Course Schedule

Current semester Spring 2014, and future semesters are now available to view.

View undergraduate course grid View graduate course grid

Number

Name

Professor(s)

Meet Time

Room

CSCI-GA.1144-001
(1151) PAC II Mohamed Zahran
Office Hours T 6:00-8:30PM CIWW 312

This course builds directly on the foundation developed in PAC I, covering the essentials of computer organization through the study of assembly language programming and C, as well as introducing the students to the analysis of algorithms. Topics include: (1) Assembly language programming for the Intel chip family, emphasizing computer organization, the Intel x86 instruction set, the logic of machine addressing, registers and the system stack. (2) Programming in the C language, a general-purpose programming language which also has low-level features for systems programming. (3) An introduction to algorithms, including searching, sorting, graph algorithms and asymptotic complexity. Examples and assignments reinforce and refine those first seen in PAC I and often connect directly to topics in the core computer science graduate courses, such as Programming Languages, Fundamental Algorithms, and Operating Systems

Prerequisites: CSCI-GA 1133 or departmental permission.
CSCI-GA.1144-002
(1862) PAC II Recitation Rohit Gupta R 7:10-8:00PM CIWW 312

This course builds directly on the foundation developed in PAC I, covering the essentials of computer organization through the study of assembly language programming and C, as well as introducing the students to the analysis of algorithms. Topics include: (1) Assembly language programming for the Intel chip family, emphasizing computer organization, the Intel x86 instruction set, the logic of machine addressing, registers and the system stack. (2) Programming in the C language, a general-purpose programming language which also has low-level features for systems programming. (3) An introduction to algorithms, including searching, sorting, graph algorithms and asymptotic complexity. Examples and assignments reinforce and refine those first seen in PAC I and often connect directly to topics in the core computer science graduate courses, such as Programming Languages, Fundamental Algorithms, and Operating Systems

Prerequisites: CSCI-GA 1133 or departmental permission.
CSCI-GA.1170-001
(1152) Fundamental Algorithms Alan Siegel
Office Hours M 5:10-7:00PM CIWW 102

Reviews a number of important algorithms, with emphasis on correctness and efficiency. The topics covered include solution of recurrence equations, sorting algorithms, selection, binary search trees and balanced-tree strategies, tree traversal, partitioning, graphs, spanning trees, shortest paths, connectivity, depth-first and breadth-first search, dynamic programming, and divide-and-conquer techniques.

Prerequisites: At least one year of experience with a high-level language such as Pascal, C, C++, or Java; and familiarity with recursive programming methods and with data structures (arrays, pointers, stacks, queues, linked lists, binary trees).
CSCI-GA.1170-002
(1153) Fundamental Algorithms Recitation Alan Siegel
Office Hours R 5:10-6:00PM CIWW 109

Reviews a number of important algorithms, with emphasis on correctness and efficiency. The topics covered include solution of recurrence equations, sorting algorithms, selection, binary search trees and balanced-tree strategies, tree traversal, partitioning, graphs, spanning trees, shortest paths, connectivity, depth-first and breadth-first search, dynamic programming, and divide-and-conquer techniques.

Prerequisites: At least one year of experience with a high-level language such as Pascal, C, C++, or Java; and familiarity with recursive programming methods and with data structures (arrays, pointers, stacks, queues, linked lists, binary trees).
CSCI-GA.2110-001
(1154) Programming Languages Cory Plock
Office Hours T 5:10-7:00PM CIWW 101

Discusses the design, use, and implementation of imperative, object-oriented, and functional programming languages. The topics covered include scoping, type systems, control structures, functions, modules, object orientation, exception handling, and concurrency. A variety of languages are studied, including C++, Java, Ada, Lisp, and ML, and concepts are reinforced by programming exercises.

Prerequisites: Students taking this class should already have substantial programming experience.
CSCI-GA.2110-002
(1155) Programming Languages Recitation Abhinand Sundararajan R 6:10-7:00PM CIWW 109

Discusses the design, use, and implementation of imperative, object-oriented, and functional programming languages. The topics covered include scoping, type systems, control structures, functions, modules, object orientation, exception handling, and concurrency. A variety of languages are studied, including C++, Java, Ada, Lisp, and ML, and concepts are reinforced by programming exercises.

Prerequisites: Students taking this class should already have substantial programming experience.
CSCI-GA.2112-001
MATH-GA 2043-001
(1156) Scientific Computing Yu Chen R 7:10-9:00PM CIWW 1302
Methods for numerical applications in the physical and biological sciences, engineering, and finance. Basic principles and algorithms; specific problems from various application areas; use of standard software packages.

Prerequisites: Multivariate calculus and linear algebra. Some programming experience recommended.
CSCI-GA.2130-001
(1157) Compiler Construction Kristoffer Rose
Office Hours M 7:10-9:00PM CIWW 202
This is a capstone course based on compilers and modern programming languages. The topics covered include structure of one-pass and multiple-pass compilers; symbol table management; lexical analysis; traditional and automated parsing techniques, including recursive descent and LR parsing; syntax-directed translation and semantic analysis; run-time storage management; intermediate code generation; introduction to optimization; and code generation. The course includes a special compiler-related capstone project, which ties together concepts of algorithms, theory (formal languages), programming languages, software engineering, computer architecture, and other subjects covered in the MS curriculum. This project requires a substantial semester-long programming effort, such as construction of a language compilation or translation system that includes lexical and syntactic analyzers, a type checker, and a code generator.

Prerequisites: CSCI-GA 1170, CSCI-GA 2110, and CSCI-GA 2250.
CSCI-GA.2250-001
(1158) Operating Systems Hubertus Franke
Office Hours T 7:10-9:00PM CIWW 109
The topics covered include a review of linkers and loaders and the high-level design of key operating systems concepts such as process scheduling and synchronization; deadlocks and their prevention; memory management, including (demand) paging and segmentation; and I/O and file systems, with examples from Unix/Linux and Windows. Programming assignments may require C, C++, Java, or C#.
CSCI-GA.2262-001
(1159) Data Communications and Networks Jean-Claude Franchitti
Office Hours R 7:10-9:00PM CIWW 102

This course teaches the design and implementation techniques essential for engineering robust networks. Topics include networking principles, Transmission Control Protocol/Internet Protocol, naming and addressing (Domain Name System), data encoding/decoding techniques, link layer protocols, routing protocols, transport layer services, congestion control, quality of service, network services, programmable routers and overlay networks.

Prerequisites: Students must have a working knowledge of fundamental data structures and associated algorithms. For some of the practical aspects of the course, a working knowledge of an object-oriented programming language (e.g., C++, C#, or preferably Java) is expected. An undergraduate course in data communication and networks is helpful but not required.
CSCI-GA.2271-001
(14571) Computer Vision Davi Geiger
Office Hours W 7:10-9:00PM CIWW 101

Basic techniques of computer vision and image processing. General algorithms for image understanding problems. Study of binary image processing, edge detection, feature extraction, motion estimation, color processing, stereo vision, and elementary object recognition. Mathematical, signal processing, and image processing tools. Relation of computer vision algorithms to the human visual system.

Prerequisites: CSCI-GA 1170
CSCI-GA.2421-001
MATH-GA 2020-001
(1161) Numerical Methods II Jonathan Goodman R 5:10-7:00PM CIWW 512
Numerical linear algebra. Approximation theory. Quadrature rules and numerical integration. Nonlinear equations and optimization. Ordinary differential equations. Elliptic equations. Iterative methods for large, sparse systems. Parabolic and hyperbolic equations.

