COURSE CURRICULUM

In Year 1, the curriculum focuses on advanced theoretical foundations and specialized technological competencies. Machine Learning Basics introduces core concepts of supervised and unsupervised learning. Algorithms and Logical Algorithms deepen understanding of algorithmic design and analysis. Cryptography covers modern encryption methods and information security principles, while Optimization Algorithms and Operations Research address mathematical approaches to complex decision-making problems. Information Systems and Data Mining explore data-driven system design and knowledge extraction techniques. Computer Graphics introduces modeling and rendering techniques, and Advanced Inference Methods strengthen statistical and probabilistic reasoning skills. Advanced Software Architecture Patterns and Advanced XML Technologies focus on scalable system design and structured data management. NoSQL Databases examines modern data storage solutions. Sensor Networks and the Internet of Things addresses distributed systems and connected devices, and Parallel and High Performance Computing develops competencies in scalable and performance-oriented computation.In Year 2, students advance toward theoretical depth and applied innovation. Geometric Modelling, Coding Theory, and Theory of Neural Networks expand mathematical and computational perspectives. Models of Computation and Declarative Programming strengthen formal and programming paradigms knowledge. Visualization and Visual Analytics focuses on interpreting complex datasets, while the Data Science Lab provides hands-on project experience. Advanced Machine Learning and Text and Web Mining explore intelligent data-driven applications. Information Systems in Practice and Advanced Software Engineering emphasize real-world system development. The program concludes with a thesis demonstrating independent research competence.