collageComputer Science Ranking at Drexel University Drexel Institution, commonly referred to as Drexel, is a private research university with its main campus in Philadelphia’s University City area. Francis Palmer Smith, an architect and entrepreneur, and financier J. I. Smith founded it as a vocational school in 1891. For your convenience, this article offers all of the necessary information on Drexel University in Philadelphia, Pennsylvania. It is critical to learn everything there is to know about this university. This will enable you to make the finest career decisions possible.
Read on to find out the drexel university computer science ranking, drexel university computer engineering ranking, drexel university computer science acceptance rate, temple university computer science ranking and drexel computer science acceptance rate. You will also find updated related posts on drexel university computer science ranking on collegelearners.
Understanding a university’s ranking is critical when choosing a university. After the application process and researching colleges of choice, understanding the drexel university computer science ranking is critical.
Drexel University Computer Science Ranking
Drexel was ranked #28 on most recent list of the best schools for compsci majors. This puts the bachelor’s program at the school solidly in the top 15% of all colleges and universities in the country. It is also ranked #3 in Pennsylvania.
- Prepares students for careers in a rapidly changing profession and to allow easy entrance to graduate education in the computer science field
- Offers courses in core areas such as programming and data structures, and electives in many specialty areas such as artificial intelligence, computer vision and graphics, systems architecture, computer security and software engineering
- Offers two optional concentrations:
- Game Programming and Development (GMPD): provides conceptual understanding of game design and practical experience in the design and the development of games.
- Computer Security: gives students the ability to design and implement computing security and privacy processes, software and systems. Students use mathematical foundations, algorithmic principles and computer science theory in the modeling and design of such systems.
- Customize your degree through a variety of available minors at CCI, including Data Science, Computing Technology, Human-Computer Interaction, Information Systems, Security Technology and Software Engineering, or choose from the hundreds of available minors at Drexel.
drexel university computer science acceptance rate
Drexel University Admissions
Drexel University admissions is more selective with an acceptance rate of 77% and an early acceptance rate of 92.4%. Half the applicants admitted to Drexel University have an SAT score between 1180 and 1380 or an ACT score of 25 and 31. However, one quarter of admitted applicants achieved scores above these ranges and one quarter scored below these ranges. The application deadline is Jan. 15 and the application fee at Drexel University is $50.
What is Drexel University best known for?The most popular majors at Drexel University include: Business, Management, Marketing, and Related Support Services; Engineering; Health Professions and Related Programs; Visual and Performing Arts; Computer and Information Sciences and Support Services; Biological and Biomedical Sciences; Psychology; Social Sciences;
Is Drexel a top 100 school?
PHILADELPHIA, PA – Drexel University’s School of Education ranks #1 among all Philadelphia-based universities for best online master’s in education programs according to the 2021 rankings from U.S. News and World Report
drexel university world ranking 2020
Drexel University Ranking Highlights
- According to US News & World Report 2021, Drexel University ranked #93 in Best Colleges for Veterans.
- According to US News & World Report 2021, Drexel University ranked #133 in National University Ranking.
- On the report of QS World University Rankings, Drexel University has ranked #59 among the US Universities.
- As per Times Higher Education (THE), the university’s ranking is #351-400.
- According to US News & World Report 2021, Drexel University ranked #53 in Best Undergraduate Engineering Programs.
Drexel University Global Ranking
There were various Ranking Indicators used by platforms to determine and establish the ranking of a particular institute, the ranking in the respective country, and its subject-wise rankings. Some of these indicators are – Calculation of its Research Performance (Publications, Books, Conferences, etc.), analyzing various Reputation Indicators, Bibliometric Indicators, Scientific Excellence Indicators, etc. And as per the calculations, various segment-wise rankings of the university are calculated.
Drexel University is one of the best and most popular universities in the US. It was ranked #501-510 in 2019, #561-570 in 2020, and #601-650 in 2021, as per the QS World University Rankings. In the last decade, the university has seen depreciation in its ranking, other than the years 2017-19, where the university’s ranking remained constant. Drexel University has seen a decrease, moreover, in the current academic year of 2021.
