Computer Science
Computer Science at Manhattan
Computer Science prepares students for work in a number of computer-related fields as software engineers, designers of algorithms and designers of applications in various areas.
The Computer Science Department offers B.S. and B.A. degrees in Computer Science and provides the opportunity to pursue an interdisciplinary minor.
The B.S. Computer Science undergraduate program is accredited by the Computing Accreditation Commission of ABET.
The Computer Science degree combines depth in all aspects of modern Computer Science theory with the development of high level skills in computer programming and design of algorithms.
The program includes introduction to computer programming, object-oriented programming beginning with C++ and then Java, data structures and algorithms, discrete structures and fundamentals of discrete mathematics, systems programming with Linux, operating systems, databases, computer organization, computer security, numerical computation, computer networks, software engineering and capstone project design, plus electives in programming languages (Python, R, Matlab, other languages), cloud computing, artificial intelligence, artificial neural networks and machine learning, data mining, cryptography and cybersecurity, web security, blockchain technology, parallel computing, image processing and analysis, Linux kernel programming and other.
There is a concentration area in Artificial Intelligence and Machine Learning within a B.S. and B.A. degrees, which includes three courses: Neural Networks and Learning Systems, Artificial Intelligence, and Data Mining.
Students are encouraged to participate in programming contests such as the international ACM Collegiate programming contest and summer programs such as Google Summer of Code or research programs held at off-campus locations. With a faculty sponsor, a student may apply for support for an on-campus research project during the summer. Every year students present at the Manhattan College annual student research conference and publish in The Manhattan Scientist journal.
The Department started a graduate program (M.S.) in Computer Science in 2018. This program includes a special one year option for those students who received their undergraduate degree in Computer Science from Manhattan College. Staying only for one more year in the College and taking 24 more credits (8 courses or 6 courses and Master Thesis/Project) students may get their M.S. degree in Computer Science.
Mission Statement
The Computer Science Department strives for excellence in giving our students knowledge through comprehensive educational programs, research, dissemination through scholarly publications, and service to the profession, the community, the state, and the nation.
Program Educational Objectives
Within a few years after their graduation, graduates of the Manhattan College Computer Science Program will:
- Have professional careers in industry, government, academia or entrepreneurship or will be engaged in advanced studies.
- Demonstrate effective teamwork or leadership, with integrity and ethical considerations in their work.
- Continue to enhance their knowledge and adapt to changes in technology as well as a varied and globalized society.
Program Learning Outcomes
Graduates of the program will have an ability to:
- Analyze a complex computing problem and to apply principles of computing and other relevant disciplines to identify solutions.
- Design, implement, and evaluate a computing-based solution to meet a given set of computing requirements in the context of the program’s discipline.
- Communicate effectively in a variety of professional contexts.
- Recognize professional responsibilities and make informed judgments in computing practice based on legal and ethical principles.
- Function effectively as a member or leader of a team engaged in activities appropriate to the program’s discipline.
- Apply computer science theory and software development fundamentals to produce computing-based solutions.
The Computer Science programs employ the standard set of ABET student learning outcomes for computing programs.
Degree Plans
General Requirements: Major courses should be taken in accordance with the PLAN OF STUDY listed below. The order in which School of Science core courses are taken is flexible. A minimum grade of C in each of the major courses is required. Before taking any major course, the student must obtain a grade of C or better in the prerequisite courses.
Major Computer Science
A major program in computer science is available in the School of Science within either a curriculum leading to a Bachelor of Science degree or a curriculum leading to a Bachelor of Arts degree.
B.S. in Computer Science
The Department has been working continuously on keeping its B.S. program in such a rapidly developing area as Computer Science up to date. Thus some changes, which are also important for ABET accreditation, were made recently.
