41 courses with the subject CMPT, each shown exactly as we captured it from the college's catalog, with every element we hold. Where the wording looks broken, that is our reading of the catalog, not the college's text.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
A study of foundations used in computing models and simulations, including models and simulations in machine learning and cybersecurity. This includes a study of computational linear algebra (spaces, linear transformations, systems of linear equations including overdetermined systems) and applied probability (counting techniques, probability, random variables and distributions, statistical analysis). Prerequisite: A grade of C or better in CMPT-335 and MATH-185.
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.
This course provides an overview of Python programming and covers the fundamentals, the object-oriented features, and design of applications. 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 class design, inheritance, polymorphism, design of applications, and AI-related applications in particular. Prerequisites: grade C or higher in CMPT-102 or in BUAN-205 or in CIS-205. Cross-listed with CMPG-742 Python Programming.
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.
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.
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. Prerequisites: Open to juniors and seniors majoring in Computer Science, Computer Information Systems, Electrical Engineering, and Computer Engineering OR Instructor's permit OR Department Chair's permit Cross-listed with CMPG-763 Data Mining.
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.
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.
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.
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.
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.
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.
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: Prerequisites: Open to juniors and seniors majoring in Computer Science, Computer Information Systems, Electrical Engineering, and Computer Engineering OR CMPT-335 OR Instructor's permit OR Department Chair's permit Cross-listed with CMPG-720 Artificial Intelligence.
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.
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.
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.
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.
Admission only by permission of the Chair of the Department. This course is offered when demand warrants.
Admission only by permission of the Chair of the Department. This course is offered when demand warrants.
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. Prerequisites: Open to juniors and seniors majoring in Computer Science, Computer Information Systems, Electrical Engineering, and Computer Engineering OR CMPT-335 OR Instructor's permit OR Department Chair's permit Cross-listed with CMPG-465 Neural Networks and Learning Systems.
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.
Admission by permission of the Chair of the Department. This course is offered when demand warrants.
Individual study and/or research under faculty supervision.
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.
This course introduces the principles and practice of parallel computing, with a focus on modern applications in artificial intelligence. Students will learn models of parallel computation, parallel architectures, and programming techniques such as message passing, shared memory, and GPU computing. The course emphasizes design, analysis, and implementation of parallel algorithms, highlighting their role in accelerating AI and machine learning tasks. Topics include parallel sorting and searching, matrix operations, and neural network training. Case studies will demonstrate how parallel computing enables large-scale deep learning, and other AI-related applications. By the end of the course, students will be able to analyze problems for parallelism, implement parallel solutions, and evaluate performance trade-offs. Prerequisites: Open to juniors and seniors majoring in Computer Science, Computer Information Systems, Electrical Engineering, and Computer Engineering OR Instructor's permit OR Department Chair's permit Cross-listed with CMPG-771 Parallel Computing.
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.
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.
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.
This course focuses on the Linux Kernel, a large-scale open source software project. Topics include in-depth discussions, and hands-on modifications of the Linux memory, process, storage, and network sub-systems. Programming topics include creating kernel modules, simple device drivers, as well as modifying and compiling the kernel source code. Cross-listed with CMPG-780.
This course introduces the fundamentals of deep learning and generative artificial intelligence (AI), focusing on both theoretical understanding and practical implementation. Students will learn core deep learning concepts, deep neural networks architectures, convolutional neural networks, image recognition using convolutional neural networks, generative AI neural network architectures, and state-of-the-art generative AI models. Applications of generative AI in text and image generation will be considered. The course emphasizes hands-on work, with biweekly projects that build towards a final course project. Prerequisites: Open to juniors and seniors majoring in Computer Science, Computer Information Systems, Electrical Engineering, and Computer Engineering OR CMPT-335 OR Instructor's permit OR Department Chair's permit Cross-listed with CMPG-785.
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 456 or permission of the Department Chair.
Source: Manhattan College's catalog, linked per course · table learning_unit · CourseShelf publish 61
