Human-computer interaction and user-centered design in the context of software engineering. Examines the fundamental principles of human-computer interaction. Includes evaluating a system's usability based on well-defined criteria; user and task analysis, as well as conceptual models and metaphors; the use of prototyping for evaluating design alternatives; and physical design of software user-interfaces, including windows, menus, and commands.Prerequisite: CS 2110 or CS 2100 with a grade of C- or better

This course covers topics on the computer architecture abstraction hierarchy ranging from a step above silicon to a step below modern programming languages. Students in this course will learn to write low-level code in C and Assembly, how data is stored in memory, the basics of hardware design from gates and registers through general-purpose computers, and legal, ethical, and security issues related to these topics. CS 1100 - CS 1199 and either familiarity with Java, C++, or another C-like language, or concurrent enrollment in CS 2100

This course covers the principles of secure network communications and the application of network security. Topics include: attack types, attack surfaces, attack phases, network security devices.(a)symmetric key encryption, cryptographic hash function, authentication/identification techniques, key distribution, and data integrity assurance. Also, currently used security mechanisms and protocols will be discussed. Prerequisite: CS 3710 with a grade of C- or better

A second course in computer systems, this course will explore a more realistic model of processors and how they and the operating system work together to provide various functionality we depend on as application programmers. Course topics include permission models, system architecture, concurrency, virtual memory, cryptographic primitives, and TCP/IP networking. Prereq CS 2100 and CS 2130 with a grade of C- or better

Investigates the architectural foundations of the various cloud platforms, as well as examining both current cloud computing platforms and modern cloud research. Student assignments utilize the major cloud platforms. Prerequisite: CS 2150 or CS 3140 with a grade of C- or better

Mobile computing devices have become ubiquitous in our communities. In this course, we focus on the creation of mobile solutions for various modern platforms, including major mobile operating systems. Topics include mobile device architecture, programming languages, software engineering, user interface design, and app distribution. Prerequisite: CS 2150 or CS 3140 with a grade of C- or better

Analyzes process communication and synchronization; resource management; virtual memory management algorithms; file systems; and networking and distributed systems. Prerequisite: CS 3330 or (CS 2501 COA 2 & CS 2150) or (CS 3130 and CS 3100) with a grade of C- or better or ECE 3430 or ECE 3502 Embedded Computing & Robotics 2

The goal of this course is to understand the fundamental limits on what can be efficiently computed. These limits reveal properties about information, communication, and computing, as well as practical issues about how to solve problems. Introduces computation theory including grammars, automata, and Turing machines. Prereq: CS 4102 or CS 3100 with a grade of C- or better

Viruses, worms, and other malicious software are an ever-increasing threat to computer systems. There is an escalating battle between computer security specialists and the designers of malicious software. This course provides an essential understanding of the techniques used by both sides of the computer security battle. Prerequisite: CS 3710 with a grade of C- or better

Course content varies by section and is selected to fill timely and special interests and needs of students. See CS 7501 for example topics. May be repeated for credit when topic varies. Prerequisite: Instructor permission.

Analyzes modern software engineering practice for multi-person projects; methods for requirements specification, design, implementation, verification, and maintenance of large software systems; advanced software development techniques and large project management approaches; project planning, scheduling, resource management, configuration control, and documentation. Prerequisite: CS 2150 or CS 3140 with a grade of C- or better

A second course in computing with an emphasis on foundational data structures and program analysis. The course provides a introduction to object oriented programming and the Java programming language, concurrency, and inheritance / polymorphism. Additionally, foundational data structures and related algorithms / analysis are studied. These include lists, stacks, queues, trees, hash tables, and priority queues. Prereq: CS 1100 - CS 1199

An introduction to machine learning: the study of algorithms that improve their performance through experience. Covers both machine learning theory and algorithms. Introduces algorithms, theory, and applications related to both supervised and unsupervised learning, including regression, classification, and optimization and major algorithm families for each.Prerequisites: CS 2150 or CS 3100 with a grade of C- or better; APMA 3100, APMA 3110, MATH 3100, or equivalent and Math 3350 or APMA 3080 or equivalent

Introduces artificial intelligence. Covers fundamental concepts and techniques and surveys selected application areas. Core material includes state space search, logic, and resolution theorem proving. Application areas may include expert systems, natural language understanding, planning, machine learning, or machine perception. Provides exposure to AI implementation methods, emphasizing programming in Common LISP. Prerequisite: CS 2150 or CS 3100 with a grade of C- or better

