This revised edition offers significant updates that deepen understanding and promote hands-on learning: l Expanded AI Project Cycle: A structured exploration of problem scoping, data acquisition, modelling, evaluation and deployment. l Advanced AI Domains: Coverage of Machine Learning, Deep Learning and real-world applications in fields like Computer Vision and Natural Language Processing. l Ethical AI Frameworks: Emphasis on fairness, bias reduction and responsible innovation. l No-Code AI Tools: Practical, project-based exposure using intuitive tools that make AI accessible to all. l Interactive Labs: A new and exciting addition—Interactive Labs—invite students to learn while having fun through guided digital experiments, simulations and challenges. These labs turn concepts into experiences, encouraging creativity and deeper understanding. l Use Case Walkthroughs: Step-by-step examples of AI in action across sectors such as education, healthcare and sustainability. l AI-Driven Social Impact Projects: Opportunities to create AI solutions addressing real-world issues and promoting innovation with purpose.

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