Bachelor of Science in Computer Science

This is a calculus-based physics course covering the fundamental principles of mechanics. It concentrates on the conservation of energy, the particle motion, the collisions, the rotation of solid bodies, simple machines and on the fluid mechanics. The focus lies on the resolution of one and twodimensional mechanical problems.

This course is intended to be taken with Physics 110. It primarily includes experiments on classical mechanics. Particular emphasis is placed on laboratory technique, data collection and analysis and on reporting.

This course covers techniques and applications of integration, transcendental functions, infinite sequences and series and parametric equations.

This course covers partial differentiation, multiple integrals, line and surface integrals, and threedimensional analytic geometry.

This course covers systems of linear equations, linear independence, linear transformations, inverse of a matrix, determinants, vector spaces, eigenvalues, eigenvectors, and diagonalization.

The course introduces principles of statistics and probability for undergraduate students in Engineering. The course covers the basic concepts of probability, discrete and continuous random variables, probability distributions, expected values, joint probability distributions, and independence. The course also covers statistical methods and topics including data summary and description techniques, sampling distributions, hypothesis testing, and regression analysis.

This course is an introduction to object-oriented programming principles and techniques using Java. Topics include Java elementary programming, and Java object-oriented features such us methods, objects, classes, access modifiers, constructors, immutable objects & classes, abstraction, encapsulation, inheritance, polymorphism, dynamic binding, object castings, abstract and interface classes, and exception handling.

This course covers the basic discrete mathematical structure, methods of reasoning, and counting techniques: sets, equivalence relations, propositional logic, predicate logic, induction, recursion, pigeon-hole principle, permutation and combinations.

This course introduces data structures and various fundamental computer science algorithms. The course covers abstract data-type concepts, stacks, queues, lists, and trees. Several sorting and searching algorithms are covered. Additional topics include an introduction to graphs and their implementation and running time and time complexity measurement.

This course provides a programmer's view of the execution of programs in computer systems. Topics covered include instruction sets, machine-level code, assembly language, performance evaluation and optimization, memory organization and management, address translation, and virtual memory.

Pre-requisite(s): CSCI 215 and STAT 346
This course provides an introduction to the different sub-areas of Artificial Intelligence (AI). In addition, students learn basic concepts, methods and algorithms of AI and how they can be used to solve practical AI problems. The topics include classical and adversarial search & heuristic, knowledge representation, probabilistic reasoning, convex optimization methods, Bayesian methods, reinforcement learning, and supervised and unsupervised learning techniques. Particular focus will be placed on real-world applications of the material.

This course provides an introduction to data science and highlights its importance in real world context. Topics include data science concepts, project lifecycle, tools & programming environment, fundamentals of Python programming, numerical processing, data visualization, exploratory data analysis, data preprocessing, parameter optimization, model performance evaluation, and applications of machine learning algorithms in Python (i.e., Naïve Bayes, k-Nearest Neighbors, Linear/Multiple/Logistic Regressions, Decision Trees, and Clustering Applications), natural language processing, and real-world data science case studies.

This course introduces the design and analysis principles for various algorithms. The topics covered include searching algorithms, dynamic programming, greedy algorithms, Huffman coding, graph traversing algorithms, shortest path algorithms, linear programming, and NP-completeness.

This course is an introductory course on database management systems. The goal of the course is to present a comprehensive introduction to the use of data management systems. Some of the topics covered are the following: The Entity-Relationship Model, the Relational Data Model, the SQL language, the database design, and the database integrity and security.

This course covers the principles, components, and design of modern operating systems, focusing on the UNIX platform. Topics include system structure, process concept, multithreaded programming, process scheduling, synchronization, atomic transaction, deadlocks, memory management, and file system.

The course provides an introduction to the theory and practice of compilation. Topics include compiler architecture, components, phases, software tools, lexical roles and specifications, regular expressions, syntax roles and specifications, context-free grammars, top-down parsing, bottom-up parsing, LR parsers & parse trees, syntax directed translation, syntax tree, abstract syntax tree, and finite automata.

This course is an introduction to basic concepts in the design of programming languages. The course focuses on programming languages within the functional and logic programming paradigms such as Scheme and Prolog. Topics include history of programming languages, language design criteria, functional programming, syntax, logic programming, semantics, and object-oriented principles.

Co-requisite(s): CENG 336
This course covers details of microprocessor design including the instruction set architecture, memory design, and data path and control design. The course also emphasizes memory performance related concepts such as associativity and multi-level caching. Additional topics include virtual memory and performance speed-up techniques using pipelining, multithreading, and multiprocessing.