Prerequisites: Corequisite: linear algebra.
CSCI-GA.2433-001
(1162) Database Systems Zvi Kedem
Office Hours M 7:10-9:00PM CIWW 109
Database system architecture. Modeling an application and logical database design. The relational model and relational data definition and data manipulation languages. Design of relational databases and normalization theory. Physical database design. Concurrency and recovery. Query processing and optimization.
CSCI-GA.2440-001
(1163) Software Engineering Jean-Claude Franchitti
Office Hours R 5:10-7:00PM CIWW 101
This is a capstone course focusing on large-scale software development. This course presents modern software engineering techniques and examines the software life cycle, including software specification, design, implementation, testing, and maintenance. Object-oriented design methods are also considered. Software engineering projects involve creation of a large-scale software system and require some or all of the following elements: formation of a small team, project proposal, literature review, interim report, project presentation, and final report.

Prerequisites: CSCI-GA 1170, CSCI-GA 2110, and CSCI-GA 2250
CSCI-GA.2520-001
BIOL-GA 1127-001
(1164) Bioinformatics and Genomes Richard Bonneau
Office Hours F 1:00-3:45PM CIWW 102
The recent explosion in the availability of genome-wide data such as whole genome sequences and microarray data led to a vast increase in bioinformatics research and tool development. Bioinformatics is becoming a cornerstone for modern biology, especially in fields such as genomics. It is thus crucial to understand the basic ideas and to learn fundamental bioinformatics techniques. The emphasis of this course is on developing not only an understanding of existing tools but also the programming and statistics skills that allow students to solve new problems in a creative way.
CSCI-GA.2566-001
(1165) Foundations Of Machine Learning Mehryar Mohri
Office Hours M 5:10-7:00PM CIWW 109

This course introduces the fundamental concepts and methods of machine learning, including the description and analysis of several modern algorithms, their theoretical basis, and the illustration of their applications. Many of the algorithms described have been successfully used in text and speech processing, bioinformatics, and other areas in real-world products and services. The main topics covered are probability and general bounds; PAC model; VC dimension; perceptron, Winnow; support vector machines (SVMs); kernel methods; decision trees; boosting; regression problems and algorithms; ranking problems and algorithms; halving algorithm, weighted majority algorithm, mistake bounds; learning automata, Angluin-type algorithms; and reinforcement learning, Markov decision processes (MDPs).

Prerequisites: CSCI-GA 1180.
CSCI-GA.2567-001
DS-GA 1003-001
(20925) Machine Learning and Computational Statistics David Sontag
Office Hours T 5:10-7:00PM CIWW 109

The course covers a wide variety of topics in machine learning, pattern recognition, statistical modeling, and neural computation. It covers the mathematical methods and theoretical aspects, but primarily focuses on algorithmic and practical issues.

Cross-listing for DS-GA 1003.

Prerequisites: DS-GA-1001: Intro to Data Science or its equivalent, DS-GA-1002: Statistical and Mathematical Methods or its equivalent. Solid mathematical background, equivalent to a 1-semester undergraduate course in each of the following: linear algebra, multivariate calculus (primarily differential calculus), probability theory, and statistics. (The coverage in DS-GA 1002 is sufficient.) Python programming required for most homework assignments. Recommended: Computer science background up to a "data structures and algorithms" course. Recommended: At least one advanced, proof-based mathematics course
CSCI-GA.2567-002
DS-GA 1003-002
(20926) Machine Learning and Computational Statistics Lab Yonatan Halpern R 8:10-9:40PM CIWW 109

The course covers a wide variety of topics in machine learning, pattern recognition, statistical modeling, and neural computation. It covers the mathematical methods and theoretical aspects, but primarily focuses on algorithmic and practical issues.

Cross-listing for DS-GA 1003.

Prerequisites: DS-GA-1001: Intro to Data Science or its equivalent, DS-GA-1002: Statistical and Mathematical Methods or its equivalent. Solid mathematical background, equivalent to a 1-semester undergraduate course in each of the following: linear algebra, multivariate calculus (primarily differential calculus), probability theory, and statistics. (The coverage in DS-GA 1002 is sufficient.) Python programming required for most homework assignments. Recommended: Computer science background up to a "data structures and algorithms" course. Recommended: At least one advanced, proof-based mathematics course
CSCI-GA.2568-001
DS-GA 1004-001
(20927) Big Data Juliana Freire
Office Hours M 7:10-9:00PM CANTR 101

This course covers methods and tools for automatic knowledge extraction from very large datasets. Methods include on-line learning, feature hashing, class embedding, distributed databases, map-reduce framework, and applications.

Cross-listing for DS-GA 1004.

Prerequisites: DS-GA-1001 or equivalent undergraduate course, DS-GA-1002.
CSCI-GA.2568-002
DS-GA 1004-002
(20928) Big Data Lab Nandita Chugh R 7:10-8:00PM CIWW 109

This course covers methods and tools for automatic knowledge extraction from very large datasets. Methods include on-line learning, feature hashing, class embedding, distributed databases, map-reduce framework, and applications.

Cross-listing for DS-GA 1004.

Prerequisites: DS-GA-1001 or equivalent undergraduate course, DS-GA-1002.
CSCI-GA.2572-001
DS-GA.1008-001
(21331) Deep Learning Yann LeCun
Office Hours M 5:10-7:00PM CANTR 101

This course concerns the latest techniques in deep learning and representation learning, focusing on supervised and unsupervised deep learning, embedding methods, metric learning, convolutional net and recurrent nets, with applications to computer vision, natural language understanding, and speech recognition.

Prerequisites: DS-GA 1001 Intro to Data Science or a graduate-level machine learning course.
CSCI-GA.2572-002
DS-GA.1008-002
(21332) Deep Learning Lab TBA W 5:10-6:00PM CIWW 109

This course concerns the latest techniques in deep learning and representation learning, focusing on supervised and unsupervised deep learning, embedding methods, metric learning, convolutional net and recurrent nets, with applications to computer vision, natural language understanding, and speech recognition.

Prerequisites: DS-GA 1001 Intro to Data Science or a graduate-level machine learning course.
CSCI-GA.2580-001
(2021) Web Search Engines CANCELLED -

Discusses the design of general and specialized Web search engines and the extraction of information from the results of Web search engines. Topics include Web crawlers, database design, query language, relevance ranking, document similarity and clustering, the “invisible” Web, specialized search engines, evaluation, natural language processing, data mining applied to the Web, and multimedia retrieval.

Prerequisites: Recommend CSCI-GA 1180.
CSCI-GA.2590-001
(1864) Natural Language Processing Ralph Grishman
Office Hours T 5:10-7:00PM CIWW 202

Natural Language Processing applies computational and linguistic knowledge to the processing of natural languages (English, Chinese, Spanish, Japanese). Applications include: machine translation, information extraction, information retrieval, and others. On the one hand, the class will include the modeling and representation of linguistic phenomena. On the other, It will cover methods for applying this knowledge using both manual rules and machine learning. Sample topics include: formal languages, hmm, part of speech tagging, vector-based methods, shallow and full parsing, semantic role labeling, information extraction and machine translation. Students will complete shared tasks (POS-tagging, Information Extraction, etc.) and group final projects. There will also be a midterm exam and several small written assignments.

Prerequisites: Some facility with Java and Python and a knowledge of the elements of probability and statistics is expected.

Prerequisites: Some facility with Java and Python and a knowledge of the elements of probability and statistics is expected.
CSCI-GA.2620-001
(2022) Networks and Distributed Systems Lakshminarayanan Subramanian
Office Hours W 7:10-9:00PM CIWW 312

This is a capstone course. A course in computer networks and large-scale distributed systems. Teaches the design and implementation techniques essential for engineering both robust networks and Internet-scale distributed systems. The goal is to guide students so they can initiate and critique research ideas in networks and distributed systems and implement and evaluate a working system that can handle a real-world workload. Topics include routing protocols, network congestion control, wireless networking, peer-to-peer systems, overlay networks and applications, distributed storage systems, and network security.