Students entered starting from 2020 should follow the curriculum below:
| MATH 185 | Calculus I | 4 |
| MATH 186 | Calculus II | 4 |
| MATH 351 | Computational Linear Algebra & Statistics for Computer Science | 3 |
| CMPT 101 | Computer Science I | 3 |
| CMPT 102 | Computer Science II | 3 |
| CMPT 238 | Data Structures and Algorithms - I | 3 |
| CMPT 240 | Data Structures and Algorithms - II | 3 |
| CMPT 258 | Database Systems I | 3 |
| EECE 229 | Introduction to Digital Systems | 3 |
| CMPT 312 | Operating Systems | 3 |
| CMPT 334 | Computer Organization | 3 |
| CMPT 335 | Discrete Structures | 3 |
| CMPT 353 | Systems Programming | 3 |
| CMPT 360 | Object Oriented Design with Java | 3 |
| CMPT 367 | Computer Security | 3 |
| CMPT 439 | Numerical Computation | 3 |
| CMPT 456 | Software Engineering | 3 |
| CMPT 466 | Computer Networks | 3 |
| CMPT 490 | Capstone | 4 |
| PHYS 101 & PHYS 191 | Physics I and Physics I Lab | 4 |
| PHYS 102 & PHYS 192 | Physics II and Physics II Lab | 4 |
| PHYS 221 | Physics of Digital Systems | 4 |
| Approved departmental electives | 15 | |
| SCI 100 | Science Orientation Seminar I | 1 |
| SCI 101 | Science Orientation Seminar II | 1 |
| Total Credits | 89 | |
B.A. in Computer Science
Students entered starting from 2020 should follow the curriculum below:
| MATH 185 | Calculus I | 4 |
| MATH 186 | Calculus II | 4 |
| MATH 351 | Computational Linear Algebra & Statistics for Computer Science | 3 |
| CMPT 101 | Computer Science I | 3 |
| CMPT 102 | Computer Science II | 3 |
| CMPT 238 | Data Structures and Algorithms - I | 3 |
| CMPT 258 | Database Systems I | 3 |
| EECE 229 | Introduction to Digital Systems | 3 |
| CMPT 312 | Operating Systems | 3 |
| CMPT 334 | Computer Organization | 3 |
| CMPT 335 | Discrete Structures | 3 |
| CMPT 353 | Systems Programming | 3 |
| CMPT 360 | Object Oriented Design with Java | 3 |
| CMPT 439 | Numerical Computation | 3 |
| CMPT 456 | Software Engineering | 3 |
| CMPT 466 | Computer Networks | 3 |
| CMPT 490 | Capstone | 4 |
| Approved departmental electives | 12 | |
| Three SCI 2xx courses * | 9 | |
| SCI 100 | Science Orientation Seminar I | 1 |
| SCI 101 | Science Orientation Seminar II | 1 |
| Total Credits | 77 | |
- *
Students may opt instead to take one (1) full year of a science with lab (8 credits, that is two science courses with labs). In this case total credits required in this core for graduation is 76 instead of 77
Minor in Computer Science
The minor in Computer Science consists of a minimum of 15 credits. Specific requirements are listed below. A grade of at least C is required for all courses meeting the requirements for a minor in Computer Science. Note: CMPT 155 nor CMPT 214 will not be credited toward the minor in Computer Science.
Transfer Credit: At most one course transferred from another institution may be credited toward the fifteen credits required for a minor. A minimum of four courses, 12 credits, must be taken within the Department of Computer Science at Manhattan College.
Application: When the required courses are completed, a student must get a Minor Form from the department secretary, fill it out and have it signed by the Chair of the Department.