Additionally, the scores in the overall university performance result in its ranking in the world. Here are some ranking indicators that determine the position of an institute in the world and the country:
| Ranking Criteria | Score (Out of 100) |
|---|---|
| Faculty Student | 34.1 |
| Citations per Faculty | 29.6 |
| International Students | 23.4 |
Here is the ranking of the best universities in the US compared to Drexel University in its ranking and global score :
| University | Global Rank | Global Score |
|---|---|---|
| Harvard University | #1 | 100.0 |
| Massachusetts Institute of Technology | #2 | 97.9 |
| Stanford University | #3 | 95.3 |
| University of California – Berkley | #4 | 89.8 |
| University of Oxford | #5 | 87.0 |
| Drexel University | #387 | 54.4 |
Drexel University National Ranking
Drexel University is a Private University located in the US. The university was established in 1891. In the last five years, the university has seen an excellent rise in its admission statistics. The university’s freshmen applications tripled, undergraduate employment doubled, endowment tripled, and research funding doubled.
With an average 6-year graduation rate of 71% and an average Global Score of 56, Drexel University performed well in securing its place as one of the Best National Universities.
The ranking parameters for all major ranking agencies are the same. Ranking agencies like Top Universities, Times Higher Education, and The US News, etc. calculate the university’s world and country ranking based on similar criteria.
The country-wise ranking of Drexel University as determined by various reports are as follows :
- As per QS Top Universities, Drexel University has ranked #59th in US UNI (universities) Rankings.
- As per The US News, Drexel University has ranked #133 in National Universities.
- As per Times Higher Education (THE), the university’s ranking is #351-400.
- As per Shanghai Ranking (ARWU) 2020, the university’s ranking is #301-400.
Drexel University beat Thomas Jefferson University by three ranks. However, it fell short by a minimal score from Temple University. Overall, the ranking of Drexel University is above average on a national level.
Here are the rankings of other universities in Philadelphia, USA :
| University | Global Rank | Global Score |
|---|---|---|
| University of Pennsylvania | #14 | 84.2 |
| Temple University | #312 | 57.5 |
| Drexel University | #387 | 54.4 |
| Thomas Jefferson University | #390 | 54.2 |
Drexel University Subject Rankings
The University consists of 15 faculties namely, Goodwin College of Professional Studies and Dornsife School of Public Health, College of Computing & Informatics, School of Education, and College of Engineering, School of Entrepreneurship College Of Arts and Sciences, School of Biomedical Engineering, Science and Health Systems, Lebow College of Business, Center for Food And Hospitality Management, Pennoni Honors College, Westphal College of Media Arts & Design, College of Nursing and Health Professions,.
As per QS World University Rankings, Drexel University has been ranked #45 in its subject ranking.
- As per QS 2020, Drexel University held ##151-200 Global MBA Ranking, and a rank of #401-450 in its Business & Management Studies program.
- According to Times Higher Education (THE), Drexel University ranked #151-175 in Engineering and Technology, #501-600 in Computer, and #251-300 in Business and Economics.
As per U.S. News and World Report, Drexel University ranked :
- #27 in Best Undergraduate Mechanical Engineering Program
- #54 in UG Engineering Program Rankings
- #75 in Best Engineering School Ranking (PG Level)
- #84 in Best Business School Ranking (PG Level)
- #9 in IG Business Program Rankings
drexel university ranking engineering
Drexel University is ranked No. 79 (tie) in Best Engineering Schools. Schools are ranked according to their performance across a set of widely accepted indicators of excellence.
Engineering School Program Rankings
- #79inBest Engineering Schools (tie)
Engineering School Specialty Rankings
- inBiomedical Engineering / Bioengineering
- inChemical Engineering
- inCivil Engineering
- inComputer Engineering
- inElectrical / Electronic / Communications Engineering
- inEnvironmental / Environmental Health Engineering
- inMaterials Engineering
- inMechanical Engineering
The College of Engineering at Drexel University has an application deadline of Sept. 1. The application fee is $65 for U.S. residents and $65 for international students. Its tuition is full-time: $1,342 per credit and part-time: $1,342 per credit. The 2020 Ph.D. student-faculty ratio is 2.5:1. The College of Engineering at Drexel University has 130 full-time faculty on staff.
drexel computer science courses
Courses
CS 150 Computer Science Principles 3.0 Credits
An introduction to computer science principles: the big ideas and computational thinking practices central to computer science, and the societal impact of computing and information technology. Exposure to algorithms, big data, machine learning, privacy, security and digital citizenship while introducing and reinforcing the importance of programming.
