Introduction to AI Course
Course Provider - Smart Cities Academy
Course Provider - Smart Cities Academy
Qualification - Smart Cities Academy Micro-credential
Qualification - Smart Cities Academy Micro-credential
Duration - 3 hours
Duration - 3 hours
Language - English (can be customized for Face-to-Face)
Language - English (can be customized for Face-to-Face)
Format - Online On Demand, Online Face to Face*, In Person Face to Face*
Language - English (can be customized for Face-to-Face)
Target Audience - Anyone seeking a structured understanding of Responsible AI and its strategic, ethical, and governance implications.
Target Audience - Anyone seeking a structured understanding of Responsible AI and its strategic, ethical, and governance implications.
Cost - USD245
Cost - USD245
Prerequisites - There are no prerequisites for this course
Prerequisites - There are no prerequisites for this course
Prerequisites - There are no prerequisites for this course
Outline
| MODULE 1 - Foundations of Artificial Intelligence MODULE 2 - AI Ethics and Responsible AI MODULE 3 - Introduction to AI Governance Frameworks MODULE 4 - Developing an AI Strategy MODULE 5 - Building a Risk-Aware AI Culture, and Assessment |
Outline
| MODULE 1 - Foundations of Artificial Intelligence MODULE 2 - AI Ethics and Responsible AI MODULE 3 - Introduction to AI Governance Frameworks MODULE 4 - Developing an AI Strategy MODULE 5 - Building a Risk-Aware AI Culture, and Assessment |
Learning Outcomes
- Explain key AI concepts, including LLMs and computer vision systems.
- Differentiate between types of AI and common misconceptions.
- Describe core AI ethical principles and why they matter in real-world deployment.
- Identify major AI governance frameworks at global, regional, and national levels.
- Understand AI risk categories across the lifecycle.
Learning Outcomes
- Explain key AI concepts, including LLMs and computer vision systems.
- Differentiate between types of AI and common misconceptions.
- Describe core AI ethical principles and why they matter in real-world deployment.
- Identify major AI governance frameworks at global, regional, and national levels.
- Understand AI risk categories across the lifecycle.