Minor Requirement for Students in the School of Engineering
| The following two courses are required: | ||
| CMPT 102 | Computer Science II | 3 |
| CMPT 238 | Data Structures and Algorithms - I | 3 |
| One of the following courses is required: | ||
| CMPT 240 | Data Structures and Algorithms - II | 3 |
| CMPT 258 | Database Systems I | 3 |
| CMPT 312 | Operating Systems | 3 |
| CMPT 353 | Systems Programming | 3 |
| CMPT 360 | Object Oriented Design with Java | 3 |
| CMPT 367 | Computer Security | 3 |
| CMPT 439 | Numerical Computation | 3 |
| CMPT 456 | Software Engineering | 3 |
| CMPT 466 | Computer Networks | 3 |
| Electives: | 6 | |
| Any two CMPT courses at the 200-400 level (including any course from the list above), not including CMPT 214 | ||
Minor Requirements for Students in the Kakos Schools of Arts and Sciences and O'Malley School of Business
| The following three courses are required: | ||
| CMPT 101 | Computer Science I | 3 |
| CMPT 102 | Computer Science II | 3 |
| CMPT 238 | Data Structures and Algorithms - I | 3 |
| One of the following courses is required: | ||
| CMPT 240 | Data Structures and Algorithms - II | 3 |
| CMPT 258 | Database Systems I | 3 |
| CMPT 312 | Operating Systems | 3 |
| CMPT 335 | Discrete Structures | 3 |
| CMPT 353 | Systems Programming | 3 |
| CMPT 360 | Object Oriented Design with Java | 3 |
| CMPT 439 | Numerical Computation | 3 |
| CMPT 456 | Software Engineering | 3 |
| Elective: | 3 | |
| One CMPT course at the 200-400 level (including any course from the list above), not including CMPT 214 | ||
PLAN OF STUDY
Bachelor of Science in Computer Science
Students entered starting from 2020 shall follow the following plan of study:
| First Year | |||
|---|---|---|---|
| Fall | Credits | Spring | Credits |
| CMPT 101 | 3 | CMPT 102 | 3 |
| MATH 185 | 4 | CMPT 335 | 3 |
| SCI 100 | 1 | MATH 186 | 4 |
| Modern Language* | 3 | Modern Language* | 3 |
| RELS 110 | 3 | ENGL 110 | 3 |
| LLRN 102 | 3 | SCI 101 | 1 |
| 17 | 17 | ||
| Second Year | |||
| Fall | Credits | Spring | Credits |
| CMPT 238 | 3 | CMPT 240 | 3 |
| CMPT 360 | 3 | CMPT 258 | 3 |
| MATH 351 | 3 | PHYS 102 & PHYS 192 | 4 |
| PHYS 101 & PHYS 191 | 4 | Social Science | 3 |
| PHIL 150 | 3 | ENGL 150 | 3 |
| 16 | 16 | ||
| Third Year | |||
| Fall | Credits | Spring | Credits |
| CMPT 353 | 3 | CMPT 312 | 3 |
| CMPT 439 | 3 | CMPT 334 | 3 |
| CMPT 466 | 3 | PHYS 221 | 4 |
| EECE 229 | 3 | CMPT Elective | 3 |
| RELS Catholic Studies | 3 | MUSC 150 or ART 150 | 3 |
| 15 | 16 | ||
| Fourth Year | |||
| Fall | Credits | Spring | Credits |
| CMPT 456 | 3 | CMPT 367 | 3 |
| CMPT Electives | 6 | CMPT 490 | 4 |
| RELS Global/Contemporary | 3 | CMPT Electives | 6 |
| HIST 150 | 3 | Social Science | 3 |
| 15 | 16 | ||
| Total Credits: 128 | |||
- *
One year sequence of a modern foreign language.
Bachelor of Arts in Computer Science
Students entered starting from 2020 and taking 9 credits of SCI 2xx shall follow the following 125-credit plan of study:
| First Year | |||
|---|---|---|---|
| Fall | Credits | Spring | Credits |
| CMPT 101 | 3 | CMPT 102 | 3 |
| MATH 185 | 4 | CMPT 335 | 3 |
| SCI 100 | 1 | MATH 186 | 4 |
| Modern Language* | 3 | Modern Language* | 3 |
| RELS 110 | 3 | ENGL 110 | 3 |
| LLRN 102 | 3 | SCI 101 | 1 |
| 17 | 17 | ||
| Second Year | |||
| Fall | Credits | Spring | Credits |
| CMPT 238 | 3 | CMPT 258 | 3 |
| CMPT 360 | 3 | SCI 2xx** | 3 |
| SCI 2xx** | 3 | ENGL 150 | 3 |
| MATH 351 | 3 | Social Science | 3 |
| PHIL 150 | 3 | Free Elective | 3 |
| 15 | 15 | ||
| Third Year | |||
| Fall | Credits | Spring | Credits |
| CMPT 353 | 3 | CMPT 312 | 3 |
| CMPT 439 | 3 | CMPT 334 | 3 |
| CMPT 466 | 3 | RELS Catholic Studies | 3 |
| EECE 229 | 3 | MUSC 150 or ART 150 | 3 |
| SCI 2xx** | 3 | CMPT Elective | 3 |
| 15 | 15 | ||
| Fourth Year | |||
| Fall | Credits | Spring | Credits |
| CMPT 456 | 3 | CMPT 490 | 4 |
| CMPT Elective | 3 | RELS Global/Contemporary | 3 |
| Free Electives | 3 | CMPT Elective | 6 |
| Social Science | 3 | Free Electives | 3 |
| HIST 150 | 3 | ||
| 15 | 16 | ||
| Total Credits: 125 | |||
- *
One year sequence of a modern foreign language.
