Cloud computing has emerged as a cornerstone of modern digital infrastructure, significantly influencing how educational institutions deliver content, manage resources, and foster collaboration. However, despite its potential, barriers such as unequal access, limited faculty expertise, and lack of standardized curricula hinder its effective integration into academic environments. This paper explores a transformative approach to cloud computing education by leveraging artificial intelligence (AI) and data science to enhance accessibility, engagement, and collaborative learning. The study presents a framework that integrates AI-powered adaptive learning systems, predictive analytics, and intelligent tutoring to personalize educational content delivery based on learners' performance, preferences, and learning styles. Through the application of data science methodologies, large-scale academic data is analyzed to identify learning gaps, optimize curriculum design, and predict student outcomes. The integration of AI-driven virtual laboratories and cloud-based simulation platforms further allows students to gain hands-on experience in a scalable and cost-effective manner, eliminating geographical and financial constraints. Moreover, AI facilitates intelligent collaboration tools that enable real-time feedback, peer-to-peer learning, and instructor-student interactions, thereby enriching the learning experience. Case studies from various higher education institutions implementing AI-enhanced cloud education platforms demonstrate improved learning outcomes, increased student engagement, and greater institutional efficiency. The research also highlights the role of AI in automating administrative tasks such as resource allocation, grading, and progress tracking, allowing educators to focus more on pedagogical strategies. This paper concludes with policy recommendations and best practices for implementing AI and data science in cloud computing education, emphasizing the need for cross-sector partnerships, faculty training, and equitable access to technology. The proposed model aims to not only democratize cloud computing education but also cultivate a data-literate academic workforce capable of thriving in the evolving digital economy.