A.B. Computer Science

Princeton University

Bachelor's degree

In Princeton (USA)

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Description

  • Type

    Bachelor's degree

  • Location

    Princeton (USA)

The Department of Computer Science (link is external) curriculum encourages students to learn fundamental concepts of the discipline and to become proficient in the use of advanced computer systems. The plan provides opportunities for study in software systems, algorithms and complexity, machine architecture, computer graphics, programming languages, machine learning, and other core areas of computer science. Most computer science students enjoy programming and are given ample opportunity to do so within the curriculum.

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Princeton (USA)
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08544

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Subjects

  • Computational
  • Network Training
  • Programming
  • Engineering
  • Technology
  • Systems
  • Project
  • Private
  • Web
  • Graphics
  • Design
  • Algorithms
  • Network
  • Internet
  • Networks
  • Computing
  • Staff

Course programme

COS 109 Computers in Our World (also

EGR 109

) Fall QR Computers are all around us. How does this affect the world we live in? This course is a broad introduction to computing technology for humanities and social science students. Topics will be drawn from current issues and events, and will include discussion of how computers work, what programming is and why it is hard, how the Internet and the Web work, security and privacy. Two 90-minute lectures. Self-scheduled computer laboratory. B. Kernighan

COS 116 The Computational Universe (also

EGR 116

) Not offered this year STL Computers have brought the world to our fingertips. This course explores at a basic level the science "old and new" underlying this new computational universe: propositional logic of the ancient Greeks (microprocessors); quantum mechanics (silicon chips); network and system phenomena (internet and search engines); computational intractability (secure encryption); and efficient algorithms (genomic sequencing). Ultimately, this study makes us look anew at ourselves: our genome; language; music; "knowledge"; and, above all, the mystery of our intelligence. Two 90-minute lectures, one three-hour laboratory. A. Finkelstein

COS 126 Computer Science: An Interdisciplinary Approach (also

EGR 126

) Fall/Spring QR An introduction to computer science in the context of scientific, engineering, and commercial applications. The course will teach basic principles and practical issues, and will prepare students to use computers effectively for applications in computer science, physics, biology, chemistry, engineering, and other disciplines. Topics include: hardware and software systems; programming in Java; algorithms and data structures; fundamental principles of computation; and scientific computing, including simulation, optimization, and data analysis. No prior programming experience required. Video lectures, one or two classes, two preceptorials. R. Sedgewick

COS 217 Introduction to Programming Systems Fall/Spring QR An introduction to computer organization and system software. The former includes topics such as processor and memory organization, input/output devices, and interrupt structures. The latter includes assemblers, loaders, libraries, and compilers. Programming assignments are implemented in assembly language and C using the UNIX operating system. Three lectures. Prerequisite: 126 or instructor's permission. A. Appel

COS 226 Algorithms and Data Structures Fall/Spring QR This course surveys the most important algorithms and data structures in use on computers today. Particular emphasis is given to algorithms for sorting, searching, and string processing. Fundamental algorithms in a number of other areas are covered as well, including geometric algorithms, graph algorithms, and some numerical algorithms. The course will concentrate on developing implementations, understanding their performance characteristics, and estimating their potential effectiveness in applications. Two online lectures, two class meetings, one precept. K. Wayne

COS 231 An Integrated, Quantitative Introduction to the Natural Sciences I (See ISC 231)

COS 232 An Integrated, Quantitative Introduction to the Natural Sciences I (See ISC 232)

COS 233 An Integrated, Quantitative Introduction to the Natural Sciences II (See ISC 233)

COS 234 An Integrated, Quantitative Introduction to the Natural Sciences II (See ISC 234)

COS 306 Contemporary Logic Design (See ELE 206)

COS 314 Computer and Electronic Music through Programming, Performance, and Composition (See MUS 314)

COS 318 Operating Systems Fall A study of the design and analysis of operating systems. Topics include: processes, mutual exclusion, synchronization, semaphores, monitors, deadlock prevention and detection, memory management, virtual memory, processor scheduling, disk management, file systems, security, protection, distributed systems. Two 90-minute lectures. Prerequisites: 217 and 226 or instructor's permission. J. Singh

COS 320 Compiling Techniques Spring The principal algorithms and concepts associated with translator systems. Topics include lexical analysis, syntactic analysis, parsing techniques, symbol table management, code generation and optimization, run time system design, implementation issues related to programming language design. Course will include a large-scale programming project utilizing the above topics. Three lectures. Prerequisites: 217 and 226 or instructor's permission. D. August

COS 323 Computing and Optimization for the Physical and Social Sciences (See ORF 363)

COS 333 Advanced Programming Techniques Fall/Spring The practice of programming. Emphasis is on the development of real programs, writing code but also assessing tradeoffs, choosing among design alternatives, debugging and testing, and improving performance. Issues include compatibility, robustness, and reliability, while meeting specifications. Students will have the opportunity to develop skills in these areas by working on their own code and in group projects. Two 90-minute lectures. Prerequisites: 217 and 226 (as corequisite). B. Kernighan, R. Dondero Jr.