Co-requisite(s): CENG 335
This course covers modern computer system architecture and computer design principles. A Hardware Description Language is used to design basic components of a microprocessor datapath and control. Additional topics covered include Adders, MUX, Counters, ALU, registers/shift registers, RAM, pipelining, and cache memory.

This course examines in detail the software development process. Topics include concepts such as software processes, software specification, software design implementation, software testing, software evolution, and software reuse.

This course provides students with hands on training on design, troubleshooting, modeling and evaluating of computer networks. Topics include network addressing, Address Resolution Protocol (ARP), basic troubleshooting tools, IP routing, and route discovery. Additionally, student will perform network modeling, simulation, and analysis using Packet tracer and WireShark analyzer.

Co-requisite(s): CSCI 462
This course provides students with hands on training on design, troubleshooting, modeling and evaluating of computer networks. Topics include network addressing, Address Resolution Protocol (ARP), basic troubleshooting tools, IP routing, and route discovery. Additionally, student will perform network modeling, simulation, and analysis using Packet tracer and WireShark analyzer.

Examines information security services and mechanisms in network context. Topics include symmetric and asymmetric cryptography; message authentication codes, hash functions and digital signatures, digital certificates and public key infrastructure; access control including hardware and biometrics; intrusion detection and securing network-enabled applications including e-mail and web browsing.

The course requires seniors to work in small teams to solve significant problems. Over the duration of CSCI 492 and CSCI 493, students design, implement, and evaluate a solution to the problem in conjunction with a faculty advisor. The course reinforces programming principles and serves as a capstone for computing knowledge obtained in the BSCS and BAIDS curricula. The recognition of the ethical and legal principles are also aspects of the course.

The course requires seniors to work in small teams to solve significant problems. Over the duration of CSCI 492 and CSCI 493, students design, implement, and evaluate a solution to the problem in conjunction with a faculty advisor. The course reinforces programming principles and serves as a capstone for computing knowledge obtained in the BSCS and BAIDS curricula. The recognition of the ethical and legal principles are also aspects of the course.

This course introduces fundamentals of robot modelling and control. Topics include forward and inverse kinematics, Jacobians, trajectory design and configuration space, motion planning, mobile robot sensors and actuation and computer vision.

This course is an introduction to basic concepts in the design of programming languages. The course focuses on programming languages within the functional and logic programming paradigms such as Scheme and Prolog. Topics include history of programming languages, language design criteria, functional programming, syntax, logic programming, semantics, and object-oriented principles.

This course introduces computer graphics and drawing algorithms in a laboratory environment. The topics covered include graphics output primitives and their implementations, two-dimensional and three-dimensional geometric transformations and viewing, hierarchical modeling, computer animation, spline representations, visible-surface detection methods, illumination models, and surface-rendering methods, and texturing and surface-detail methods.

This course is an introduction to parallel programming principles and techniques. Topics include parallel computing memory architecture, memory organization, parallel programming models, parallel program design, performance evaluation, thread-based parallelism, process-based parallelism, message passing, asynchronous programming, and heterogeneous programming.

This course provides an introduction to and overview of the field of human-computer interaction (HCI). The topics include usability principles, predictive evaluation, design management processes, graphic design, understanding user's requirements gathering, task analysis, handling errors & help, prototyping & UI software, interaction styles, user models, evaluation, and universal design.

From smart phones, to multi-core CPUs and GPUs, to the world's largest supercomputers and web sites, parallel processing is ubiquitous in modern computing. The goal of this course is to provide a deep understanding of the fundamental principles and engineering trade-offs involved in designing modern parallel computing systems as well as to teach parallel programming techniques necessary to effectively utilize these machines. Because writing good parallel programs requires an understanding of key machine performance characteristics, this course will cover both parallel hardware and software design.

The course introduces the fundamentals of signal processing and communications for multimedia applications. It covers various topics relating to audio, image and video processing, storage and transmission. It discusses the human visual and hearing systems and relates them to image and sound digitization processes. The course also covers various lossless and lossy methods for audio, image and video compression. In addition, it gives the student hands on experience on applying the presented processing techniques using suitable software packages.

This course is a survey of information security considerations as they apply to information systems analysis, design, and operations. Topics include information security vulnerabilities, threats, and risk management. Furthermore, the course introduces several cryptographic algorithms in addition to the privacy and secrecy of statistical databases and e-government applications.

This course gives instructors the opportunity to cover the latest developments and contemporary issues in computing. Instructors will provide a detailed course outline at the beginning of the semester.

Undergraduate research under the guidance of an engineering faculty member for juniors and seniors. Fixed credit hours; 3 credits are assigned, this is equivalent to a minimum of 9 hours of research time per week; a pass/fail grade is to be used. Student will be engaged in a creative research project at the discretion of the faculty member. The course is open to all engineering students.