- **
Students may opt instead to take one (1) full year of a lab science (8 credits) in this case total credits for graduation is 124.
Students entered starting from 2020 and taking 8 credits of two Science courses with labs shall follow the following 124-credit plan of study:
| First Year | |||
|---|---|---|---|
| Fall | Credits | Spring | Credits |
| CMPT 101 | 3 | CMPT 102 | 3 |
| MATH 185 | 4 | CMPT 335 | 3 |
| SCI 100 | 1 | MATH 186 | 4 |
| Modern Language* | 3 | Modern Language* | 3 |
| RELS 110 | 3 | ENGL 110 | 3 |
| LLRN 102 | 3 | SCI 101 | 1 |
| 17 | 17 | ||
| Second Year | |||
| Fall | Credits | Spring | Credits |
| CMPT 238 | 3 | CMPT 258 | 3 |
| CMPT 360 | 3 | SCI with Lab II | 4 |
| SCI with Lab I | 4 | ENGL 150 | 3 |
| MATH 351 | 3 | Social Science | 3 |
| PHIL 150 | 3 | Free Elective | 3 |
| 16 | 16 | ||
| Third Year | |||
| Fall | Credits | Spring | Credits |
| CMPT 353 | 3 | CMPT 312 | 3 |
| CMPT 439 | 3 | CMPT 334 | 3 |
| CMPT 466 | 3 | RELS Catholic Studies | 3 |
| EECE 229 | 3 | MUSC 150 or ART 150 | 3 |
| undefined | CMPT Elective | 3 | |
| 12 | 15 | ||
| Fourth Year | |||
| Fall | Credits | Spring | Credits |
| CMPT 456 | 3 | CMPT 490 | 4 |
| CMPT Elective | 3 | RELS Global/Contemporary | 3 |
| Free Electives | 3 | CMPT Elective | 6 |
| Social Science | 3 | Free Electives | 3 |
| HIST 150 | 3 | ||
| 15 | 16 | ||
| Total Credits: 124 | |||
- *
One year sequence of a modern foreign language.
Courses
CMPT 101. Computer Science I. 3 Credits.
An introduction to basic programming concepts and problem solving skills using the C++ language. Topics include flow of control, loops, functions, arrays, strings and files. CMPT 101 cannot be taken after CMPT 102.
CMPT 102. Computer Science II. 3 Credits.
An introduction to advance programming concepts using the C++ language. Topics include pointers, structured data, classes, inheritance, poloymorphism, exceptions, templates, and recursion. Prerequisite: A grade of C or better in CMPT 101 or ENGR 116.
CMPT 121. Computer Applications for Life Sciences. 3 Credits.
This course explores the use of the computer for analyzing data appropriate to the life sciences.
Topics include using Excel for research: worksheet basics, formulas and functions, charts and graphics, macros and VBA, passing data sets between applications;Computer representations of discrete time dynamical systems, growth and decay models, linear, exponential and logarithmic regression:Introduction to writing simple computer programs and/or procedures.
CMPT 155. Computer Applications for Life Sciences. 3 Credits.
This course explores the use of the computer for analyzing data appropriate to the life sciences. Topics include using electronic spreadsheets and other dedicated software for research: worksheet basics, formulas and functions, charts and graphics, passing data sets between applications; computer representatons of growth and decay models, linear, exponential and logarithmic regression; statistical functions and probability distributions, matrices.
CMPT 201. Computer Sci II for Eng.. 3 Credits.
An introduction to programming and problem solving skills using C++ language. Topics include flow of control, loops, functions, arrays, strings, files, pointers, structured data, recursion, classes, inheritance, and polymorphism. Prerequisite: A grade of C or better in ENGS 116 or permission of the instructor.