Supports the writing of the technical report component of the fourth-year thesis, credit for which is given in STS 4600. Students will write the report assuming a non-technical audience. The course is part of the CS 4XXX elective option in the fourth-year CS thesis track. BS CS 4th years (both first & second majors) and pre- or co-requisite STS 4500

Introduces discrete mathematics and proof techniques involving first order predicate logic and induction. Application areas include sets, tuples, functions, relations, and combinatorial problems. Prereq: CS 1100 - CS 1199

An introduction to testing for assuring software quality. Covers concepts and techniques for testing software, including testing at the unit, module, subsystem, and system levels; automatic and manual techniques for generating and validating test data; the testing process; static vs. dynamic analysis; functional testing; inspections; testing in specific application domains; and reliability assessment.Prerequisite: CS 2150 or (CS 2100 and CS 2120) with a grade of C- or better

Content varies, depending on instructor interests and the needs of the Department. Taught strictly at the undergraduate level. Prerequisite: Instructor permission; additional specific requirements vary with topics.

Presents programming languages and implementations used in developing web applications. Both client and server side languages are presented as well as database languages. In addition, frameworks that enable interactive web pages are discussed as well as formatting languages. Language features and efficiencies including scoping, parameter passing, object orientation, just in time compilation and dynamic binary translation are included. Prerequisite: CS 2150 or CS 3140 with a grade of C- or better

Introduces the fundamental concepts for design and development of database systems. Emphasizes relational data model and conceptual schema design using ER model, practical issues in commercial database systems, database design using functional dependencies, and other data models. Develops a working relational database for a realistic application. Prerequisite: CS 2150 or (CS 2120 and 3140) with a grade of C- or better

Builds upon previous analysis of algorithms and the effects of data structures on them. Algorithms selected from areas such as searching, shortest paths, greedy algorithms, backtracking, divide-and-conquer, dynamic programming, and machine learning. Analysis techniques include asymptotic worst case, expected time, amortized analysis, and reductions. Prerequisites: CS 2150 or (CS 2100 & CS 2120); APMA 1090 or MATH 1210 or MATH 1310 or equivalent. CS 3140 is recommended.

A first course in communication networks for upper-level undergraduate students. Topics include the design of modern communication networks; point-to-point and broadcast network solutions; advanced issues such as Gigabit networks; ATM networks; and real-time communications. Cross-listed as ECE 4457. Prerequisite: CS 3330 or CS 2501 topic "COA 2" or ECE 3430 or ECE 4435 or ECE 3502 topic "ECR II" or CS 3130. Must complete CS courses with a grade of C- or better.

Covers advanced principles of operating systems. Technical topics include support for distributed OSs; microkernels and OS architectures; processes and threads; IPC; files servers; distributed shared memory; object-oriented OSs; reflection in OSs; real-time kernels; multiprocessing; multimedia and quality of service; mobile computing; and parallelism in I/O. Prerequisite: Undergraduate course in OS; CS 6354 or instructor permission.

How computers create, preserve, manipulate and communicate information and the concepts and tools used to that end. Units include how computers work, web technologies, creating web pages, algorithms and logic, basic programming, and solving problems with spreadsheets. Students will learn to recognize computational problems and develop basic skill sets to solve future problems in their discipline of study. No prior programming experience required. Cannot be taken for credit by students in SEAS.

Content varies, depending on instructor interests and the needs of the Department. Taught strictly at the undergraduate level. Prerequisite: Instructor permission; additional specific requirements vary with topics.

Content varies annually, depending on instructor interests and the needs of the department. Similar to CS 5501 and CS 7501, but taught strictly at the undergraduate level. Prerequisite: Instructor permission; additional specific requirements vary with topics.

A first course in programming, software development, and computer science. Introduces computing fundamentals and an appreciation for computational thinking. Special domain topics and materials will differ by section and semester. Note: CS 1110, 1111, 1112, 1113, and 1120 provide different approaches to teaching the same core material; students may only receive credit for one of these courses. Students may not enroll if CS 2100 or CS 3140 has been completed.

An overview of computer science education for undergraduate students. Topics include ethics, diversity, tutoring and teaching techniques, and classroom management. Students enrolled in this course serve as a teaching assistant for a computer science course as part of their coursework.

A first course in software engineering and software construction, this course focuses on bringing the programming concepts learned in a first course in data structures and algorithms together to begin to teach students how to build more complex systems. The course covers introductory topics in testing, software design principles, design patterns, functional programming, and data storage and manipulation. Completed CS 2100 with a C- or better.

A first course in programming, software development, and computer science. Introduces computing fundamentals and an appreciation for computational thinking. No previous programming experience required. Note: CS 1110, 1111, 1112, 1113, and 1120 provide different approaches to teaching the same core material; students may only receive credit for one of these courses. Students may not enroll if CS 2100 or CS 3140 has been completed.

