51 courses with the subject COMP, 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.
COMP 10500Introduction to Website Development (LA)3
Introduction to the design and construction of responsive interactive websites using current technologies and tools. The course covers principles of effective website design, the design process, and implementation techniques. A term project building a large interactive, mobile-ready website is required. Students who have completed or are taking COMP 20500 may not receive credit for this course. (F,S,Y) Attributes: CA, CCCS, ESTS, MC
COMP 10700Introduction to 2D Game Development (LA)4
An introduction to the design, development, and implementation of two- dimensional (2-D) games. Topics to be covered will include principles of designing games and the computational methods and tools used to create game content. Some programming will be introduced, but no prior computing experience is needed. Students will also learn the basic principles of project management and teamwork. Concepts will be put into practice as teams design and develop their own 2-D game. The course will be a combination of lectures and hands-on exercises. (F,Y) Attributes: CA, MC
g This course starts with an in-depth coverage of Google Sheets followed by a brief introduction to relational databases. Daily and weekly projects are based on real-world datasets. COMP 11000 and HLTH 13901 are mutually exclusive; students may receive credit for only one. (F,S,Y) Attributes: QL
This course introduces students to SQLite through hands-on experience working with existing databases. Emphasis is placed on querying data, creating views, and using SQLite tools to explore and manipulate relational data in a lightweight, standalone environment. (F,Y) l
This course will introduce students to the command line interface (CLI), a text based method for interacting with computers. This method of interacting with computers is commonly used for cloud-based resources like servers and it is essential for anyone working in the cloud to master this approach. (S,Y)
COMP 11500Discrete Structures for Computer Science (LA)4
An introduction to discrete structures for computer science. The major topics of study include sets, proof techniques, logic, predicate logic, relations and functions, counting and probability, matrices, and induction.
An introduction to the principles and tools of data science focusing on exploratory data analysis. Topics include data collection, types of variables, mathematical representations of data, data cleaning and wrangling, data visualization and numerical summaries, the research cycle and methods, and data ethics. This course includes an introduction to the R programming language. MATH 14800 and COMP 14800 are crosslisted; students cannot earn credit for both. Prerequisites: Math placement in group 3 or higher, math placement assessment score of 46 or greater. (F,Y)
Student undertakes a project to design and implement a computer application under the guidance of one or more faculty members. May be repeated for a total of 6 credits. Prerequisites: Permission of the computer science faculty. 1-3 credits. (F,S,Y)
This course is an introduction to solving problems by writing code. Course content includes the design, development, testing, and analyzing of python code. Also included are basic coding structures that are present across many programing languages, such as statements, loops, and functions. (F-S,Y)
This course reinforces and extends the skills learned in "Computer Programming I". It introduces object-oriented programming, functional programming, and basic algorithmic analysis. End-of-semester projects make use of APIs and libraries to access real-world data-sets and explore how programs can be useful to other disciplines or areas of interest.
COMP 19000Selected Topics in Computer Science (LA)1-4
Topics to be determined by the instructor and the Department of Computer Science. May be repeated for credit for selected topics on different subjects. (IRR)
Subject
COMP
Credits (min)
1
Credits (max)
4
Credit unit
Credits
Type
course
Repeatable
May be repeated for credit for selected topics on different subjects.
COMP 19200Independent Study in Computer Science (LA)1-4
Enrichment and extension of the regular curriculum to areas not covered in existing courses. Arranged individually between student and faculty sponsor according to guidelines available from the department. (IRR)
This course explores game development using a game engine. Students learn the basics of game design and development while reinforcing their programming skills. The course culminates with students designing and developing their own games. Prerequisites: COMP 17200 with a grade of C or better. (S,Y)
This course covers the mathematical topics needed by Computer Science students. Topics include logic, sets, functions, relations, combinatorics and discrete probability. Experimental work is conducted with Google Sheets. Prerequisites: COMP 17100. (S,Y) 2026-2027 Catalog 391
This course investigates how computer scientists create data structures to organize computer memory efficiently. It covers foundational data structures such as arrays, linked-lists, trees, and hash tables, as well as abstract data types such as lists, stacks, queues, and maps. Students engage in the scientific process to study the performance of these different data structures from both theoretical and empirical perspectives. The course culminates with a final project where students apply these skills in a realistic context and measure the effect of efficient data structures. Prerequisites: COMP 17200 with a grade of C or better. (F,Y) Attributes: DSCI
Students undertake a project to design and implement a substantial computer application under the guidance of one or more faculty members. Permission of the computer science faculty required. May be repeated for a total of six credits. (F,S,Y)
COMP 29000Selected Topics in Computer Science (LA)1-4
Topics to be determined by the instructor and the Department of Computer Science. May be repeated for credit for selected topics on different subjects. (IRR)
Subject
COMP
Credits (min)
1
Credits (max)
4
Credit unit
Credits
Type
course
Repeatable
May be repeated for credit for selected topics on different subjects.