CMPT 214. Teaching and Learning with Technology. 3 Credits.
Examines various uses of technology in the classroom to promote student learning.
CMPT 238. Data Structures and Algorithms - I. 3 Credits.
Efficiency of search, sort, and hash algorithms. Stacks, queues, priority queues, binary trees, binary search trees, general trees, heaps, and heapsort. Fall. Prerequisite: A grade of C or better in CMPT 102 or CMPT 201.
CMPT 239. Data Structures & Algorithms. 4 Credits.
Efficiency of search, sort, and hash algorithms. Stacks, queues, priority queues, binary trees, binary search trees, general trees, heaps, and heapsort. Algorithm analysis techniques, worse-case analysis, greedy algorithms, divide and conquer algorithms, recurrent algorithms. Fall. Prerequisite: A grade of C or better in CMPT 102 or CMPT 201.
CMPT 240. Data Structures and Algorithms - II. 3 Credits.
This course describes in depth the algorithm analysis techniques, asymptotic notations, worse-case analysis, greedy algorithms, divide and conquer algorithms, dynamic programming algorithms, graph algorithms, and NP-completeness. This course also covers heaps, heap sort, and priority queues. Prerequisites: A grade of C or better in CMPT 238.
CMPT 241. Web Programming. 3 Credits.
An introduction to Web programming using HTML, CSS and Javascript for development of Web-based applications. Current server-side scripting languages such as PHP will be used for creating dynamic Web pages. Spring. Prerequisite: A grade of C or better in CMPT 102 or CMPT 201 or permission of the instructor.
CMPT 258. Database Systems I. 3 Credits.
An introduction to database system concepts; SQL, database design, normalizing tables, functional dependencies, entity-relationship and relational database models; use of object-oriented design and event programming. Fall Prerequisite: A grade of C or better in CMPT 102 or CMPT 201 or permission of the instructor.
CMPT 312. Operating Systems. 3 Credits.
File systems, CPU scheduling, memory management, virtual memory and machines, disk scheduling, deadlocks and their prevention, concurrency, protection mechanisms, multiprocessors, distributed systems. A survey of the services provided by some of the more popular operating systems. Spring. Prerequisite: A grade of C or better in CMPT 353 or permission of the instructor.
CMPT 334. Computer Organization. 3 Credits.
A study of the internal architecture of a computer. Topics include instruction sets, hardwired and microprogrammed control unit designs, memory systems, I/O systems, introduction to pipeline and parallel processing. Spring. Prerequisite: A grade of C or better in EECE 229 or permission of the instructor.
CMPT 335. Discrete Structures. 3 Credits.
A study of concepts and fundamentals of propositional logic, logic of predicates, sets and set operations, mathematical induction, modular arithmetic, relations, coding theory and encryption. Detailed consideration of structures most frequently encountered in computer science: graphs, trees, and operations on them. Spring (and Fall if needed). Prerequisite: A grade of C or better in CMPT 101 or CMPT 201.
CMPT 336. Simulation and Modeling. 3 Credits.
Probability distributions, mathematical models, simulation of queuing systems, Markov chains. Prerequisite: A grade of C or better in CMPT 102 or CMPT 201 and MATH 186.
CMPT 341. Programming Languages. 3 Credits.
Study of modern programming languages different from C++ and Java (Python and C# or other popular modern programming languages can be covered). Study of language specification and analysis, control structures and data flow. Prerequisites: A grade of C or better in CMPT-102 or CMPT-201.
CMPT 342. Python Programming. 3 Credits.
This course provides an overview of Python programming and covers both the fundamentals and the object-oriented features. The emphasis will be on the logical analysis of a problem and the formulation of a computer program leading to its solution using Python. Students will be required to work on a variety of programming assignments in Python. Topics include but are not limited to fundamental programming constructs, class design, inheritance, polymorphism, lists, dictionaries, files, and GUI programming.
Prerequisites: grade C or higher in CMPT-102 and junior or senior status.
Cross-listed with CMPG-742 Python Programming.
CMPT 353. Systems Programming. 3 Credits.
C programming language. Introduction to the UNIX/Linux operating system and shell programming. Design and implementation of selected systems software in the UNIX/Linux environment. Introduction to Perl. Fall. Prerequisite: A grade C or better in CMPT 102 or CMPT 201 and CMPT 238 or CMPT 239.