Prerequisites: CSCI-GA 1170, CSCI-GA 2110, and CSCI-GA 2250.
CSCI-GA.2715-001
NEURL-GA 3402-005
(21425) Representation and Visual Analysis Eero Simoncelli TR 10:00-11:50AM Meyr 851

Advanced seminars led by the faculty to provide in-depth consideration of specific topic areas in neural science. Examples of recent topics: Neurobiology of Learning and Memory, A New View of Visual Cortex, Classic Papers in Auditory Neuroscience, Auditory and Visual Cortex, Neuroimaging, Neuronal Mechanisms of Color Vision, Neural Adaptation, Nonlinear Dynamics and Neural Modeling, Neuronal Networks.

Cross-listing for NEURL-GA 3042.

Prerequisites: TBA
CSCI-GA.2945-001
MATH-GA.2012-001
(1166) Advanced Topics in Numerical Analysis: Finite Element Methods Olof Widlund W 1:25-3:15PM CIWW 312
Topics vary each semester.

Prerequisites: Topics determine prerequisites.
CSCI-GA.2945-002
MATH-GA.2012-002
(1167) Advanced Topics in Numerical Analysis: Fast Algorithms Leslie Greengard T 1:25-3:15PM CIWW 312
Topics vary each semester.

Prerequisites: Topics determine prerequisites.
CSCI-GA.2945-003
MATH-GA.2012-003
(14573) Advanced Topics in Numerical Analysis: Course Grained Models of Materials CANCELLED -
Topics vary each semester.

Prerequisites: Topics determine prerequisites.
CSCI-GA.3033-001
(1168) Special Topics: Financial Computing Eran Fishler W 7:10-9:00PM CIWW 109

This course introduces students to the basic concepts of computational finance and explores various relations between computer science and finance. In particular, the course will introduce both theoretical and practical aspects of finance with an emphasis on the relation between real-life applications and these concepts. The course will cover various issues such as high-frequency market simulators and frameworks for performing statistical simulations. Various financial instruments will also be discussed and modeled. Emphasis will be put on efficiency and proper design. Object-oriented concepts will be discussed and put to use in real life applications.

Prerequisites: Fundamental Algorithms, Programming Languages, background in calculus and linear algebra.
CSCI-GA.3033-003
(14585) Special Topics: Algorithmic & Economic Aspects of the Internet Vahab Mirrokni
Richard Cole R 5:10-7:00PM CIWW 202

Description: In this course, we study algorithmic and economic problems related to the Internet search, online advertisement, social networks, and online markets. We discuss important economic aspects: the ideas behind Internet ad auctions, and the game theoretic analysis of self-interested agents interacting over the Internet. We also cover the central algorithmic ideas behind the large-scale analysis of the huge data sets supporting Internet search.

Our goal is to obtain a rigorous understanding of the properties of such environments and explore these properties to solve data mining and optimization problems emerging in these environments. The main areas include computational economics, computational advertising, (social) network analysis, commerce applications, and large-scale distributed computation.

Prerequisites: Fundamental Algorithms, Mathematical Techniques for CS Applications or permission of the instructor. Also, some knowledge of basic linear algebra and probability will be assumed
CSCI-GA.3033-004
(1170) Special Topics: Social Networks Bhubaneswar Mishra
Office Hours T 5:10-7:00PM CIWW 317

Social Networks is a specific example of many forms of networks that have become ubiquitous in our modern society. The World Wide Web enables information flows among vast number of humans; facebook, orkut, friendster, diaspora, etc. connect small groups of friends; amazon, ebay, etc. provide opportunities for trading, etc. These networks determine our information, influence our opinions, and shape our political attitudes. They also link us, often through important but weak ties, to other humans

Their origin is biological: going back to quorum-sensing, swarming, flocking, social grooming, gossip, etc. Yet, as we have connected our social networks to traditional human institutions (markets, justice systems, education, etc.) through new technologies, the underlying biology has become obscured, but not dormant. Economic markets also look much more like networks than anonymous marketplaces. Firms interact with the suppliers and customers in a Web-like supply chains. Systemic risk in financial markets often results from the counterparty risks created within this financial network.

This course will introduce the tools for the study of networks. It will show how certain common principles permeate the functioning of these diverse networks: e.g., issues related to robustness, fragility, and interlinkages etc.
CSCI-GA.3033-005
(1171) Special Topics: Production Quality Software Michael Schidlowsky
Office Hours W 5:10-7:00PM CIWW 512

In this course, students learn to develop production quality software. Lectures present real-world development practices that maximize software correctness and minimize development time. A special emphasis is placed on increasing proficiency in a particular programming language by doing weekly development projects and participating in code reviews.

Assignments become more sophisticated as the semester progresses, eventually incorporating unit tests, build scripts, design patterns, and other techniques. The course culminates with an assignment that requires students to contribute to an open-source project of their choice.
CSCI-GA.3033-007
(1173) Special Topics: Social Multiplayer Games Yoav Zibin
Office Hours T 5:10-7:00PM CIWW 102

The course will teach how to develop online casual multiplayer games using open technologies such as GWT, Closure, AppEngine, DHTML, JSON, AJAX, long-polling, HTML5, XMPP, OAuth2, PhoneGap, etc. The course has two big projects: An individual project where you develop a turn-based multiplayer game (with mobile and desktop graphics, artificial-intelligence, save and load, etc), and a small group project. The course will also teach about ranking systems, artificial intelligence for games, real-time and turn-based games. The course will not concern with 3D graphics.

Prerequisites: Java.
CSCI-GA.3033-008
(1868) Special Topics: Realtime & Big Data Analytics Suzanne McIntosh
Office Hours R 7:10-9:00PM CIWW 101

This course will introduce technologies at the foundation of the Big Data movement that have facilitated scalable management of vast quantities of data collected through realtime and near realtime sensing. We will also explore the tools enabling the acquisition of near realtime data in the social domain, the fusion of those data when in flight and at rest, and their meaningful representation in graphical visualizations. Students are required to complete weekly reading and/or programming assignments and demonstrate mastery of course topics by developing and demonstrating a software project of their choosing. Class time will be set aside for project proposal and final demo.

Prerequisites: CSCI-GA 2250 or equivalent Operating Systems course; programming experience in C/C++ or Java for assignments and final project; CSCI-GA 2262, CSCI-GA 2620, or undergraduate course in networks. A familiarity with databases will be useful.
CSCI-GA.3033-009
(1929) Special Topics: Cloud Computing Jean-Claude Franchitti
Office Hours M 7:10-9:00PM CIWW 102

This course provides a hands-on comprehensive study of Cloud concepts and capabilities across the various Cloud service models including Infrastructure as a Service (IaaS), Platform as a Service (PaaS), Software as a Service (SaaS), and Business Process as a Service (BPaaS). IaaS topics start with a detailed study the evolution of infrastructure migration approaches from VMWare/Xen/KVM virtualization, to adaptive virtualization, and Cloud Computing / on-demand resources provisioning.

Mainstream Cloud infrastructure services and related vendor solutions are also covered in detail. PaaS topics cover a broad range of Cloud vendor platforms including AWS, Google App Engine, Microsoft Azure, Eucalyptus, OpenStack and others as well as a detailed study of related platform services such as storage services that leverage Google Storage, Amazon S3, Amazon Dynamo, or other services meant to provide Cloud resources management and monitoring capabilities.

The SaaS and PaaS topics covered in the course will familiarize students with the use of vendor-maintained applications and processes available on the Cloud on a metered on-demand basis in multi-tenant environments. The course also covers the Cloud security model and associated challenges and delves into the implementation and support of High Performance Computing and Big Data support capabilities on the Cloud.

