Master of Computer Science in Applied Artificial Intelligence University of Niagara Falls Canada (UNF)

Program Description

Machine Learning This course covers key machine learning methodologies, including supervised (decision trees, neural networks, SVM), unsupervised, and reinforcement learning. It explores challenges, computational learning theory, and algorithm evaluation. Prerequisites include linear algebra, calculus, probability/statistics, and ideally, basic AI concepts. Advanced Databases A focus on algorithms and data structures crucial for modern database systems. It covers key aspects like buffer management, indexing, concurrency control, query optimization, and transaction management. The curriculum also explores database architectures, data models, and distributed database concepts, emphasizing security, integrity, and efficient data management techniques.

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