COMP 29200Independent Study in Computer Science (LA)1-4
Enrichment and extension of the regular curriculum to areas not covered in existing courses. Arranged individually between student and faculty sponsor according to guidelines available from the department. (IRR)
This course is a continuation of "Data Structures". It covers the three fundamental algorithm design techniques of "greedy", "divide and conquer", and "dynamic programming". It also covers the data structures needed by the featured algorithms: binary heaps, disjoint sets, directed/ undirected adjacency matrices, and directed/undirected adjacency lists. (S,Y)
COMP xxxxx Four elective courses in Computer 13-16 Science (at least one course must be a 4-credit course) •Select one course at any level •Select one course at the 200-, 300-, or 400-level •Select one course at the 300- or 400-level 4 •Select one course at the 400-level 4 MATHEMATICS REQUIREMENT Select one MATH course from the following list: (students 3-4 may not apply AP credit for MATH courses to this requirement):
This course covers the concepts of computer networks and data communications. The major topics include application layer protocols, transport layer protocols, routing, software defined networks, local area networks (including wifi), network security. The course has numerous lab components based on network-programming and packet tracing.
COMP 3700037001 Intermediate II Computer Project (NLA)1-3
After consultation with the computer science faculty, the student undertakes a project to design and implement a substantial computer application under the guidance of one or more faculty members. Permission of the computer science faculty required. May be repeated for a total of six credits. (F,S,Y)
Hands-on introduction to project design, development, implementation, and testing, with emphasis on the knowledge and skills required to successfully complete the production cycle, including team dynamics, market analysis, project management, documentation, and testing. Students work in teams on projects assigned by the instructor. TVR 38500 and COMP 38500 are cross listed courses; students cannot receive credit for both COMP 38500 and TVR 38500. Open only to Emerging Media majors. Prerequisites: COMP 20200; Junior Standing. (S,
COMP 39000Selected Topics in Computer Science (LA)1-4
Topics to be determined by the instructor and the Department of Computer Science. May be repeated for credit for selected topics on different subjects. (IRR)
Subject
COMP
Credits (min)
1
Credits (max)
4
Credit unit
Credits
Type
course
Repeatable
May be repeated for credit for selected topics on different subjects.
COMP 39200Independent Study in Computer Science (LA)1-4
Enrichment and extension of the regular curriculum to areas not covered in existing courses. Arranged individually between student and faculty sponsor according to guidelines available from the department. (IRR)
COMP 41000Algorithms + Organization = Systems (LA)4
In-depth investigation of the major concepts and implementation principles of computer systems (operating systems, networks, databases, etc.) through the exploration of seminal algorithms used in systems. Students read research papers and conduct experiments on algorithms in a systems environment. Topics may include scheduling, resource and storage allocation, problems of resolving deadlock, exclusion, and synchronization, memory allocation, secondary storage implementation, distributed system structures, switching, and IP addressing. Prerequisites: COMP 21000 and COMP 31100 both with a grade of C or better. (F,O)
An introduction to the fundamentals of computer graphics, including the mathematical foundations of graphics techniques; 2D and 3D algorithms for geometry, transformations, viewing, and lighting; stereo viewing, ray tracing, and radiosity. At least two different graphics APIs will be introduced and will be used to implement graphics programs and provide hands-on experience in the topics covered. Prerequisite: COMP 31100 or COMP 33000 with a grade of C or better. (IRR)
Capstone course in which students synthesize and apply the skills, methods, and knowledge acquired throughout their studies to a substantial data project. Emphasizes independent project design, execution, and professional presentation of results. MATH 44800 and COMP 44800 are crosslisted courses; credit can only be earned for one.