CMPT 358. Database Systems II. 3 Credits.
A continuation of 258. Introduction to middleware, database connectivity and Web development issues; ODBC, OLE DB, Active XData Objects (ADO); security. Prerequisite: A grade of C or better in CMPT 258.
CMPT 360. Object Oriented Design with Java. 3 Credits.
An introduction to object-oriented design using the programming language Java. Classes, objects, inheritance, abstract types, polymorphism, the Liskov substitution principle, design patterns, generics, iterators, and generators. Spring. Prerequisite: A grade C or better in CMPT 102 or CMPT 201.
CMPT 363. Data Mining. 3 Credits.
This course focuses on fundamental data mining algorithms and their applications in the process of knowledge discovery. The course will cover the general aspects and techniques of analyzing large, complex datasets, recognizing patterns and making predictions. The R programming language will also be introduced and used for hands-on experimentation with data mining algorithms.
Prerequisite: A grade of C or better in CMPT 258 or permission of the instructor.
Cross-listed with CMPG 763 Data Mining.
CMPT 364. Cloud Computing and Virtualization. 3 Credits.
This course offers an in-depth study of Cloud Computing and its underlying technologies, specifically Virtualization. Areas of discussion include the internal architecture of clouds, the architecture and structure of Virtual Machines, and cloud management, security, and optimizations. The course also covers Linux Containers and their features. The course supplements all the topics with tracing actual software code (Xen, KVM, QEMU, VirtualBox), study of the latest related research publications, and hands-on experience with the relevant technologies (AWS, Live Migration, Nested Virtualization).
Cross-listed with CMPG-764 Cloud Computing and Virtualization.
CMPT 367. Computer Security. 3 Credits.
This course provides a basic introduction to the key concepts in security. It covers basic concepts such as authentication, confidentiality, integrity, and non-repudiation as well as important techniques and applications. Topics include cryptography, access control, privacy, software/operating system security, and security policies. A course can be taken by juniors and seniors. Prerequisites: A grade C or higher in CMPT 335.
CMPT 368. Blockchain and Cryptocurrency Technologies. 3 Credits.
This course provides a comprehensive introduction to the revolutionary blockchain and cryptocurrency technologies. This course cover topics related to the new global money for the Internet age. This course explain how blockchain technology is transforming the Internet, allow students to understand bitcoin, cryptocurrencies and how they are disrupting the financial industry, have a comprehensive understanding of where blockchain technology is headed and how it can be leveraged. Prerequisite: grade C or higher in CMPT 238 or CMPT 239
Cross-listed with CMPG 758.
CMPT 369. Cyber Security Lab. 3 Credits.
In this course, students will learn computer and network security fundamentals by studying attacks on computer systems, networks, and the Web. Students will learn how these attacks work and how to detect and prevent the attacks. The course takes a hands-on approach by explaining theories via specially designed labs. Students are required to conduct a series of experimental exercises. Through these experiments, this course will help students enhance their understanding of principles and use these principles to solve practical problems.
Open to juniors and seniors.
Cross-listed with CMPG-769 Cyber Security Lab.
CMPT 370. Web Security. 3 Credits.
This course provides a comprehensive overview of Web security. The goal is to understand the most common web attacks and their countermeasures. We'll cover the fundamentals as well as the state-of-the-art in Web security. Topics include Principles of web security, attacks and countermeasures, denial-of-service, same-origin policy, cross site scripting, authentication, the web app vulnerabilities, injection, TLS attacks, privacy, etc. Course components include lectures, hands-on labs, 2-3 in-class quizzes, and one group course project.
Open to juniors and seniors.
Cross-listed with CMPG-770 Web Security.
CMPT 375. Internship for Juniors. 3 Credits.
Students participate in an off-campus training experience closely related to one of the areas of computer science. Frequent meetings with the advisor plus a paper are required. Prerequisites: Junior status, 3.0 GPA, and permission of the student's advisor or the Chair.
CMPT 415. Computer Graphics. 3 Credits.
Graphics primitives, two and three-dimensional transforms, clipping, hardware, projections, user interface, raster methods, hidden surface algorithms, color, shading, and ray tracing. Prerequisite: A grade of C or better in CMPT 238.