College/Department: College of Computing and Informatics
Repeat Status: Not repeatable for credit
CS 164 Introduction to Computer Science 3.0 Credits
An introduction to the field of computer science. Exposure to core areas (selected from algorithms, artificial intelligence, computer architecture, databases, graphics, human-computer interaction, programming languages, scientific computation, software engineering) while introducing and reinforcing the importance of programming.
College/Department: College of Computing and Informatics
Repeat Status: Not repeatable for credit
CS 171 Computer Programming I 3.0 Credits
Introduces fundamental concepts of computing including memory, instructions, function calls, and activation records. Covers fundamentals of structured computer programming in the language of instruction: variables, input and output, expressions, assignment statements, conditionals and branching, subprograms, parameter passing, repetition, arrays, top-down design, testing, and debugging.
College/Department: College of Computing and Informatics
Repeat Status: Not repeatable for credit
CS 172 Computer Programming II 3.0 Credits
Covers object-oriented design, inheritance hierarchies, information hiding principles, string processing, recursion, good programming style, documentation, debugging, and testing.
College/Department: College of Computing and Informatics
Repeat Status: Not repeatable for credit
Prerequisites: CS 171 [Min Grade: C] or CS 175 [Min Grade: C]
CS 175 Advanced Computer Programming I 3.0 Credits
Advanced programming in language of instruction at an accelerated pace: introduces fundamental concepts of computing including memory, instructions, function calls, and activation records. Covers fundamentals of structured computer programming in the language of instruction: conditionals and branching, subprograms, parameter passing, repetition, arrays, top-down design, testing, and debugging. Supplements basic topics with deeper presentation of advanced techniques for those with some incoming programming experience.
College/Department: College of Computing and Informatics
Repeat Status: Not repeatable for credit
CS 176 Advanced Computer Programming II 3.0 Credits
Enhanced presentation of object-oriented design, inheritance hierarchies, information hiding principles, string processing, recursion, good programming style, documentation, debugging and testing. Includes special focus on language facilities and use of libraries.
College/Department: College of Computing and Informatics
Repeat Status: Not repeatable for credit
Prerequisites: CS 171 [Min Grade: C] or CS 175 [Min Grade: C]
CS 190 Selected Computer Language 3.0 Credits
Focuses on programming in a selected language of interest. Course content, language, and prerequisites may vary according to instructor, with emphasis on applications for which the language is designed. May be repeated for credit.
College/Department: College of Computing and Informatics
Repeat Status: Can be repeated multiple times for credit
CS 260 Data Structures 3.0 Credits
Covers stacks, queues, linked allocation, binary trees, internal searching and sorting, hashing, and applications.
College/Department: College of Computing and Informatics
Repeat Status: Not repeatable for credit
Prerequisites: CS 265 [Min Grade: C]
CS 265 Advanced Programming Tools and Techniques 3.0 Credits
Introduction to the basic principles of programming practice: testing, debugging, portability, performance, design alternatives, and style. Application in a variety of programming languages, programming environments, and operating systems. Introduction to tools used in the software development process for improving program functionality, performance, and robustness.
College/Department: College of Computing and Informatics
Repeat Status: Not repeatable for credit
Prerequisites: CS 172 [Min Grade: C] or CS 176 [Min Grade: C] or ECE 105 [Min Grade: D] or ECEC 201 [Min Grade: D]
CS 270 Mathematical Foundations of Computer Science 3.0 Credits
Introduces formal logic and its connections to Computer Science. Students learn to translate statements about the behavior of computer programs into logical claims and to prove such assertions using both traditional techniques and automated tools. Considers approaches to proving termination, correctness, and safety for programs. Discusses propositional and predicate logic, logical inference, recursion and recursively defined sets, mathematical induction, and structural induction.
College/Department: College of Computing and Informatics
Repeat Status: Not repeatable for credit
Prerequisites: CS 172 [Min Grade: C] or CS 176 [Min Grade: C] or CS 265 [Min Grade: C] or ECE 105 [Min Grade: C] or ECEC 201 [Min Grade: D] or ECEC 301 [Min Grade: D]
CS 277 Algorithms and Analysis 3.0 Credits
Introduces foundational concepts in Computer Science theory, including computability, decidability, the Turing Machine, and algorithmic complexity. Applies concepts underlying graph theory and automata to current topics in computing to create contextualized connections between theory and practice.