COS 340 Reasoning about Computation Fall/Spring QR An introduction to mathematical topics relevant to computer science. Combinatorics and probability will be covered in the context of computer science applications. The course will present a computer science approach to thinking and modeling through such topics as dealing with uncertainty in data and handling large data sets. Students will be introduced to fundamental concepts such as NP-completeness and cryptography that arise from the world view of efficient computation. Prerequisites COS 126 and 226 (or sufficient mathematical background), and MAT 202 or MAT 204 or MAT 217. COS 226 can be taken along with COS 340 in the same term. R. Raz, B. Chazelle

COS 342 Introduction to Graph Theory (See MAT 375)

COS 351 Information Technology and Public Policy (See WWS 351)

COS 375 Computer Architecture and Organization (also

ELE 375

) Spring STN An introduction to computer architecture and organization. Instruction set design; basic processor implementation techniques; performance measurement; caches and virtual memory; pipelined processor design; design trade-offs among cost, performance, and complexity. Two 90-minute classes, one self-scheduled hardware laboratory. Prerequisites: COS 217. M. Martonosi

COS 381 Networks: Friends, Money and Bytes (See ELE 381)

COS 396 Introduction to Quantum Computing (See ELE 396)

COS 397 Junior Independent Work (B.S.E. candidates only) Fall Offered in the fall, juniors are provided with an opportunity to concentrate on a "state-of-the-art" project in computer science. Topics may be selected from suggestions by faculty members or proposed by the student. B.S.E. candidates only. A. Gupta

COS 398 Junior Independent Work (B.S.E. candidates only) Spring Offered in the spring, juniors are provided with an opportunity to concentrate on a "state-of-the-art" project in computer science. Topics may be selected from suggestions by faculty members or proposed by the student. B.S.E. candidates only. A. LaPaugh

COS 402 Machine Learning and Artificial Intelligence Not offered this year This course will provide a basic introduction to the core principles, algorithms and techniques of modern artificial intelligence and machine learning research and practice. Main topics will include: 1. Problem solving using search, with applications to game playing 2. Probabilistic reasoning in the presence of uncertainty 3. Hidden Markov models and speech recognition 4. Markov decision processes and reinforcement learning 5. Machine learning using decision trees, neural nets and more. 6. Basic principles of mathematical optimization for learning. Prerequisites- COS 226 and COS 340 Staff

COS 423 Theory of Algorithms Spring Design and analysis of efficient data structures and algorithms. General techniques for building and analyzing algorithms. Introduction to NP-completeness. Two 90-minute lectures. Prerequisites: 226 and 340 or instructor's permission. R. Tarjan

COS 424 Fundamentals of Machine Learning (also

SML 302

) Not offered this year Computers have made it possible to collect vast amounts of data from a wide variety of sources. It is not always clear, however, how to use the data, and how to extract useful information from them. This problem is faced in a tremendous range of social, economic and scientific applications. The focus will be on some of the most useful approaches to the problem of analyzing large complex data sets, exploring both theoretical foundations and practical applications. Students will gain experience analyzing several types of data, including text, images, and biological data. Two 90-minute lectures. Prereq: MAT 202 and COS 126 or equivalent. Staff

COS 425 Database and Information Management Systems Not offered this year Theoretical and practical aspects of database systems and systems for accessing and managing semi-structured information (e.g., Web information repositories). Topics include: relational and XML models, storage and indexing structures, query expression and evaluation, concurrency and transaction management, search effectiveness. Two 90-minute lectures. Prerequisites: 217 and 226. A. LaPaugh

COS 426 Computer Graphics Spring The principles underlying the generation and display of graphical pictures by computer. Hardware and software systems for graphics. Topics include: hidden surface and hidden line elimination, line drawing, shading, half-toning, user interfaces for graphical input, and graphic system organization. Two 90-minute lectures. Prerequisites: 217 and 226. A. Finkelstein

