CS - Computer Science

This introduction to computer science, developed by Google and their university partners, emphasizes problem solving and data analysis skills along with computer programming skills. Using Python, students learn design, implementation, testing, and analysis of algorithms and programs. Problems will be chosen from real-world examples such as graphics, image processing, cryptography, data analysis, astronomy, video games, and environmental simulation. Students get instruction from a world-class computer science professor, delivered remotely through video and interactive media, then work on collaborative projects in groups with coaching by their instructors. Prior programming experience is not a requirement for this course. 

Prerequisites: Level II placement on the Basic Math Skills Inventory or MATH 099 or permission of the instructor. An introduction to computational thinking by developing computer programs to create images, animations, visualizations, and interactive art. Topics include computational thinking, problem solving, programming in the Processing language, impact of technology on society and contemporary issues.

Prerequisites: Level II or higher math placement or MATH 099 or permission of the instructor.  An introduction to the use of computers applied to music; using applications and developing computer programs to create, record and edit musical information. This course combines computational thinking, music theory and algorithmic composition. Topics include computational thinking, problem solving, programming in the Chuck language, impact of technology on society, and contemporary issues.

This course introduces students to the importance of gathering, cleaning, normalizing, visualizing and analyzing data to drive informed decision-making, no matter the field of study. Students will learn to use a combination of tools and techniques, including spreadsheets, SQL and Python to work on real-world data sets using a combination of procedural and basic machine learning algorithms. They will also learn to ask good, exploratory questions and develop metrics to come up with a well thought-out analysis. 

Prerequisites: Level III placement on the Basic Math Skills inventory or MATH 120 (may be taken concurrently). General programming techniques for students who have had some previous experience with computer programming. Topics include: algorithmic problem solving, top-down design, object-oriented programming and design, and an introduction to abstract data types. Instruction in a high-level programming language.

Prerequisites: CS 201 and MATH 207 (or concurrent enrollment) or permission of the instructor. An introduction to the structuring and manipulation of information with implementation in the high-level programming language Java. Topics include: linked lists, sets, stacks, queues and trees; basic manipulation techniques including sort/merge and search algorithms; an introduction to algorithm efficiency analysis.

Prerequisite: CS 202 and MATH 207 Intensive introduction to object-oriented programming and advanced data structures. Topics include heaps, priority queues, hash tables, B+, B* trees and graphs. Emphasizing advantages and disadvantages of design and implementation choices, and the way these choices affect software quality. Instruction will be in the C++ programming language.

Prerequisites: CS 201 and MATH 207 or permission of the instructor. A comprehensive introduction to the general organization, architecture and functional characteristics of computer systems. Topics include machine level representation of data, assembly level machine organization, memory systems organization and architecture, alternative architectures and device interfaces.

This course is a general topics course in computer science allowing faculty and students to study particular special interests.

Prerequisites: Completion of the Social and Behavioral Analysis section or Historical Analysis section or Philosophical Inquiry section of the Core or permission of the instructor. Computer technology is a driving factor in globalization. This course studies the past, present and future impact of computer and communications technology on society, education, government and the workplace around the world. Topics covered cross national, cultural, and continental boundaries.

Prerequisites: CS 219, MATH 201 and MATH 207 (grade of C- or higher) or permission of the instructor. Introduction to the analysis and design of algorithms. Topics include: sorting, searching, advanced tree structures, graph algorithms, network flow problems, amortized analysis, divide-and-conquer, greedy algorithms, dynamic programming, combinatorial search algorithms, computational geometry and NP-completeness.

Prerequisite: CS 202 or permission of the instructor. This course will examine and discuss the life cycle of computer software. The major issues addressed are: analysis of the project, requirements specification, design, coding, testing and reliability and maintenance.

Prerequisite: CS 202 permission of the instructor. Design and implementation of databases from a real world applications point of view. The course includes database concepts such as basic architectural issues, the relational model, query processing, logical database design and normalization theory and data protection issues.

