Department of Computer Science

Data representation and computer arithmetic; logic functions and equations; description, analysis, and design of combinational and sequential circuits; functional properties of digital integrated circuits.

Advanced Operating Systems for graduate-level Computer Science students

This is a course that lets you appreciates and discover the nitty gritty details of how programming languages are designed and implemented. You will find out what are the underlying factors of how a specific programming language is designed. You will realize why some programming languages have some features and capabilities that you do not find in other programming languages. You will also realize that there is no such thing as a "supreme" or "elite" programming language, it's just that they are designed and built in a manner that suits the need of a specific type of users/programmers.

This course introduces the fundamental concepts, methods, and applications of Natural Language Processing (NLP), an interdisciplinary field that combines linguistics, artificial intelligence, and machine learning to enable computers to understand and generate human language. Students will explore the linguistic foundations of NLP, including morphology, syntax, and semantics, computational techniques for text representation, language modeling, information extraction, and other NLP tasks. The course covers both traditional NLP approaches and modern deep learning methods based on transformer architectures and large language models (LLMs).

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.