Course Title: Neural NetworksFull Marks: 45 + 30Course No: C.Sc. 543Pass Marks: 22.5 + 15Nature of the Course: Theory + LabCredit Hrs: 3 Course Description: This course deals with resembling the conscious behavior of brain in an artificially connected logical nodes that can learn itself in a supervised and unsupervisedRead More →

Course Title: Object-Oriented Software EngineeringFull Marks: 45 + 30Course No: C.Sc. 539Pass Marks: 22.5 + 15Nature of the Course: Theory + Case Studies+ ProjectCredit Hrs: 3 Course Objectives: This course aims to give students both a theoretical and a practical foundation in Object -Oriented software engineering. In the theoretical part,Read More →

Course Title: Advanced Database ConceptsFull Marks: 45 + 30Course No: C.Sc. 563Pass Marks: 22.5 + 15Nature of the Course: Theory + LabCredit Hrs: 3 Course Objectives: To study the further advanced database techniques beyond the fundamental database techniques which were covered in the graduate level course, and thus, to acquaintRead More →

Course Title: Compiler OptimizationFull Marks: 45 + 30Course No: C.Sc. 558Pass Marks: 22.5+15Nature of the Course: Theory + LabCredit Hrs: 3 Course Description: Theoretical and practical aspects of building optimizing compilers that effectively exploit modern architectures. The course will begin with the fundamentals of compiler optimization, and will build uponRead More →

Course Title: Computational GeometryFull Marks: 45+30Course No: C.Sc. 562Pass Marks: 22.5+15Credit Hours: 3Nature of the course: Theory +Lab Course Description: Computational Geometry is the study of the representation and storage of geometric data and relationships, and the design & implementation and analysis of computational algorithms that operate on geometric dataRead More →

Course Title: Machine LearningFull Marks: 45 + 30Course No: C.Sc.561Pass Marks: 22.5+15Nature of the Course: Theory + LabCredit Hrs: 3 Course Description: This course provides a broad introduction to machine learning and statistical pattern recognition. Topics include: supervised learning (generative/discriminative learning, parametric/non-parametric learning, neural networks, support vector machines); unsupervised learningRead More →

Course Title: Seminar IIFull Marks: 25Course No: C.Sc. 560Pass Marks: 12.5Nature of the Course: SeminarCredit Hrs: 1 Course Description: The seminar-II is of full marks 25 offered in the curriculum of the M. Sc. first year second semester. A student pursuing the seminar prepares a seminar report and presents theRead More →

Course Title: Systems ProgrammingFull Marks: 45+30Course Code: C.Sc. 565Pass Marks: 22.5+15Credit Hours = 3Nature of the course: Theory +Lab Course Description: This course will introduce the design and implementation of machine dependent, as well as machine independent aspects of assembler, loader, linker, microprocessor and some aspects of compiler. A projectRead More →

Course Title: Web Systems and AlgorithmsFull Marks: 45 + 30Course No: C.Sc. 559Pass Marks: 22.5+15Nature of the Course: Theory + LabCredit Hrs: 3 Course Description: This course covers the Internet systems research including the intelligent web, search engine architecture and algorithms, information retrieval, crawling, text analysis, personalization and context, collaborativeRead More →

Course Title: Remote Sensing and GISFull Marks: 45 + 30Course No: C.Sc. 624Pass Marks: 22.5+15Nature of the Course: Theory + LabCredit Hrs: 3 Course Description: This course covers the concepts and principles of remote sensing, global navigation satellite System (GNSS) and GIS Course Contents: Unit 1: Concept of Remote SensingRead More →