This course provides an overview of the state of the art in software analysis including static and dynamic analysis techniques and verification and validation. It explores the various ways that the analyses are used to predict software behavior. The applications include inference, symbolic execution, fault localization, model checking, security and performance. The course combines theory with practical implementation and usage. Prerequisites: CS 3240.

A first course in programming, software development, and computer science. Introduces computing fundamentals and an appreciation for computational thinking. Prerequisite: Students must have no previous programming experience. Note: CS 1110, 1111, 1112, 1113, and 1120 provide different approaches to teaching the same core material; students may only receive credit for one of these courses. Students may not enroll if CS 2100 or CS 3140 has been completed.

Introduces students to the fields of cybersecurity. Both non-technical issues, such as ethics and policy, and technical issues are covered. Students see and experiment with a wide range of areas within cybersecurity, including: binary exploitation, encryption, digital forensics, networks, and modern threats. Prerequisites: CS 2150 or (CS 2100 or CS 2100 place out test and CS 2130) with a grade of C- or better

This course will introduce students to the concepts and tools used in the development of modern 2-D and 3-D real-time interactive computer video games. Topics covered in this include graphics, parallel processing, human-computer interaction, networking, artificial intelligence, and software engineering. Prerequisite: CS 2150 or CS 3140 with a grade of C- or better

In-depth study of a computer science or computer engineering problem by an individual student in close consultation with departmental faculty. The study is often either a thorough analysis of an abstract computer science problem or the design, implementation, and analysis of a computer system (software or hardware). Prerequisite: Instructor permission.

Provides an overview of modern microprocessor design. The topics covered in the course will include the design of super-scalar processors and their memory systems, and the fundamentals of multi-core processor design. Prerequisite: CS 3330 with a grade of C- or better

This course is a general introduction to cryptocurrencies and blockchain applications. Students will understand the theoretical concepts that underlay cryptocurrencies, and implement both their own cryptocurrencies as well as develop applications that run on existing cryptocurrencies. Students will see the ethics, legal, and policy aspects pertaining to the subject. Prerequisite: CS 3100 with a grade of C- or better

This course is one option in the CS fourth-year thesis track. Students will seek out a faculty member as an advisor, and do an independent project with said advisor. Instructors can give the 3 credits across multiple semesters, if desired. This course is designed for students who are doing research, and want to use that research for their senior thesis. Note that this track could also be an implementation project, including a group-based project.Prerequisite: CS 2150 or CS 2501 topic DSA2 with a grade of C- or higher, and BSCS major

Required for Distinguished Majors completing the Bachelor of Arts degree in the College of Arts and Sciences. An introduction to computer science research and the writing of a Distinguished Majors thesis. Prerequisites: CS 2150 or CS 2501 topic DSA2 with a grade of C- or higher, and BSCS major

This is a graduate-level machine learning course. Machine Learning is concerned with computer programs that automatically improve their performance through experience. This course covers introductory topics about the theory and practical algorithms for machine learning from a variety of perspectives. Topics include supervised learning, unsupervised learning and learning theory. Prerequisite: Calculus, Basic linear algebra, Basic Probability and Basic Algorithm. Statistics is recommended. Students should already have good programming skills.

Interactions between robots and humans are influenced by form, function and expectations. Quantitative techniques evaluate performance of specific tasks and functions. Qualitative techniques are used to evaluate the interaction and to understand expectations and perceptions of the human side of the interaction. Students use humanoid robots to develop and evaluate interactions within a specific application context.

Cyber-physical systems (CPS) are smart systems that include co-engineered interacting networks of physical and computational components. This course will teach students the required skills to analyze the CPS that are all around us, so that when they contribute to the design of CPS, they are able to understand important safety and security aspects and feel confident designing and analyzing CPS systems.

A graduate student returning from Curricular Practical Training can use this course to claim one credit hour of academic credit after successfully reporting, orally and in writing, a summary of the CPT experience to his/her academic advisor.

Detailed study of graduate course material on an independent basis under the guidance of a faculty member.

Detailed study of graduate course material on an independent basis under the guidance of a faculty member.

Formal record of student commitment to project research for the Master of Computer Science degree under the guidance of a faculty advisor.

For master's students who are teaching assistants.

Formal record of student commitment to thesis research for the Master of Science degree under the guidance of a faculty advisor. May be repeated as necessary.

For doctoral students who are teaching assistants.

Formal record of student commitment to doctoral research under the guidance of a faculty advisor. May be repeated as necessary.