CMPT 420. Artificial Intelligence. 3 Credits.
This course will be a survey of the field of Artificial Intelligence. Topics include intelligent agents, informed and uninformed search, game trees and constraint satisfaction problems. Selected machine learning topics, such as decision trees and Bayesian network will also be discussed.
Prerequisite: A grade of C or better in CMPT 238 and CMPT 335 or permission of the instructor.
Cross-listed with CMPG 720 Artificial Intelligence.
CMPT 431. Multimedia. 3 Credits.
An introduction to multimedia capabilities of computers, including the storage and manipulation of large media files, network protocols for multimedia distribution, digital rights management, encodings for video and audio files, and methods for analyzing multimedia data. Prerequisite: CMPT 102 or permission of the instructor.
CMPT 438. Algorithms. 3 Credits.
Algorithm analysis techniques, worse-case analysis, greedy algorithms, divide and conquer algorithms, dynamic programming algorithms, branch-and-bound, and NP-completeness. Students will design algorithms, prove them correct, implement them, and then verify their implementation. Fall. Prerequisites: A grade of C or better in CMPT 102 or CMPT 201 and CMPT 238 and CMPT 335.
CMPT 439. Numerical Computation. 3 Credits.
Numerical techniques, types of errors, and accuracy of numerical solutions. Introduction to MATLAB. Solution of non-linear equations. Solution of systems of linear algebraic equations. Interpolation. Polynomial approximation. Numerical integration and differentiation. Nonlinear optimization. Students will learn numerical methods, utilize them in software, and then use this software for solving practical problems. Fall. Prerequisite: A grade of C or better in CMPT 102 or CMPT 201 and MATH 186.
CMPT 443. Computability Theory. 3 Credits.
Turing-computable functions, and their relationship to recursive functions. Formal languages, regularity, finite and push-down automata and their simulation. Universality of programs and Turing machines. Unsolvability and an introduction to the theory of computational complexity. Fall. Prerequisite: A grade of C or better in CMPT 335 or MATH 243.
CMPT 448. Cryptography & Security. 3 Credits.
This course provides a basic introduction to the principles and practice of cryptography and computer security. Topics include perfect secrecy, block ciphers, public key cryptosystems, key management, certificates, public key infrastructure (PKI), hash functions, digital signatures, non-repudiation, message authentication, access control, email and web security, intrusion detection, firewalls and security policies. Various security standards and protocols such as DES, AES, PGP, and SSL are also discussed.
Open to juniors and seniors.
Prerequisite: CMPT 335 with a grade of C or higher
Cross-listed with CMPG 768 - Cryptography and Security.
CMPT 454. Compiler Design. 3 Credits.
Introduction to automata and context-free grammars. Basic techniques of parsing and derivations. Generators, symbol tables, syntax-directed translation. Error detection, optimization, and data-flow analysis. Admission by permission of the Chair of the Department. This course is offered when demand warrants.
A study of the principles and methods advocated for the development of large and complex software systems. Each student will be required to participate in a team project devoted to the specification, design and implementation of a sizable software system. Spring. Prerequisite: A grade of C or better in CMPT 335 or CMPT 360.
CMPT 456. Software Engineering. 3 Credits.
A study of the principles and methods advocated for the development of large and complex software systems. Each student will be required to participate in a team project devoted to the specification, design and implementation of a sizable software system.
Prerequisite: CMPT 258 and CMPT 360 or permission of the instructor.
Cross-listed with CMPG 756 Software Engineering.
CMPT 463. Topics in Computer Science. 3 Credits.
Admission only by permission of the Chair of the Department. This course is offered when demand warrants.
CMPT 464. Topics in Computer Science. 3 Credits.
Admission only by permission of the Chair of the Department. This course is offered when demand warrants.
CMPT 465. Neural Networks and Learning Systems. 3 Credits.
This course provides the basic concepts of neural networks and other learning techniques including but not limited to: biological foundations of neural networks, basics of neural information processing, an artificial neuron and its activation function, multilayer feedforward neural networks and backpropagation learning, deep learning, Hopfield neural networks and associative memories, recurrent neural networks, support vector machines, validation of learning results, and clustering. Laboratory exercises provide experience with design and utilization neural and other machine learning algorithms and solving real-world classification, prediction, pattern recognition and intelligent data analysis problems. A course project will help students to develop their team-working skills and get a good experience in software project design.