College/Department: College of Computing and Informatics
Repeat Status: Not repeatable for credit
Prerequisites: CS 260 [Min Grade: C] and CS 270 [Min Grade: C] and MATH 221 [Min Grade: C]
CS 281 Systems Architecture 4.0 Credits
Covers internal function and organization of digital computers, including instruction sets, addressing methods, input-output architectures, central processor organization, machine language, and assembly language.
College/Department: College of Computing and Informatics
Repeat Status: Not repeatable for credit
Prerequisites: (CS 270 [Min Grade: C] or ECE 200 [Min Grade: D]) and (CS 172 [Min Grade: C] or CS 176 [Min Grade: C] or ECEC 301 [Min Grade: D] or ECEC 201 [Min Grade: D] or ECE 105 [Min Grade: D])
CS 283 Systems Programming 3.0 Credits
This course introduces computer systems, including interaction of hardware and software through the operating system, from the programmer’s perspective. Three fundamental abstractions are emphasized: processes, virtual memory, and files. These abstractions provide programmers a common interface to a wide variety of hardware devices. Topics covered include linking, system level I/O, concurrent programming, and network programming.
College/Department: College of Computing and Informatics
Repeat Status: Not repeatable for credit
Prerequisites: CS 265 [Min Grade: C]
CS 300 Applied Symbolic Computation 3.0 Credits
This course covers the fundamentals of symbolic mathematical methods as embodied in symbolic mathematics software systems, including: fundamental techniques, simplification of expressions, solution of applications problems, intermediate expressions swell, basic economics of symbolic manipulation, efficient solution methods for large problems, hybrid symbolic/numeric techniques.
College/Department: College of Computing and Informatics
Repeat Status: Not repeatable for credit
Prerequisites: CS 260 [Min Grade: C] and CS 270 [Min Grade: C] and MATH 200 [Min Grade: C] and MATH 201 [Min Grade: C]
CS 303 Algorithmic Number Theory and Cryptography 3.0 Credits
Covers fundamental algorithms for integer arithmetic, greatest common divisor calculation, modular arithmetic, and other number theoretic computations. Algorithms are derived, implemented and analyzed for primality testing and integer factorization. Applications to cryptography are explored including symmetric and public-key cryptosystems. A cryptosystem will be implemented and methods of attack investigated.
College/Department: College of Computing and Informatics
Repeat Status: Not repeatable for credit
Prerequisites: CS 260 [Min Grade: C] and (MATH 221 [Min Grade: C] or MATH 222 [Min Grade: C]) and (MATH 201 [Min Grade: C] or ENGR 231 [Min Grade: D])
CS 314 Computing in the Small 3.0 Credits
Explores the technologies and techniques associated with microcontrollers and Systems on Chips (SOCs) as well as their use in embedded systems. A major focus is on developing software to control input and output devices.
College/Department: College of Computing and Informatics
Repeat Status: Not repeatable for credit
CS 338 Graphical User Interfaces 3.0 Credits
This course covers the design and implementation of graphical user interfaces. Topics include: event-driven programming, application programmer interfaces, widgets, callback functions, windowing systems and desktops, rapid prototyping languages, multithreaded GUI’s. A term project involving implementation of a complex application will be undertaken.
College/Department: College of Computing and Informatics
Repeat Status: Not repeatable for credit
Prerequisites: CS 350 [Min Grade: C] or SE 310 [Min Grade: C] or CS 275 [Min Grade: C]
CS 341 Serious Game Development 3.0 Credits
The goal of this course is to learn more about serious games, that is games used in a non-entertainment context, such as games for health, education, and persuasion, through readings and through the design, development, and implementation of serious games.
College/Department: College of Computing and Informatics
Repeat Status: Not repeatable for credit
CS 342 Experimental Game Development 3.0 Credits
The goal of this course is to develop new ideas and innovations in games through the design, development, and implementation of games using short development cycles and creative thematic constraints.
