Shakia Riggins/Baffour Osei
New!
Copyright 2028 | {{checkPublicationMessage('Available 30 October 2026', '2026-10-30T00:00:00+0000')}}
Copyright 2028 | {{checkPublicationMessage('Available 30 October 2026', '2026-10-30T00:00:00+0000')}}
Available 30 October 2026
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Copyright 2028 | {{checkPublicationMessage('Available 30 October 2026', '2026-10-30T00:00:00+0000')}}
Available 30 October 2026
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About This Product

What if students could move beyond simply using AI tools to actually understanding, developing, and deploying them responsibly? "Artificial Intelligence and Machine Learning" by Riggins and Osei is a complete instructional resource that guides learners from core concepts to the ethical design, development, and deployment of real AI systems. Designed to help students overcome common classroom challenges, including black-box thinking, ethical blind spots, technical barriers, and the gap between theory and practice, it emphasizes Explainable AI, embedded ethics, concept-first mathematics, and flexible pathways from no-code tools to Python. With a project-build approach, its content engages students in creating a meaningful AI solution across the full development lifecycle. Supported by rich instructor resources, assessments, and case studies, this resource makes AI education accessible, rigorous, and relevant across disciplines.