Description: Foundations of AI and Machine Learning for Modern Computing introduces the core concepts that enable intelligent systems to analyze data, learn from patterns, and make informed decisions. It covers essential topics such as algorithms, data structures, probability, statistics, neural networks, and model evaluation techniques. The subject emphasizes how machine learning models are trained, tested, and deployed in real-world computing environments. Applications range from natural language processing and computer vision to recommendation systems and predictive analytics. By understanding these foundations, learners gain the skills needed to design scalable, efficient, and intelligent solutions that power modern digital technologies.