COMP 45500Search Engines and Recommender Systems (LA)4
Explores how information retrieval and recommendation systems such as Netflix, Facebook, and Pandora, are designed and implemented. Combines development of information retrieval skills such as web- crawling, text & multimedia processing, boolean & vector-space modeling, classification, clustering, and similarity analysis. Will involve hands- on implementation of computer softwarde systems. Prerequisites: COMP 22000 and one 300-level COMP or MATH course all with a grade of C or better. (S,O)
or COMP 45700Natural Language Processing Total Credits 24 4 Computer Science Minor 3-4 COMP 17100 and COMP 17200 are required in and can be shared across all majors and minors in the Computer Science department. No other 3-4 course can be counted in multiple majors and minors in the Computer Science department unless noted in that major or minors' curricula description.
This course explores classical statistical methods (naive Bayes, logistic regression, n-gram language models) for processing language data computationally, before focusing on the paradigm shift to neural networks and deep learning since the 2010s. Students will learn the mechanical underpinnings of processing text with neural networks, understand the processes used to train, build and refine Large Language Models (LLMs), and critically think about the ethical issues inherent in building modern language technologies. Prerequisites: COMP 35600 with a C or better and COMP 31100 with a C or better. (O,S) Attributes: DSCI
Students undertake a project to design and implement a substantial computer application under the guidance of one or more faculty members. May be repeated for a total of 6 credits. Prerequisites: Junior standing and permission of the computer science faculty. 1-3 credits. (F-
Offers students the opportunity to consolidate theory and apply concepts to a computer-based problem, thus enhancing their understanding of various facets of the computing discipline. Students are responsible for the analysis, design, development, documentation, implementation, and testing of the computer system. The project may be carried out singly or in small groups of up to four people. Prerequisites: Senior standing; permission of instructor. (F-S,Y)
Working as part of a team, the student designs, develops, and documents a significant emerging digital media project under the guidance of one or more faculty members. TVR 48500 and COMP 48500 are cross listed courses; students cannot receive credit for both COMP 48500 and TVR 48500. Prerequisites: COMP 38500 or TVR 38500 with a minimum grade of C-. (S, Y) Attributes: PROD
COMP 49000Selected Topics in Computer Science (LA)1-4
Topics to be determined by the instructor and the Department of Computer Science. May be repeated for credit for selected topics on different subjects. (IRR)
Subject
COMP
Credits (min)
1
Credits (max)
4
Credit unit
Credits
Type
course
Repeatable
May be repeated for credit for selected topics on different subjects.
COMP 49200Independent Study in Computer Science (LA)1-4
Enrichment and extension of the regular curriculum to areas not covered in existing courses. Arranged individually between student and faculty sponsor according to guidelines available from the department. (IRR)
Students explore connections between the integrative core curriculum, their computer science major, other learning experiences while at Ithaca College or abroad, and future goals. Students create a written reflection that integrates their various learning experiences and how their experience at Ithaca College has prepared them to achieve their future goals. Students also prepare a cover letter, curriculum vitae, and personal statement and identify career opportunities; and develop a showcase electronic portfolio. Prerequisites: Senior Standing; Computer Science and Emerging Media Computation majors only. (F,Y) Attributes: CP
COMP 49800Computer Science Internship for Majors and Minors (NLA)1-12
A computer science project (carried out within an organization outside the department) that is not routine, entails significant work experience, and has substantial academic content. The student is responsible for developing a project proposal and completing it in conjunction with a faculty sponsorfrom the department and a supervisor from the outside organization. At the end of the project, thestudent shall present a report based on the experience. With departmental approval, up to 4 credits may be counted as upper-level elective credit toward a major in computer science or mathematicscomputer science or a minor in the Computer Science Department. Students should have completed three-fourths of the major or minor to be eligible for this opportunity. Artificial Intelligence — B.S. Students must achieve a C or better in all courses required for the major.