Through hands-on assignments and projects, students will learn how to configure and program IaaS services. They will also learn how to develop Cloud-based software applications on top of various Cloud platforms, how to integrate application-level services built on heterogeneous Cloud platforms, and how to leverage SaaS and BPaaS solutions to build comprehensive end-to-end business solutions on the Cloud.
CSCI-GA.3033-010
(14586) Special Topics: Experiments in Motion Capture *** Christoph Bregler W 5:10-7:00PM 719BWY 1221

Topics vary each semester.

Prerequisites: Prerequisites vary according to topic.
CSCI-GA.3033-014
(14587) Special Topics: Programming Paradigms for Concurrency Thomas Wies
Office Hours M 5:10-7:00PM CIWW 317

The spread of multicore architectures has a pervasive effect on how we develop software. In this course, we focus on programming techniques for modern multicore machines. We will explore how to write programs using major paradigms for managing concurrency and how to reason about the correctness and performance of such programs.

opics include multiprocessor architecture, mutual exclusion, wait-free and lock-free synchronization, load balancing, concurrent data structures, transactional memories, and message passing. The course will involve extensive programming exercises in Java and related languages.

Prerequisites: CSCI-GA 2110 Programming Languages
CSCI-GA.3033-015
(19107) Special Topics: Virtual Machines: Concepts and Applications Mohamed Zahran
Office Hours W 5:10-7:00PM CIWW 312

Virtualization technology from VMware, IBM, Xen, Microsoft, and others is an indication of the importance of this technology, especially in this era where almost everything is in the cloud. Virtualization became the IT world's hottest trend in recent years. Have you ever wondered how you can run multiple operating systems on a single physical system and share the underlying hardware resources? How does your operating system see a hardware that differs from the actual hardware, and why we need to do so? What is a virtual server? Virtual machine is the answer to all that and much more.

In this course we will study the design and implementation of virtual machines, virtual machine monitors (aka hypervisors), as well other recent trends in virtualization. We will study virtual machines across the disciplines that use them: operating systems, programming languages, and computer architecture.

Prerequisites: CSCI-GA.2250 Operating Systems
CSCI-GA.3110-001
(14590) Honors Programming Languages Patrick Cousot
Office Hours TR 3:30-4:45PM CIWW 312
The course will introduce a panorama of programming languages concepts underlying the main programming language paradigms (such as imperative, functional, object-oriented, logic, concurrent, and scripting languages) and present in detail the formal methods (code semantics, specification, and verification) used in modern high quality assurance tools for software safety and security. A programming project (design and implementation of an interpreter/compiler for an dynamic object-oriented mini-language) will be programmed in OCaml, a multiparadigm language introduced at the beginning of the course.

Prerequisites: Permission of the instructor for master’s students
CSCI-GA.3205-001
(2023) Applied Cryptography & Network Security Zvi Kedem
Office Hours M 5:10-7:00PM CIWW 101
This course first introduces the fundamental mathematical cryptographic algorithms, focusing on those that are used in current systems. To the extent feasible, the mathematical properties of the cryptographic algorithms are justified, using elementary mathematical tools. Second, actual security mechanisms and protocols, mainly those employed for network traffic that rely on the previously introduced cryptographic algorithms, are presented. The topics covered include introduction to basic number-theoretical properties, public/private and symmetric key systems, secure hash functions, digital signature standards, digital certificates, IP security, e-mail security, Web security, and stand-alone computer privacy and security tools.
CSCI-GA.3220-001
(14591) Advanced Cryptography Yevgeniy Dodis
Office Hours W 5:10-7:00PM CIWW 201
Basics of computational number theory for cryptography. Identification protocols. Digital signatures. Public-key encryption. Additional selected topics.

Prerequisites: CSCI-GA 3210.
CSCI-GA.3350-001
(14592) Theory Of Comp Honors Subhash Khot
Office Hours MW 3:30-4:45PM CIWW 312

TBA

Prerequisites: TBA
CSCI-GA.3700-001
MCC-GE 2295-001
(14593) Values Embodied in Information and Communication Technologies (4 credits) Helen Nissenbaum R 2:00-4:10PM EAST 207

Studies social, political & ethical values embodied in computer & information systems, & new media. Students examine work in the philosophy & social study of technology to understand the rich & sometimes troubling relationship between values & technical design. Course will ask: Is technology neutral? Who should make key decisions? What is the role of scientists & engineers? The course examines specific cases, such as, the Internet, search engines, web- cookies, & data mining from philosophical, empirical, & technical perspectives.

Cross-listing for MCC-GE 2295.

Prerequisites: TBA
CSCI-GA.3812-001
(1174) Information Technology Projects * Evan Korth
Office Hours W 6:00-9:00PM CIWW 317

This is a capstone course that connects students directly with real-world information technology problems. The goal of this course is to teach the skills needed for success in real-world information technology via a combination of classroom lectures and practical experience with large projects that have been specified by local “clients.” The typical clients are primarily companies, but can also be government agencies or nonprofit organizations. Each project lasts for the entire semester and is designed to involve the full software project life cycle. Examples of such projects are development of software to solve a business problem, including specifying requirements, writing and testing prototype code, and writing a final report; and evaluation of commercial software to be purchased to address a business problem, including gathering requirements, designing an architecture to connect the new software with existing systems, and assessing the suitability of available software products.

Prerequisites: For MS in IS students: Successful completion of CSCI-GA 1170 Fundamental Algorithms and two of the following three courses: CSCI-GA 2262 Data Communications & Networks; CSCI-GA 2250 Operating Systems; CSCI-GA 2433 Database Systems. For MS in CS students: Successful completion of CSCI-GA 1170 Fundamental Algorithms, CSCI-GA 2110 Programming Languages, and CSCI-GA 2250 Operating Systems. PERMISSION OF THE DEPARTMENT REQUIRED.
CSCI-GA.3813-001
(1175) Adv Lab MS * Faculty -

Large-scale programming project or research in cooperation with a faculty member.

Prerequisites: Permission of the faculty project supervisor and the Director of Graduate Studies.
CSCI-GA.3813-002
(1176) Adv Lab MS * Faculty -

Large-scale programming project or research in cooperation with a faculty member.

Prerequisites: Permission of the faculty project supervisor and the Director of Graduate Studies.
CSCI-GA.3813-003
(1177) Adv Lab MS * Faculty -

Large-scale programming project or research in cooperation with a faculty member.

Prerequisites: Permission of the faculty project supervisor and the Director of Graduate Studies.
CSCI-GA.3813-004
(1178) Adv Lab MS * Faculty -

Large-scale programming project or research in cooperation with a faculty member.

Prerequisites: Permission of the faculty project supervisor and the Director of Graduate Studies.
CSCI-GA.3813-005
(1179) Adv Lab PhD ** Faculty -

Large-scale programming project or research in cooperation with a faculty member.

Prerequisites: Permission of the faculty project supervisor and the Director of Graduate Studies.
CSCI-GA.3813-006
(1180) Adv Lab PhD ** Faculty -

Large-scale programming project or research in cooperation with a faculty member.

Prerequisites: Permission of the faculty project supervisor and the Director of Graduate Studies.
CSCI-GA.3813-007
(1181) Adv Lab PhD ** Faculty -

Large-scale programming project or research in cooperation with a faculty member.

Prerequisites: Permission of the faculty project supervisor and the Director of Graduate Studies.
CSCI-GA.3813-008
(1182) Adv Lab PhD ** Faculty -

Large-scale programming project or research in cooperation with a faculty member.

