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.
Why Choose KORNERSTONE
- Accredited, practitioner-led, expert certificate trainers to provide high quality training
- Official training material included
- Practical, scenario-based learning – focus on application, not just theory
- Excellent Passing Rate
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
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
Dates & Locations
October 15, 2026
October 23, 2026
Exam & Certification
AWS Certified AI Practitioner.
Unlock new career possibilities with this AI certification. AWS Certified AI Practitioner validates in-demand knowledge of artificial intelligence (AI), machine learning (ML), and generative AI concepts and use cases. Sharpen your competitive edge and position yourself for career growth and higher earnings.
Who should earn AWS Certified AI Practitioner?
