Master of Computer Science in Applied Artificial Intelligence

Course Overview This program offers an in-depth exploration of machine learning, advanced databases, and artificial neural networks. Students will gain a solid foundation in machine learning methodologies, dive into advanced database management systems, and develop expertise in deep learning architectures and applications in computer vision and natural language processing. Key Program Highlights Comprehensive coverage of machine learning techniques, including supervised, unsupervised, and reinforcement learning, along with computational learning theory and algorithm evaluation. Focus on advanced database algorithms, including buffer management, indexing, query optimization, and transaction management, with an emphasis on security and efficient data management techniques. In-depth study of artificial neural networks and deep learning, exploring network architectures, optimization techniques, and practical applications in computer vision and natural language processing. Prerequisites include linear algebra, calculus, probability/statistics, and basic AI concepts, providing a solid foundation for students in the field of data science and machine learning.