode
Duration
1 Day(s)
Language
Cantonese
Location
2/F, Centre Point, 181 Gloucester Road, Wanchai, HK
Course Overview
Course description
In this course, you will learn about the fundamental concepts, methods, and strategies for using generative AI. You
will gain a solid understanding of use cases where generative AI can provide solutions and address business needs.
Additionally, you will learn about practical insights into technologies related to generative AI and how you can use
those technologies to solve real-world problems. By the end of the course, you will explore project planning and how
to discuss implementation of generative AI in your organization.
- • Course level: Fundamental
- • Duration: 1 day
Activities
- This course includes presentations, hands-on labs, demonstrations, and group exercises.
Course objectives
In this course, you will:
- • Summarize generative AI concepts, methods, and strategies
- • Discuss the appropriate use of generative AI and machine learning and their technologies
- • Describe how to use generative AI responsibly and safely
- • Recognize the types of generative AI solutions with specific use cases
- • Explain implementation and project planning of generative AI to your organization
What You’ll Learn
Day 1
Module 1: Introducing Generative AI
- • Generative AI explained
- • Foundation models
- • AWS generative AI services
- • Demo: Generative AI solution
Module 2: Exploring Generative AI Use Cases
- • Identify suitable use cases
- • Generative AI applications and use cases
- • Explore generative AI use case scenarios
- • Use case for class
Module 3: Essentials of Prompt Engineering
- • Introduction to prompt engineering
- • Prompt design best practices
- • Advanced prompting strategies
- • Model settings and parameters
- • Hands-on Lab: Optimizing Slogan Generation with Amazon Bedrock
Module 4: Responsible AI Principles and Considerations
- • Introduction to responsible AI
- • Core dimensions of responsible AI
- • Generative AI considerations
- • Hands-on Lab: Implementing Responsible AI Principles with Amazon Bedrock Guardrails
Module 5: Security, Governance, and Compliance
- • Security overview
- • Adverse prompts
- • Generative AI security services
- • Governance
- • Compliance
Module 6: Implementing Generative AI Projects
- • Introduction – Generative AI application
- • Define a use case
- • Select a foundational model
- • Improve performance
- • Evaluate results
- • Deploy the application
- • Demo: Amazon Q Business
Module 7: Integrating Generative AI into the Development Lifecycle
- • Introduction
- • Hands-on Lab: Capstone – Creating a Project Plan with Generative AI
Module 8: Course Wrap-up
- • Next steps and additional resources
- • Course summar