Prerequisite: Permission of the department. An opportunity for students to serve as teaching assistants in the computer science program. Under faculty supervision, assistants will work with students in laboratory and help sessions for introductory courses. May be repeated for a maximum of 4 credits. Grading is on a satisfactory/unsatisfactory basis.

Prerequisite: Permission of the instructor. The study of selected topics in computer science, accomplished through readings, problem assignments and projects.

An upper-level special topics course offered at the discretion of the department. The content and methods vary with the interest of students and faculty members

Prerequisites: 21 credits of computer science courses at the 200-level or above and permission of the department. Supervised work in computer-related projects in a governmental, private-industrial or educational setting. In order to enroll in this course, a student must meet College internship requirements. Grading is on a satisfactory/unsatisfactory basis.

Prerequisite: Junior standing and CS 219 or permission of the instructor. History, fundamental principles, and future directions of A.I. Topics include state-space searching, knowledge representation, logic and deduction, natural language processing, neural networks, learning, vision, robotics, and cognitive science. Topics will be treated at a level of depth and detail appropriate for a first course in AI.

Prerequisites: Junior standing and CS 428 or permission of the instructor. Introduction to the field of modeling learning with computers. Topics included are explorations of inductive learning, learning decision trees, ensemble learning, computational learning theory, and statistical learning methods.

Prerequisites: Junior standing and CS 428 or permission of the instructor Comprehensive examination of the theory and practice behind robot-building and the deployment of intelligent systems. Topics are divided between robot architectures (control paradigms, kinematics, sensors, actuators and navigation) and cognitive robotics (learning, decision-making, coordination and cooperation).

Prerequisite: CS 226 or permission of the instructor. Introduction to combinational and sequential circuit design. Topics include Boolean algebra and simplification techniques, arithmetic circuits, decoders, flip-flops, counters, registers, memory systems, analog-to-digital conversion and VHDL programming.

Prerequisites: CS 226. Foundations of networking technology and understanding of challenges faced in design and architecture of Data networks. Topics include networking principles, Transmission, Control Protocol, Internet Protocol, data encoding/decoding techniques and wireless communication.

Prerequisites: CS 226 and CS 219 or permission of the instructor. An in-depth study of architectural concepts and principles including performance-based design tradeoffs. Topics to be covered include: instruction set design, arithmetic algorithms, hardwired and microprogrammed control, memory hierarchy design, input/output, pipelines, RISC, CISC, vector processors, parallel processors and superscalar machines.

Prerequisites: CS 226 and CS 219 or permission of the instructor. Fundamental principles of operating systems. Topics include: process management; concurrency; deadlock; CPU scheduling; memory management; disk management; files systems; security; and distributed, real-time and multiprocessor operating systems.

Prerequisites: Junior standing and CS 219 or permission of the instructor. A comprehensive introduction to both the principles and the practice of parallel computing. Topics to be covered include: programming and architectural models, parallel algorithms and parallelizing compilers.

Prerequisites: CS 226 and CS 219. A survey of the major programming paradigms and their related languages, including procedural, functional, logic and object-oriented programming. Topics include: binding, exception handling, data sharing, scope, parameter passing, type checking, runtime storage management, lexical analysis, syntactic analysis, parsing, code generation and optimization.

Prerequisites: CS 329 and senior standing, or permission of the instructor. Course focuses on cultivating proficiency in technical communication, using appropriate research methods, enhancing the ability to identify computational problems, properly state research questions, critically assess scientific literature, present data and results, work in teams and improve technical writing and time management skills.

Prerequisites: CS 324, CS 474 and senior standing, or permission of the instructor Students majoring in computer science complete a capstone project, serving as a culmination of their studies. The project entails the development of a significant piece of software or carrying out a research study by a student team, supervised by a designated faculty member within the department and evaluated by a faculty committee.

Prerequisite: By invitation of the department. The departmental honors paper is a two-semester senior-year program designed for students who wish to pursue intensive research or special projects in close coordination with faculty advisers. Departmental honors students are known as the Christine P. Tischer Scholars and receive 6 credits for this work.