Prerequisites: Permission of the faculty project supervisor and the Director of Graduate Studies.
CSCI-GA.3840-001
(1183) Master's Thesis Research * Faculty -

Prerequisites: Approval of a faculty adviser and the Director of Graduate Studies for the M.S. programs.
CSCI-GA.3850-001
(1184) PhD Seminar: Cryptography ** Yevgeniy Dodis
Office Hours T 12:30-3:15PM CIWW 412
Graduate seminars serve as loosely structured forums for exploring research topics from broad areas of computer science. They are designed to foster dialogue by bringing together faculty and students from a given area and to encourage the exchange of ideas. As such, they bridge the gap between more structured course offerings and informal research meetings. Subject matter varies by section.

Prerequisites: Permission of the instructor.
CSCI-GA.3850-004
(1185) PhD Seminar: Formal Methods ** Thomas Wies
Office Hours R 11:00-12:30PM CIWW 412
Graduate seminars serve as loosely structured forums for exploring research topics from broad areas of computer science. They are designed to foster dialogue by bringing together faculty and students from a given area and to encourage the exchange of ideas. As such, they bridge the gap between more structured course offerings and informal research meetings. Subject matter varies by section.

Prerequisites: Permission of the instructor.
CSCI-GA.3850-006
(1869) PhD Seminar: Machine Learning ** Mehryar Mohri
Office Hours T 3:45-5:00PM CIWW 317
Graduate seminars serve as loosely structured forums for exploring research topics from broad areas of computer science. They are designed to foster dialogue by bringing together faculty and students from a given area and to encourage the exchange of ideas. As such, they bridge the gap between more structured course offerings and informal research meetings. Subject matter varies by section.

Prerequisites: Permission of the instructor.
CSCI-GA.3860-001
(1186) PhDThesis Research ** Faculty -

Prerequisites: Permission of the thesis adviser or director of graduate studies for the Ph.D. program.
CORE-UA.0109-001 Quantitative Reasoning: Mathematics and Computing CANCELLED -

This course teaches key mathematical concepts using the new Python programming language. The first part of the course teaches students how to use the basic features of Python: operations with numbers and strings, variables, Boolean logic, control structures, loops and functions. The second part of the course focuses on the phenomena of growth and decay: geometric progressions, compound interest, exponentials and logarithms. The third part of the course introduces three key mathematical concepts: trigonometry, counting problems and probability. Students use Python to explore the mathematical concepts in labs and homework assignments. No prior knowledge of programming is required.

Prerequisites: Permission of the department.
CORE-UA.0109-002 Quantitative Reasoning: Mathematics and Computing CANCELLED -

This course teaches key mathematical concepts using the new Python programming language. The first part of the course teaches students how to use the basic features of Python: operations with numbers and strings, variables, Boolean logic, control structures, loops and functions. The second part of the course focuses on the phenomena of growth and decay: geometric progressions, compound interest, exponentials and logarithms. The third part of the course introduces three key mathematical concepts: trigonometry, counting problems and probability. Students use Python to explore the mathematical concepts in labs and homework assignments. No prior knowledge of programming is required.

Prerequisites: Permission of the department.
CSCI-UA.0002-001
(5866) Intro To Computer Programming Michael Kadri MW 2:00-3:15PM CIWW 102

An introduction to the fundamentals of computer programming, which is the foundation of computer science. Students design, write, and debug computer programs. No knowledge of programming is assumed.

Prerequisites: Three years of high school mathematics or equivalent. No prior computing experience is assumed. Students with any programming experience should consult with the department before registering. Students with any reported score on the Computer Science AP examination cannot enroll in this course; Albert will block them from registering for it. Students who have taken or are taking Introduction to Computer Science (CSCI-UA 101) will not receive credit for this course. Does not count toward the computer science major; serves as the prerequisite for students with no previous programming experience who want to continue into CSCI-UA 101 and pursue the major. Students may not receive credit for both CSCI-UA 2 and CSCI-UA 3.
CSCI-UA.0002-002
(5867) Intro To Computer Programming Jerry Waxman
Office Hours TR 3:30-4:45PM CIWW 101

An introduction to the fundamentals of computer programming, which is the foundation of computer science. Students design, write, and debug computer programs. No knowledge of programming is assumed.

Prerequisites: Three years of high school mathematics or equivalent. No prior computing experience is assumed. Students with any programming experience should consult with the department before registering. Students with any reported score on the Computer Science AP examination cannot enroll in this course; Albert will block them from registering for it. Students who have taken or are taking Introduction to Computer Science (CSCI-UA 101) will not receive credit for this course. Does not count toward the computer science major; serves as the prerequisite for students with no previous programming experience who want to continue into CSCI-UA 101 and pursue the major. Students may not receive credit for both CSCI-UA 2 and CSCI-UA 3.
CSCI-UA.0002-003
(5868) Intro To Computer Programming David Dakota Blair TR 11:00-12:15PM CIWW 102

An introduction to the fundamentals of computer programming, which is the foundation of computer science. Students design, write, and debug computer programs. No knowledge of programming is assumed.

Prerequisites: Three years of high school mathematics or equivalent. No prior computing experience is assumed. Students with any programming experience should consult with the department before registering. Students with any reported score on the Computer Science AP examination cannot enroll in this course; Albert will block them from registering for it. Students who have taken or are taking Introduction to Computer Science (CSCI-UA 101) will not receive credit for this course. Does not count toward the computer science major; serves as the prerequisite for students with no previous programming experience who want to continue into CSCI-UA 101 and pursue the major. Students may not receive credit for both CSCI-UA 2 and CSCI-UA 3.
CSCI-UA.0002-004
(5869) Intro To Computer Programming Syed Salahuddin
Office Hours MW 9:30-10:45AM CIWW 102

An introduction to the fundamentals of computer programming, which is the foundation of computer science. Students design, write, and debug computer programs. No knowledge of programming is assumed.

Prerequisites: Three years of high school mathematics or equivalent. No prior computing experience is assumed. Students with any programming experience should consult with the department before registering. Students with any reported score on the Computer Science AP examination cannot enroll in this course; Albert will block them from registering for it. Students who have taken or are taking Introduction to Computer Science (CSCI-UA 101) will not receive credit for this course. Does not count toward the computer science major; serves as the prerequisite for students with no previous programming experience who want to continue into CSCI-UA 101 and pursue the major. Students may not receive credit for both CSCI-UA 2 and CSCI-UA 3.
CSCI-UA.0002-005
(5870) Intro To Computer Programming Craig Kapp
Office Hours MW 11:00-12:15PM CIWW 102

An introduction to the fundamentals of computer programming, which is the foundation of computer science. Students design, write, and debug computer programs. No knowledge of programming is assumed.

Prerequisites: Three years of high school mathematics or equivalent. No prior computing experience is assumed. Students with any programming experience should consult with the department before registering. Students with any reported score on the Computer Science AP examination cannot enroll in this course; Albert will block them from registering for it. Students who have taken or are taking Introduction to Computer Science (CSCI-UA 101) will not receive credit for this course. Does not count toward the computer science major; serves as the prerequisite for students with no previous programming experience who want to continue into CSCI-UA 101 and pursue the major. Students may not receive credit for both CSCI-UA 2 and CSCI-UA 3.
CSCI-UA.0002-006
(5871) Intro To Computer Programming Joseph Versoza
Office Hours MW 3:30-4:45PM CIWW 517

An introduction to the fundamentals of computer programming, which is the foundation of computer science. Students design, write, and debug computer programs. No knowledge of programming is assumed.

