- 提示:
- 課程詳情以機構網站為準。
課程資料
報名日期*
全年招生
價錢
-
課程級別
學習模式
修業期
1 日
教學語言
廣東話
地點
Kornerstone
*提示: 以上時間表僅供參考，以機構網站為準。
課程簡介
Overview
In this course, you will:
- Learn fundamental concepts, techniques, and strategies for generative AI
- Gain insight into real-world use cases where generative AI can solve business challenges
- Explore practical technologies and architectures behind generative AI, and how to apply them in real settings
- Develop skills in project planning, implementation, and organizational adoption of generative AI
By the end of this course, you will be able to:
- Discuss how generative AI can be integrated into your organization’s initiatives
- Define a project roadmap with clear steps and stakeholder alignment
- Evaluate responsible AI principles, security risks, and governance in generative systems
Stay ahead in digital economy: global tech leaders are investing billions in cloud, AI, and data, and demand for certified Data & AI professionals is rising rapidly. Get certified and positioned as the candidate organizations seek.
Skills Covered
In this course, you will learn to:
- 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
Target Audience
This course is intended for those with limited prior knowledge of generative AI:
- Business analyst
- IT support
- Marketing professional
- Product or project manager
- Line-of-business or IT manager
- Sales professionals
課程內容
Course Curriculum
Module 1: Introducing Generative AI
- Generative AI explained
- Foundation models
- AWS generative AI services
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 of 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
- Amazon Q Business (guided demo)
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 summary