COS 429 Computer Vision Fall An introduction to the concepts of 2D and 3D computer vision. Topics include low-level image processing methods such as filtering and edge detection; segmentation and clustering; optical flow and tracking; shape reconstruction from stereo, motion, texture, and shading. Throughout the course, there will also be examination of aspects of human vision and perception that guide and inspire computer vision techniques. Prerequisites: 217 and 226. Two 90-minute lectures. O. Russakovsky

COS 432 Information Security (also

ELE 432

) Fall/Spring Security issues in computing, communications, and electronic commerce. Goals and vulnerabilities; legal and ethical issues; basic cryptology; private and authenticated communication; electronic commerce; software security; viruses and other malicious code; operating system protection; trusted systems design; network security; firewalls; policy, administration and procedures; auditing; physical security; disaster recovery; reliability; content protection; privacy. Prerequisites: 217 and 226. Two 90-minute lectures. A. Narayanan, P. Mittal

COS 433 Cryptography (also

MAT 473

) Spring An introduction to modern cryptography with an emphasis on fundamental ideas. The course will survey both the basic information and complexity-theoretic concepts as well as their (often surprising and counter-intuitive) applications. Among the topics covered will be private key and public key encryption schemes, digital signatures, pseudorandom generators and functions, chosen ciphertext security; and time permitting, some advanced topics such as zero knowledge proofs, secret sharing, private information retrieval, and quantum cryptography. Prerequisites: 226 or permission of instructor. Two 90-minute lectures. M. Zhandry

COS 435 Information Retrieval, Discovery, and Delivery Not offered this year This course studies both classic techniques of indexing documents and searching text, and also new algorithms that exploit properties of the World Wide Web, digital libraries, and multimedia collections. There is significant emphasis on current methods employed by Web search engines, including methods of employing user profiles to enhance search results. Pragmatic issues of handling very large amounts of information that may be widely dispersed--caching, distributed storage, and networking technology--are also covered. Prerequisite: COS 226 and MAT 202. Two 90-minute lectures. A. LaPaugh

COS 436 Human-Computer Interface Technology (also

ELE 469

) Not offered this year Creating technologies that fit into people's everyday lives involves more than having technically sophisticated algorithms, systems, and infrastructure. It involves understanding how people think and behave and using this data to design user-facing interfaces that enhance and augment human capabilities. Introduction to the field of human-computer interaction and the tools, techniques, and principles that guide research on people. Design and implement user-facing systems that bring joy rather than frustrate the user and put these skills into practice in a group project involving the creation of an interactive system. Prerequisite COS 217. Staff

COS 441 Programming Languages Not offered this year How to design and analyze programming languages and how to use them effectively. Functional programming languages, object-oriented languages; type systems, abstraction mechanisms, operational semantics, safety and security guarantees. Implementation techniques such as object representations and garbage collection will also be covered. Prerequisites: COS 217 and 226. Three lectures. Staff

COS 448 Innovating Across Technology, Business, and Marketplaces (also

EGR 448

) Spring This course introduces engineering students to the types of issues that are tackled by leading and innovative Chief Technology Officers: the technical visionaries and/or managers at companies who innovate at the boundaries of technology, business, and marketplaces by understanding all of these areas deeply. These individuals are true partners to the business leaders of the organization, not merely implementers of business goals. The focus will be on software technologies and businesses based on them. To use specific contexts, we will emphasize two complementary areas as examples: businesses based on cloud computing and on marketplaces. J. Singh

COS 451 Computational Geometry Not offered this year Introduction to basic concepts of geometric computing, illustrating the importance of this new field for computer graphics, solid modelling, robotics, databases, pattern recognition, and statistical analysis. Algorithms for geometric problems. Fundamental techniques, for example, convex hulls, Voronoi diagrams, intersection problems, multidimensional searching. Two 90-minute lectures. Prerequisites: 226 and 340 or 341, or equivalent. B. Chazelle

COS 455 Introduction to Genomics and Computational Molecular Biology (See QCB 455)

COS 461 Computer Networks Spring This course studies computer networks and the services built on top of them. Topics include packet-switch and multi-access networks, routing and flow control, congestion control and quality-of-service, Internet protocols (IP, TCP, BGP), the client-server model and RPC, elements of distributed systems (naming, security, caching) and the design of network services (multimedia, peer-to-peer networks, file and Web servers, content distribution networks). Two lectures, one preceptorial. Prerequisite: 217. N. Feamster

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A.B. Computer Science

Price on request

The best Other Science courses

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