Prerequisites: Three years of high school mathematics or equivalent. No prior computing experience is assumed. Students with any programming experience should consult with the department before registering. Students with any reported score on the Computer Science AP examination cannot enroll in this course; Albert will block them from registering for it. Students who have taken or are taking Introduction to Computer Science (CSCI-UA 101) will not receive credit for this course. Does not count toward the computer science major; serves as the prerequisite for students with no previous programming experience who want to continue into CSCI-UA 101 and pursue the major. Students may not receive credit for both CSCI-UA 2 and CSCI-UA 3.
CSCI-UA.0002-007
(5872) Intro To Computer Programming Amos Bloomberg
Office Hours TR 9:30-10:45AM CIWW 109

An introduction to the fundamentals of computer programming, which is the foundation of computer science. Students design, write, and debug computer programs. No knowledge of programming is assumed.

Prerequisites: Three years of high school mathematics or equivalent. No prior computing experience is assumed. Students with any programming experience should consult with the department before registering. Students with any reported score on the Computer Science AP examination cannot enroll in this course; Albert will block them from registering for it. Students who have taken or are taking Introduction to Computer Science (CSCI-UA 101) will not receive credit for this course. Does not count toward the computer science major; serves as the prerequisite for students with no previous programming experience who want to continue into CSCI-UA 101 and pursue the major. Students may not receive credit for both CSCI-UA 2 and CSCI-UA 3.
CSCI-UA.0002-008
(7987) Intro To Computer Programming Edith Schonberg TR 2:00-3:15PM CIWW 317

An introduction to the fundamentals of computer programming, which is the foundation of computer science. Students design, write, and debug computer programs. No knowledge of programming is assumed.

Prerequisites: Three years of high school mathematics or equivalent. No prior computing experience is assumed. Students with any programming experience should consult with the department before registering. Students with any reported score on the Computer Science AP examination cannot enroll in this course; Albert will block them from registering for it. Students who have taken or are taking Introduction to Computer Science (CSCI-UA 101) will not receive credit for this course. Does not count toward the computer science major; serves as the prerequisite for students with no previous programming experience who want to continue into CSCI-UA 101 and pursue the major. Students may not receive credit for both CSCI-UA 2 and CSCI-UA 3.
CSCI-UA.0002-009
(14588) Intro To Computer Programming Syed Salahuddin
Office Hours MW 12:30-1:45PM CIWW 101

An introduction to the fundamentals of computer programming, which is the foundation of computer science. Students design, write, and debug computer programs. No knowledge of programming is assumed.

Prerequisites: Three years of high school mathematics or equivalent. No prior computing experience is assumed. Students with any programming experience should consult with the department before registering. Students with any reported score on the Computer Science AP examination cannot enroll in this course; Albert will block them from registering for it. Students who have taken or are taking Introduction to Computer Science (CSCI-UA 101) will not receive credit for this course. Does not count toward the computer science major; serves as the prerequisite for students with no previous programming experience who want to continue into CSCI-UA 101 and pursue the major. Students may not receive credit for both CSCI-UA 2 and CSCI-UA 3.
CSCI-UA.0002-010
(20570) Intro To Computer Programming Phoenix Perry MW 8:00-9:15AM CIWW 102

An introduction to the fundamentals of computer programming, which is the foundation of computer science. Students design, write, and debug computer programs. No knowledge of programming is assumed.

Prerequisites: Three years of high school mathematics or equivalent. No prior computing experience is assumed. Students with any programming experience should consult with the department before registering. Students with any reported score on the Computer Science AP examination cannot enroll in this course; Albert will block them from registering for it. Students who have taken or are taking Introduction to Computer Science (CSCI-UA 101) will not receive credit for this course. Does not count toward the computer science major; serves as the prerequisite for students with no previous programming experience who want to continue into CSCI-UA 101 and pursue the major. Students may not receive credit for both CSCI-UA 2 and CSCI-UA 3.
CSCI-UA.0004-001
(5873) Intro to Web Design & Computer Principles Nathan Hull
Office Hours MW 12:30-1:45PM CIWW 102
Introduces students to both the practice of web design and the basic principles of computer science. The practice component covers not only web design but also current graphics and software tools. The principles section includes an overview of hardware and software, the history of computers, and a discussion of the impact of computers and the Internet.

Prerequisites: Three years of high school mathematics or equivalent. No prior computing experience is assumed. Students with computing experience should consult with the department before registering.
CSCI-UA.0004-002
(5874) Intro to Web Design & Computer Principles Nathan Hull
Office Hours TR 2:00-3:15PM CIWW 102
Introduces students to both the practice of web design and the basic principles of computer science. The practice component covers not only web design but also current graphics and software tools. The principles section includes an overview of hardware and software, the history of computers, and a discussion of the impact of computers and the Internet.

Prerequisites: Three years of high school mathematics or equivalent. No prior computing experience is assumed. Students with computing experience should consult with the department before registering.
CSCI-UA.0004-003
(5875) Intro to Web Design & Computer Principles Craig Kapp
Office Hours TR 9:30-10:45AM CIWW 201
Introduces students to both the practice of web design and the basic principles of computer science. The practice component covers not only web design but also current graphics and software tools. The principles section includes an overview of hardware and software, the history of computers, and a discussion of the impact of computers and the Internet.

Prerequisites: Three years of high school mathematics or equivalent. No prior computing experience is assumed. Students with computing experience should consult with the department before registering.
CSCI-UA.0004-004
(5876) Intro to Web Design & Computer Principles Joshua Clayton
Office Hours MW 9:30-10:45AM CIWW 201
Introduces students to both the practice of web design and the basic principles of computer science. The practice component covers not only web design but also current graphics and software tools. The principles section includes an overview of hardware and software, the history of computers, and a discussion of the impact of computers and the Internet.

Prerequisites: Three years of high school mathematics or equivalent. No prior computing experience is assumed. Students with computing experience should consult with the department before registering.
CSCI-UA.0004-005
(7659) Intro to Web Design & Computer Principles Joshua Clayton
Office Hours TR 11:00-12:15PM CIWW 512
Introduces students to both the practice of web design and the basic principles of computer science. The practice component covers not only web design but also current graphics and software tools. The principles section includes an overview of hardware and software, the history of computers, and a discussion of the impact of computers and the Internet.

Prerequisites: Three years of high school mathematics or equivalent. No prior computing experience is assumed. Students with computing experience should consult with the department before registering.
CSCI-UA.0004-006
(7988) Intro to Web Design & Computer Principles Alvaro Olsen
Office Hours MW 11:00-12:15PM CIWW 202
Introduces students to both the practice of web design and the basic principles of computer science. The practice component covers not only web design but also current graphics and software tools. The principles section includes an overview of hardware and software, the history of computers, and a discussion of the impact of computers and the Internet.

Prerequisites: Three years of high school mathematics or equivalent. No prior computing experience is assumed. Students with computing experience should consult with the department before registering.
CSCI-UA.0004-007
(14610) Intro to Web Design & Computer Principles Adam Scher
Office Hours TR 8:00-9:15AM CIWW 101
Introduces students to both the practice of web design and the basic principles of computer science. The practice component covers not only web design but also current graphics and software tools. The principles section includes an overview of hardware and software, the history of computers, and a discussion of the impact of computers and the Internet.

Prerequisites: Three years of high school mathematics or equivalent. No prior computing experience is assumed. Students with computing experience should consult with the department before registering.
CSCI-UA.0060-001
(5877) Database Design And Web Implementation Deena Engel TR 11:00-12:15PM CIWW 317

Introduces principles and applications of database design and working with data. Students use Python as they prepare, analyze, and work with data and use SQL to study the principles and implementations of relational databases. Also covers other database paradigms, such as NoSQL. Students apply these principles to computer systems and their respective fields of interest.

