6000

This intensive, graduate-level bridge course provides students with the essential knowledge and skills in programming and algorithmic thinking required for advanced study in computer science. Designed for students who lack a formal undergraduate background in computer science, the course emphasizes both theoretical concepts and practical applications. Topics include advanced programming paradigms, data structures, algorithm design techniques, complexity analysis, recursion, dynamic programming, graph algorithms, and optimization strategies. Through a combination of lectures, programming labs, and problem-solving assignments, students will develop the ability to design, implement, and analyze efficient algorithms, preparing them for the rigor of master’s-level coursework.

This graduate-level preparatory course provides students with the essential knowledge and skills in data architecture and data structures required for success in advanced computer science studies. Designed for students entering the Master of Science in Computer Science program without an undergraduate degree in computer science or equivalent background, the course bridges the gap by introducing core concepts of how data is organized, stored, and accessed in modern computing systems. Students will examine fundamental data structures, their time and space complexities, and their applications in solving computational problems. In parallel, the course explores principles of data architecture, including data modeling, database systems, data integration, and strategies for supporting enterprise-scale information management. Through a combination of theory, hands-on programming, and applied case studies, students will develop a strong foundation for subsequent graduate-level coursework.