Department of Computer Science

Computer systems organization from a designer’s point of view; assembly language; addressing, stacks, argument passing, arithmetic operations, decisions, modularization; input/output operations and interrupts; memory hierarchy and cache memory; pipeline design techniques; super-scalar CPU architecture; parallel architectures.

Data Models: Relational Model. Database Management System, Data Definition and Manipulation Language. Data security, integrity, synchronization, protection, and recovery. Principle database systems and query languages.

Expansion and development of material introduced in CMSC 11; Processing files and linked-lists; Programming in the C language; Recursion; Systematic program development: top-down design and program verification.

This course is the second part of a two-part course on software engineering and will focus on the implementation, validation, evaluation and maintenance of software. The course emphasizes assurance in the software through various testing activities.

 This course covers an introduction to the fundamental principles and techniques of deep learning. Topics tackled include fundamental principles of artificial neural networks, neural network architectures, survey of advanced neural network architectures, and regularization techniques, among others.

This course covers an introduction to fundamental data structures, algorithms, and their analyses, which lie at the core of computing. The course provides a focus on abstract data types, analysis of algorithms, sorting algorithms, elementary data structures, hash tables, binary trees, heaps, and graphs.