Prerequisites: Introduction to Computer Programming (No Prior Experience) (CSCI-UA 2) or Introduction to Computer Programming (Limited Prior Experience) (CSCI-UA 3). Students that have successfully completed Data Management and Analysis (CSCI-UA 479) are NOT eligible to take this course.
CSCI-UA.0061-001
(7640) Web Development And Programming Deena Engel MW 12:30-1:45PM CIWW 317

Provides a practical approach to web technologies and programming. Students build interactive, secure, and powerful web programs. Covers client and server side technologies for the web.

Prerequisites: Introduction to Computer Programming (No Prior Experience) (CSCI-UA 2) or Introduction to Computer Programming (Limited Prior Experience) (CSCI-UA 3), and Introduction to Web Design and Computer Principles (CSCI-UA 4). Students that have successfully completed Applied Internet Technology (CSCI-UA 467) are NOT eligible to take this course.
CSCI-UA.0070-001 Computational Knowledge Management CANCELLED -

TBA

Prerequisites: TBA
CSCI-UA.0101-001
(5878) Intro To Computer Science Andrew Case TR 3:30-4:45PM CIWW 102

How to design algorithms to solve problems and how to translate these algorithms into working computer programs. Experience is acquired through projects in a high-level programming language. Intended primarily for computer science majors but also suitable for students of other scientific disciplines. Programming assignments.

Prerequisites: Introduction to Computer Programming (No Prior Experience) (CSCI-UA 2) or Introduction to Computer Programming (Limited Prior Experience) (CSCI-UA 3), or a score of 3 on the AP Computer Science exam (scores of 4 and 5 are acceptable prerequisites for students who wish to take CSCI-UA 101 before entering CSCI-UA 102; they will forfeit the AP credit), or departmental permission assessed by placement exam.
CSCI-UA.0101-002
(5879) Intro To Computer Science Andrew Case TR 3:30-4:45PM CIWW 102

How to design algorithms to solve problems and how to translate these algorithms into working computer programs. Experience is acquired through projects in a high-level programming language. Intended primarily for computer science majors but also suitable for students of other scientific disciplines. Programming assignments.

Prerequisites: Introduction to Computer Programming (No Prior Experience) (CSCI-UA 2) or Introduction to Computer Programming (Limited Prior Experience) (CSCI-UA 3), or a score of 3 on the AP Computer Science exam (scores of 4 and 5 are acceptable prerequisites for students who wish to take CSCI-UA 101 before entering CSCI-UA 102; they will forfeit the AP credit), or departmental permission assessed by placement exam.
CSCI-UA.0101-003
(5880) Intro To Computer Science Craig Kapp
Office Hours MW 3:30-4:45PM CIWW 102

How to design algorithms to solve problems and how to translate these algorithms into working computer programs. Experience is acquired through projects in a high-level programming language. Intended primarily for computer science majors but also suitable for students of other scientific disciplines. Programming assignments.

Prerequisites: Introduction to Computer Programming (No Prior Experience) (CSCI-UA 2) or Introduction to Computer Programming (Limited Prior Experience) (CSCI-UA 3), or a score of 3 on the AP Computer Science exam (scores of 4 and 5 are acceptable prerequisites for students who wish to take CSCI-UA 101 before entering CSCI-UA 102; they will forfeit the AP credit), or departmental permission assessed by placement exam.
CSCI-UA.0101-004
(5881) Intro To Computer Science Amos Bloomberg
Office Hours MW 2:00-3:15PM CIWW 109

How to design algorithms to solve problems and how to translate these algorithms into working computer programs. Experience is acquired through projects in a high-level programming language. Intended primarily for computer science majors but also suitable for students of other scientific disciplines. Programming assignments.

Prerequisites: Introduction to Computer Programming (No Prior Experience) (CSCI-UA 2) or Introduction to Computer Programming (Limited Prior Experience) (CSCI-UA 3), or a score of 3 on the AP Computer Science exam (scores of 4 and 5 are acceptable prerequisites for students who wish to take CSCI-UA 101 before entering CSCI-UA 102; they will forfeit the AP credit), or departmental permission assessed by placement exam.
CSCI-UA.0101-005
(7990) Intro To Computer Science Simina Fluture MW 11:00-12:15PM CIWW 101

How to design algorithms to solve problems and how to translate these algorithms into working computer programs. Experience is acquired through projects in a high-level programming language. Intended primarily for computer science majors but also suitable for students of other scientific disciplines. Programming assignments.

Prerequisites: Introduction to Computer Programming (No Prior Experience) (CSCI-UA 2) or Introduction to Computer Programming (Limited Prior Experience) (CSCI-UA 3), or a score of 3 on the AP Computer Science exam (scores of 4 and 5 are acceptable prerequisites for students who wish to take CSCI-UA 101 before entering CSCI-UA 102; they will forfeit the AP credit), or departmental permission assessed by placement exam.
CSCI-UA.0101-006
(7991) Intro To Computer Science Joanna Klukowska
Office Hours TR 9:30-10:45AM CIWW 102

How to design algorithms to solve problems and how to translate these algorithms into working computer programs. Experience is acquired through projects in a high-level programming language. Intended primarily for computer science majors but also suitable for students of other scientific disciplines. Programming assignments.

Prerequisites: Introduction to Computer Programming (No Prior Experience) (CSCI-UA 2) or Introduction to Computer Programming (Limited Prior Experience) (CSCI-UA 3), or a score of 3 on the AP Computer Science exam (scores of 4 and 5 are acceptable prerequisites for students who wish to take CSCI-UA 101 before entering CSCI-UA 102; they will forfeit the AP credit), or departmental permission assessed by placement exam.
CSCI-UA.0101-007
(20748) Intro To Computer Science Douglas Moody
Office Hours WF 8:00-9:15AM CIWW 101

How to design algorithms to solve problems and how to translate these algorithms into working computer programs. Experience is acquired through projects in a high-level programming language. Intended primarily for computer science majors but also suitable for students of other scientific disciplines. Programming assignments.

Prerequisites: Introduction to Computer Programming (No Prior Experience) (CSCI-UA 2) or Introduction to Computer Programming (Limited Prior Experience) (CSCI-UA 3), or a score of 3 on the AP Computer Science exam (scores of 4 and 5 are acceptable prerequisites for students who wish to take CSCI-UA 101 before entering CSCI-UA 102; they will forfeit the AP credit), or departmental permission assessed by placement exam.
CSCI-UA.0102-001
(5882) Data Structures Eric Koskinen MW 11:00-12:15PM CIWW 109

Use and design of data structures, which organize information in computer memory. Stacks, queues, linked lists, binary trees: how to implement them in a high-level language, how to analyze their effect on algorithm efficiency, and how to modify them. Programming assignments.

Prerequisites: Introduction to Computer Science (CSCI-UA 101), or a score of 4 or 5 on the AP Computer Science examination.
CSCI-UA.0102-002
(5883) Data Structures Eric Koskinen MW 11:00-12:15PM CIWW 109

Use and design of data structures, which organize information in computer memory. Stacks, queues, linked lists, binary trees: how to implement them in a high-level language, how to analyze their effect on algorithm efficiency, and how to modify them. Programming assignments.

Prerequisites: Introduction to Computer Science (CSCI-UA 101), or a score of 4 or 5 on the AP Computer Science examination.
CSCI-UA.0102-003
(5884) Data Structures - Recitation Sumit Gupta M 3:30-4:45PM CIWW 109

Use and design of data structures, which organize information in computer memory. Stacks, queues, linked lists, binary trees: how to implement them in a high-level language, how to analyze their effect on algorithm efficiency, and how to modify them. Programming assignments.

Prerequisites: Introduction to Computer Science (CSCI-UA 101), or a score of 4 or 5 on the AP Computer Science examination.
CSCI-UA.0102-004
(5885) Data Structures Joanna Klukowska
Office Hours TR 3:30-4:45PM CIWW 109

Use and design of data structures, which organize information in computer memory. Stacks, queues, linked lists, binary trees: how to implement them in a high-level language, how to analyze their effect on algorithm efficiency, and how to modify them. Programming assignments.