Cross-listed with CMPG-765 Neural Networks and Learning Systems.
CMPT 466. Computer Networks. 3 Credits.
This is an introductory course to computer networks. It teaches the fundamentals of networking systems, their architecture, function and operation and how those fundamentals reflected in current network technologies. Topics include application layer protocols, Internet protocols, network interfaces, local and wide area networks, wireless networks, bridging and routing, and network security.
Prerequisites: CMPT 102 and CMPT 335 with grade C or higher.
CMPT 467. Special Topic: Networks. 3 Credits.
Admission by permission of the Chair of the Department. This course is offered when demand warrants.
CMPT 468. Topics in Computer Science. 3 Credits.
Admission by permission of the Chair of the Department. This course is offered when demand warrants.
CMPT 469. Independent Study. 3 Credits.
Individual study and/or research under faculty supervision.
CMPT 470. Mobile Computing. 3 Credits.
This course is designed for students interested in writing applications for modern mobile devices using Apple's iOS technology as the development platform. Topics include introduction to the Swift programming language (control flow, collections, optionals, functions, structures, classes, and protocols), the Xcode interface builder for iOS, auto layout and stack views, design patterns, segues, and table views. Students are required to have a MacBook with Xcode installed.
Prerequisites: A grade C or better in CMPT 238.
CMPT 471. Parallel Computing. 3 Credits.
In a parallel computation, multiple processors work together to solve a given problem. Currently, most computers are equipped with multicore processors. It is essential to learn how to use parallel machines effectively. In this course, students will learn about parallelism through shared-memory systems, distributed-memory systems, and GPUs. This course is about designing efficient programs to harness the power provided by modern parallel computers, so that the programs attain the highest possible levels of performance.
Open to juniors and seniors.
Cross-listed with CMPG 771.
CMPT 475. Internship for Seniors. 3 Credits.
Students participate in an off-campus training experience closely related to their area of computer science. Frequent meetings with the advisor plus a paper are required. Prerequisites: Senior status, 3.0 GPA, and permission of the student's advisor or the Chair.
CMPT 477. Image Processing & Analysis. 3 Credits.
This course provides the basic concepts of image processing and analysis including but not limited to image sensing and acquisition, visual perception, image enhancement (mostly spatial domain image enhancement, but some essential elements of the frequency domain enhancement will also be considered), image filtering in spatial and frequency domain, edge detection and image segmentation, elements of image restoration, image understanding and recognition, elements of color image processing. Laboratory exercises provide experience with design and software utilization of image processing algorithms and processing images related to various real-world applications (medical and satellite image processing, old images restoration, and digital photography). Students will program various algorithms and use their programs for processing real images. This will help them to accomplish specified challenges as they develop problem solving skills. A course project will help students to develop their team-working skills and get a good experience of software project design.
Open to juniors and seniors
Cross-listed with CMPG 767.
CMPT 478. Coding Interview Preparation: Algorithms, Data Structures and Skills. 3 Credits.
This elective course will help students prepare for the unique aspects of a coding job interview, with programming techniques, computer science foundations, strategic insights, practicing skills and some tips. Class meeting will consist of lectures and programming activities. Students will work on a lot of coding exercises to learn problem-solving techniques, improve the understanding of data structures and algorithms. The LeetCode platform will be used throughout the course. In addition, there will be an in-class programming competition and a mock interview session to allow students to get some practice in real-life simulated environments.
Open to juniors and seniors
Prerequisite: CMPT 238 or CMPT 239 with a grade of C or higher
Cross-listed with CMPT 478.
CMPT 490. Capstone. 4 Credits.
The aim of the capstone project in the senior year of Computer Science majors is to familiarize them with the process of solving real-world computational problems as practiced in industry. This course requires students to develop a project based on the knowledge and skills acquired in earlier coursework and integrate their knowledge and skills as a practical design effort. The work should be typically performed as a team project. Spring. Prerequisite: a grade of C or better in CMPT 360 or CMPT 456 or permission of the Department Chair.