College/Department: College of Computing and Informatics
Repeat Status: Not repeatable for credit
Prerequisites: CS 345 [Min Grade: C], GMAP 345 [Min Grade: D] (Can be taken Concurrently)
CS 345 Computer Game Design and Development 3.0 Credits
This course introduces students to the computer game design process. Students also learn how the individual skills of modeling, animation, scripting, interface design and story telling are coordinated to produce interactive media experiences for various markets, devices and purposes.
College/Department: College of Computing and Informatics
Repeat Status: Not repeatable for credit
Prerequisites: (DIGM 260 [Min Grade: D] or GMAP 260 [Min Grade: D]) and (CS 265 [Min Grade: C] or DIGM 141 [Min Grade: D])
CS 352 Processor Architecture & Analysis 3.0 Credits
This course covers performance evaluation and benchmarking, pipelining, superscalar processors, multiprocessors, and interfacing processors and peripherals. The memory hierarchy, including cache and virtual memory, are also explored from a programmer’s perspective with high-performance computing techniques in mind.
College/Department: College of Computing and Informatics
Repeat Status: Not repeatable for credit
Prerequisites: CS 281 [Min Grade: C] or ECEC 355 [Min Grade: D]
CS 360 Programming Language Concepts 3.0 Credits
Introduces the design and implementation of modern programming languages: formal theory underlying language implementation; concerns in naming, binding, storage allocation and typing; semantics of expressions and operators, control flow, and subprograms; procedural and data abstraction; functional, logic, and object-oriented languages. Students will construct an interpreter for a nontrivial language.
College/Department: College of Computing and Informatics
Repeat Status: Not repeatable for credit
Prerequisites: CS 260 [Min Grade: C] and CS 265 [Min Grade: C] and CS 270 [Min Grade: C]
CS 361 Concurrent Programming 3.0 Credits
Covers programming of concurrent, cooperating sequential processes. Studies race conditions, critical sections, mutual exclusion, process synchronization, semaphores, monitors, message passing, the rendezvous, deadlock, and starvation.
College/Department: College of Computing and Informatics
Repeat Status: Not repeatable for credit
Restrictions: Cannot enroll if classification is Freshman
Prerequisites: CS 260 [Min Grade: C] and (CS 281 [Min Grade: C] or ECEC 355 [Min Grade: D])
CS 370 Operating Systems 3.0 Credits
Explores the internal algorithms and structures of operating systems: CPU scheduling, memory management, file systems, and device management. Considers the operating system as a collection of cooperating sequential processes (servers) providing an extended or virtual machine that is easier to program than the underlying hardware. Topics include virtual memory, input/output devices, disk request scheduling, deadlocks, file allocation, and security and protection.
College/Department: College of Computing and Informatics
Repeat Status: Not repeatable for credit
Restrictions: Cannot enroll if classification is Freshman
Prerequisites: CS 283 [Min Grade: C] or ECEC 353 [Min Grade: D]
CS 375 Web Development 3.0 Credits
Introduction to web development with a focus on programming full-stack web applications. Covers front-end topics like HTML, CSS, and client-side JavaScript, and back-end topics like web servers and databases.
College/Department: College of Computing and Informatics
Repeat Status: Not repeatable for credit
Prerequisites: CS 265 [Min Grade: C]
CS 377 Software Security 3.0 Credits
An introduction to foundational systems concepts underpinning the broad area of software security. Topics covered include access control, software vulnerabilities such as buffer overflows and race conditions, insecurity in software, cryptocurrency, malware, and operating systems security.
College/Department: College of Computing and Informatics
Repeat Status: Not repeatable for credit
Prerequisites: CS 283 [Min Grade: C] or ECEC 353 [Min Grade: D]
CS 380 Artificial Intelligence 3.0 Credits
Explores the foundations of artificial intelligence: production systems, heuristic programming, knowledge representation, and search algorithms. Also covers programming in an AI language. Additional topics chosen from game theory, decision support systems, pattern matching and recognition, image understanding, natural language, fuzzy and non-monotonic logic, machine learning, theorem proving, and common sense reasoning.
College/Department: College of Computing and Informatics
Repeat Status: Not repeatable for credit
Restrictions: Cannot enroll if classification is Freshman
Prerequisites: CS 260 [Min Grade: C] and CS 270 [Min Grade: C]
CS 383 Machine Learning 3.0 Credits
This course covers the fundamentals of modern statistical machine learning. Lectures will cover the theoretical foundation and algorithmic details of representative topics including probabilities and decision theory, regression, classification, graphical models, mixture models, clustering, expectation maximization, hidden Markov models, and weak learning.
