Key Learning Areas
1. Introduction to Artificial Intelligence
• History and evolution of AI.
• Types of AI: Narrow, General, and Emerging.
• Common misconceptions about AI.
2. AI Technologies and Tools
• Machine learning and deep learning basics.
• Natural Language Processing (NLP).
• Robotics, computer vision, and intelligent automation.
3. Business Applications of AI
• AI in finance, auditing, and risk management.
• AI for customer experience and personalization.
• AI for fraud detection, cybersecurity, and compliance.
4. Data in AI Systems
• The role of data in training AI.
• Data governance and quality challenges.
• Big data, cloud, and analytics integration.
5. AI Governance and Ethics
• Ethical considerations in AI use.
• Bias, transparency, and accountability.
• Regulatory and compliance issues.
6. The Future of AI
• Emerging trends such as generative AI and quantum computing.
• Implications for jobs, industries, and society.