College/Department: College of Computing and Informatics
Repeat Status: Not repeatable for credit
Prerequisites: CS 260 [Min Grade: C] and (MATH 201 [Min Grade: C] or ENGR 231 [Min Grade: D]) and (MATH 221 [Min Grade: C] or MATH 222 [Min Grade: C]) and (MATH 311 [Min Grade: C] or MATH 410 [Min Grade: C] or ECE 361 [Min Grade: D])
CS 385 Evolutionary Computing 3.0 Credits
This course covers computational intelligence approaches to problem solving for classification, adaptation, optimization, and automated control. Methods covered will include evolutionary programming/genetic algorithms, genetic programming, neural networks, swarm optimization, and fuzzy logic.
College/Department: College of Computing and Informatics
Repeat Status: Not repeatable for credit
Prerequisites: CS 260 [Min Grade: C] and CS 380 [Min Grade: C]
CS 387 Game AI Development 3.0 Credits
This course focuses on artificial intelligence (AI) techniques for computer games. Students will learn both basic and advanced AI techniques that are used in a variety of game genres including first-person shooters, driving games, strategy games, platformers, etc. The course will emphasize the difference between traditional AI and game AI, the latter having a strong design component, focusing on creating games that are “fun to play.” Topics include path-finding, decision-making, strategy and machine learning in games.
College/Department: College of Computing and Informatics
Repeat Status: Not repeatable for credit
Prerequisites: CS 260 [Min Grade: C] and CS 380 [Min Grade: C]
CS 429 Software Defined Radio Laboratory 3.0 Credits
This laboratory course takes a Software-Defined Radio (SDR) implementation approach to learn about modern analog and digital communication systems. Software defined radio uses general purpose radio hardware that can be programmed in software to implement different communication standards. We will begin by discussing the basic principles of wireless radio frequency transmissions and leverage this knowledge to build analog and digital communication systems. Knowledge of these techniques and systems will provide a platform that can be used in the class project for further exploration of wireless networking topics such as cybersecurity, cognitive radio, smart cities, and the Internet of Things.
College/Department: College of Computing and Informatics
Repeat Status: Not repeatable for credit
Prerequisites: (CS 260 [Min Grade: C] and CS 265 [Min Grade: C] and CS 270 [Min Grade: C])
CS 430 Computer Graphics 3.0 Credits
The course presents the fundamental geometric representations and drawing algorithms of computer graphics through lectures and programming assignments. The representations include lines, curves, splines, polygons, meshes, parametric surfaces and solids. The algorithms include line drawing, curve and surface evaluation, polygon filling, clipping, 3D-to-2D projection and hidden surface removal.
College/Department: College of Computing and Informatics
Repeat Status: Not repeatable for credit
Prerequisites: CS 260 [Min Grade: C] and (MATH 201 [Min Grade: C] or MATH 261 [Min Grade: C] or ENGR 231 [Min Grade: D])
CS 431 Advanced Rendering Techniques 3.0 Credits
The creation of realistic images from 3D models is central to the development of computer graphics. The ray tracing algorithm has become one of the most popular and powerful techniques for creating photo-realistic images. This class explores the algorithmic components of ray tracing. Students implement many of these components in their class programming projects.
College/Department: College of Computing and Informatics
Repeat Status: Not repeatable for credit
Prerequisites: CS 430 [Min Grade: D] or CS 432 [Min Grade: D]
CS 432 Interactive Computer Graphics 3.0 Credits
This is a project-oriented class that covers the concepts and programming details of interactive computer graphics. These include graphics primitives, display lists, picking, shading, rendering buffers and transformations. Students will learn an industry-standard graphics system by implementing weekly programming assignments. The course culminates with a student-defined project.
College/Department: College of Computing and Informatics
Repeat Status: Not repeatable for credit
Prerequisites: CS 260 [Min Grade: C] and (MATH 201 [Min Grade: C] or MATH 261 [Min Grade: C] or ENGR 231 [Min Grade: D])
CS 435 Computational Photography 3.0 Credits
Fundamentals of computational photography, an interdisciplinary field at the intersection of computer vision, graphics, and photography. Covered topics include fundamentals of cameras, novel camera designs, image manipulation, single-view modeling, and image-based rendering with an emphasis on learning the computational methods and their underlying mathematical concepts through hands-on assignments.
College/Department: College of Computing and Informatics
Repeat Status: Not repeatable for credit
Prerequisites: CS 260 [Min Grade: C] and (MATH 201 [Min Grade: C] or MATH 261 [Min Grade: C] or ENGR 231 [Min Grade: D])
CS 440 Theory of Computation 3.0 Credits
Finite automata, regular sets, and regular expressions; pushdown automata, context-free languages, and normal forms for grammars; Turing machines and recursively enumerable sets; Chomsky hierarchy; computability theory.
College/Department: College of Computing and Informatics
Repeat Status: Not repeatable for credit
Restrictions: Cannot enroll if classification is Freshman or Sophomore
Prerequisites: CS 270 [Min Grade: C] and (MATH 221 [Min Grade: C] or MATH 222 [Min Grade: C])
CS 441 Compiler Implementation 3.0 Credits
Covers the fundamentals of optimizing compilers and code generation, including compiler intermediate representations, basic compiler optimizations, program analyses to enable optimizations (such as value numbering), and generation of efficient code (register allocation and instruction selection).
College/Department: College of Computing and Informatics
Repeat Status: Not repeatable for credit
Prerequisites: (CS 281 [Min Grade: C] or ECE 350 [Min Grade: D]) and CS 360 [Min Grade: C]
CS 457 Data Structures and Algorithms I 4.0 Credits
This course covers techniques for analyzing algorithms, including: asymptotic analysis, recurrence relations, and probabilistic analysis; data structures such as hash tables and binary trees; algorithm design techniques such as dynamic programming, greedy methods, and divide & conquer, as well as graph algorithms for graph traversal, minimum spanning trees, and shortest paths.
College/Department: College of Computing and Informatics
Repeat Status: Not repeatable for credit
Prerequisites: CS 260 [Min Grade: C] and CS 270 [Min Grade: C] and (MATH 221 [Min Grade: C] or MATH 222 [Min Grade: C])
CS 458 Data Structures and Algorithms II 3.0 Credits
This course covers the amortized analysis of algorithms and data structures; Fibonacci heaps; graph algorithms for maximizing network flow and computing minimum all pairs shortest paths; string matching algorithms; NP-Completeness and approximation algorithms.
College/Department: College of Computing and Informatics
Repeat Status: Not repeatable for credit
Prerequisites: CS 457 [Min Grade: D]
CS 461 Database Systems 3.0 Credits
Covers topics including structure and function of database systems, normal form theory, data models (relational, network, and hierarchical), query processing (ISBL), relational algebra and calculus, and file structures. Includes programming project using DBMS.
College/Department: College of Computing and Informatics
Repeat Status: Not repeatable for credit
Restrictions: Cannot enroll if classification is Freshman
Prerequisites: CS 260 [Min Grade: C]
CS 465 Privacy and Trust 3.0 Credits
This course will motivate the need for privacy protection and introduce basic privacy properties such as anonymity, unlinkability or unobservability. We will then discuss how these properties can be formalized, modeled and measured. The course will provide a broad overview of the state-of-the-art in privacy technologies, explain the main issues that these technologies address, what the current solutions are able to achieve, and the remaining open problems.
College/Department: College of Computing and Informatics
Repeat Status: Not repeatable for credit
Prerequisites: CS 303 [Min Grade: D]
CS 472 Computer Networks: Theory, Applications and Programming 3.0 Credits
Introduction to computer networking theory, applications and programming, focusing on large heterogeneous networks. Broad topdown introductions to computer networking concepts including distributed applications, socket programming, operation system and router support, router algorithms, and sending bits over congested, noisy and unreliable communication links.
College/Department: College of Computing and Informatics
Repeat Status: Not repeatable for credit
Prerequisites: CS 361 [Min Grade: D] or CS 283 [Min Grade: C] or ECEC 353 [Min Grade: D]
CS 475 Network Security 3.0 Credits
An introduction to foundational systems concepts underpinning the specialized area of network security. Focus to be given to security issues pertaining to the Data Link, Network, and Transport layers of the network stack. Topics include packet sniffing and spoofing, as well as MAC, IP, ICMP, TCP, and UDP attacks.
College/Department: College of Computing and Informatics
Repeat Status: Not repeatable for credit
Prerequisites: CS 472 [Min Grade: D] or CS 283 [Min Grade: C] or ECEC 353 [Min Grade: D]
CS 476 High Performance Computing 3.0 Credits
This course is an introduction to high performance computing, including concepts and applications. Course contents will include discussions of different types of high performance computer architectures (multi-core/multi-threaded processors, parallel computers, etc), the design, implementation, optimization and analysis of efficient algorithms for uni-processors, multi-threaded processors, parallel computers, and high performance programming.
College/Department: College of Computing and Informatics
Repeat Status: Not repeatable for credit
Prerequisites: (CS 281 [Min Grade: C] and CS 283 [Min Grade: C]) or (ECEC 353 [Min Grade: D] and ECEC 355 [Min Grade: D])
CS 479 Advanced Network Security 3.0 Credits
A treatment of advanced systems concepts underpinning the specialized area of network security. Focus to be given to security issues pertaining to the Application layer of the network stack. Topics include security attacks on Firewalls and DNS, as well as attacks on Web Applications such as Cross-Site Request Forgery, Cross-Site Scripting, and SQL Injection.
College/Department: College of Computing and Informatics
Repeat Status: Not repeatable for credit
Prerequisites: CS 475 [Min Grade: D]
CS 481 Advanced Artificial Intelligence 3.0 Credits
This course covers topics in representation, reasoning, and decision-making under uncertainty; learning; solving problems with time-varying properties. Assignments applying AI techniques toward building intelligent machines that interact with dynamic, uncertain worlds will be given.
College/Department: College of Computing and Informatics
Repeat Status: Not repeatable for credit
Prerequisites: CS 380 [Min Grade: D] and (MATH 311 [Min Grade: D] or MATH 410 [Min Grade: D] or ECE 361 [Min Grade: D])
CS 486 Topics in Artificial Intelligence 3.0 Credits
A variety of special topics are offered in artificial intelligence (AI) including: intelligent time-critical reasoning, knowledge-based agents, machine learning, natural language processing, and geometric reasoning. This course may be repeated for credit as topics vary.
College/Department: College of Computing and Informatics
Repeat Status: Can be repeated multiple times for credit
Prerequisites: CS 380 [Min Grade: C]
CS I199 Independent Study in CS 0.0-12.0 Credits
Self-directed within the area of study requiring intermittent consultation with a designated instructor.
College/Department: College of Computing and Informatics
Repeat Status: Can be repeated multiple times for credit
CS I299 Independent Study in CS 0.0-12.0 Credits
Self-directed within the area of study requiring intermittent consultation with a designated instructor.
College/Department: College of Computing and Informatics
Repeat Status: Can be repeated multiple times for credit
CS I399 Independent Study in CS 0.0-12.0 Credits
Self-directed within the area of study requiring intermittent consultation with a designated instructor.
College/Department: College of Computing and Informatics
Repeat Status: Can be repeated multiple times for credit
CS I499 Independent Study in Computer Science 0.0-12.0 Credits
Self-directed within the area of study requiring intermittent consultation with a designated instructor.
College/Department: College of Computing and Informatics
Repeat Status: Can be repeated multiple times for credit
CS T180 Special Topics in Computer Science 0.0-12.0 Credits
Topics decided upon by faculty will vary within the area of study.
College/Department: College of Computing and Informatics
Repeat Status: Can be repeated multiple times for credit
CS T280 Special Topics in Computer Science 0.0-12.0 Credits
Topics decided upon by faculty will vary within the area of study.
College/Department: College of Computing and Informatics
Repeat Status: Can be repeated multiple times for credit
CS T380 Special Topics in Computer Science 0.0-12.0 Credits
Topics decided upon by faculty will vary within the area of study.
College/Department: College of Computing and Informatics
Repeat Status: Can be repeated multiple times for credit
CS T480 Special Topics in Computer Science 0.0-12.0 Credits
Topics decided upon by faculty will vary within the area of study.
College/Department: College of Computing and Informatics
Repeat Status: Can be repeated multiple times for credit
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