Prerequisites: Introduction to Computer Science (CSCI-UA 101), or a score of 4 or 5 on the AP Computer Science examination.
CSCI-UA.0102-005
(5886) Data Structures - Recitation Eric Schles W 3:30-4:45PM CIWW 109

Use and design of data structures, which organize information in computer memory. Stacks, queues, linked lists, binary trees: how to implement them in a high-level language, how to analyze their effect on algorithm efficiency, and how to modify them. Programming assignments.

Prerequisites: Introduction to Computer Science (CSCI-UA 101), or a score of 4 or 5 on the AP Computer Science examination.
CSCI-UA.0201-001
(5887) Computer Systems Organization Andrew Case TR 11:00-12:15PM CIWW 109

Covers the internal structure of computers, machine (assembly) language programming, and the use of pointers in high-level languages. Topics include the logical design of computers, computer architecture, the internal representation of data, instruction sets, and addressing logic, as well as pointers, structures, and other features of high-level languages that relate to assembly language. Programming assignments are in both assembly language and other languages.

Prerequisites: Data Structures (CSCI-UA 102).
CSCI-UA.0201-002
(5888) Computer Systems Organization Andrew Case TR 11:00-12:15PM CIWW 109

Covers the internal structure of computers, machine (assembly) language programming, and the use of pointers in high-level languages. Topics include the logical design of computers, computer architecture, the internal representation of data, instruction sets, and addressing logic, as well as pointers, structures, and other features of high-level languages that relate to assembly language. Programming assignments are in both assembly language and other languages.

Prerequisites: Data Structures (CSCI-UA 102).
CSCI-UA.0201-003
(8683) Computer Systems Organization Andrew Case MW 2:00-3:15PM CIWW 101

Covers the internal structure of computers, machine (assembly) language programming, and the use of pointers in high-level languages. Topics include the logical design of computers, computer architecture, the internal representation of data, instruction sets, and addressing logic, as well as pointers, structures, and other features of high-level languages that relate to assembly language. Programming assignments are in both assembly language and other languages.

Prerequisites: Data Structures (CSCI-UA 102).
CSCI-UA.0202-001
(5889) Operating Systems Benjamin Goldberg
Office Hours MW 9:30-10:45AM CIWW 109

Covers the principles and design of operating systems. Topics include process scheduling and synchronization, deadlocks, memory management (including virtual memory), input/output, and file systems. Programming assignments.

Prerequisites: Computer Systems Organization (CSCI-UA 201).
CSCI-UA.0202-002
(5890) Operating Systems Benjamin Goldberg
Office Hours MW 9:30-10:45AM CIWW 109

Covers the principles and design of operating systems. Topics include process scheduling and synchronization, deadlocks, memory management (including virtual memory), input/output, and file systems. Programming assignments.

Prerequisites: Computer Systems Organization (CSCI-UA 201).
CSCI-UA.0310-001
(5891) Basic Algorithms Richard Cole
Office Hours TR 2:00-3:15PM CIWW 109

Introduction to the study of algorithms. Presents two main themes: designing appropriate data structures and analyzing the efficiency of the algorithms that use them. Algorithms studied include sorting, searching, graph algorithms, and maintaining dynamic data structures. Homework assignments, not necessarily involving programming.

Prerequisites: Data Structures (CSCI-UA 102); Discrete Mathematics (MATH-UA 120); and either Calculus I (MATH-UA 121) OR Mathematics for Economics I (MATH-UA 211).
CSCI-UA.0310-002
(5892) Basic Algorithms Richard Cole
Office Hours TR 2:00-3:15PM CIWW 109

Introduction to the study of algorithms. Presents two main themes: designing appropriate data structures and analyzing the efficiency of the algorithms that use them. Algorithms studied include sorting, searching, graph algorithms, and maintaining dynamic data structures. Homework assignments, not necessarily involving programming.

Prerequisites: Data Structures (CSCI-UA 102); Discrete Mathematics (MATH-UA 120); and either Calculus I (MATH-UA 121) OR Mathematics for Economics I (MATH-UA 211).
CSCI-UA.0310-003
(5893) Basic Algorithms - Recitation Adriana Lopez-Alt W 12:30-1:45PM CIWW 109

Introduction to the study of algorithms. Presents two main themes: designing appropriate data structures and analyzing the efficiency of the algorithms that use them. Algorithms studied include sorting, searching, graph algorithms, and maintaining dynamic data structures. Homework assignments, not necessarily involving programming.

Prerequisites: Data Structures (CSCI-UA 102); Discrete Mathematics (MATH-UA 120); and either Calculus I (MATH-UA 121) OR Mathematics for Economics I (MATH-UA 211).
CSCI-UA.0330-001
MATH-UA.0144
(15112) Introduction to Computer Simulation Charles Peskin TR 11:00-12:15PM CIWW 201

In this course, students will learn how to do computer simulations of such phenomena as orbits (Kepler problem and N-body problem), epidemic and endemic disease (including evolution in response to the selective pressure of a malaria), musical stringed instruments (piano, guitar, and violin), and traffic flow in a city (with lights, breakdowns, and gridlock at corners). The simulations are based on mathematical models, numerical methods, and Matlab programming techniques that will be taught in class. The use of animations (and sound where appropriate) to present the results of simulations will be emphasized.

Prerequisites: Calculus I (MATH-UA 121) or Math for Economics II (MATH-UA 212) and General Physics (PHYS-UA 11).
CSCI-UA.0330-002
MATH-UA.0144
(15971) Introduction to Computer Simulation Chengcheng Huang F 11:00-12:15PM CIWW 201

In this course, students will learn how to do computer simulations of such phenomena as orbits (Kepler problem and N-body problem), epidemic and endemic disease (including evolution in response to the selective pressure of a malaria), musical stringed instruments (piano, guitar, and violin), and traffic flow in a city (with lights, breakdowns, and gridlock at corners). The simulations are based on mathematical models, numerical methods, and Matlab programming techniques that will be taught in class. The use of animations (and sound where appropriate) to present the results of simulations will be emphasized.

Prerequisites: Calculus I (MATH-UA 121) or Math for Economics II (MATH-UA 212) and General Physics (PHYS-UA 11).
CSCI-UA.0380-001
(7989) Topics of General Interest: Physical Computing Amos Bloomberg
Office Hours MW 12:30-1:45PM CIWW 202
Detailed descriptions available when topics are announced. Typical offerings include Computing in the Humanities and Arts and Introduction to Flash Programming. Does not count toward the computer science major.

Prerequisites: Topics determine prerequisites.
CSCI-UA.0380-002
(16571) Topics of General Interest: Drawing on the Web Joshua Clayton
Office Hours MW 3:30-4:45PM 719BWY 1221
Detailed descriptions available when topics are announced. Typical offerings include Computing in the Humanities and Arts and Introduction to Flash Programming. Does not count toward the computer science major.

Prerequisites: Topics determine prerequisites.
CSCI-UA.0421-001
(5894) Numerical Computing Denis Zorin
Office Hours MW 11:00-12:15PM 719BWY 1221

The need for floating-point arithmetic, the IEEE floating-point standard, and the importance of numerical computing in a wide variety of scientific applications. Fundamental types of numerical algorithms: direct methods (e.g., for systems of linear equations), iterative methods (e.g., for a nonlinear equation), and discretization methods (e.g., for a differential equation). Numerical errors: can you trust your answers? Uses graphics and software packages such as Matlab. Programming assignments.

Prerequisites: Computer Systems Organization (CSCI-UA 201), either Calculus I (MATH-UA 121) or both of Mathematics for Economics I and II (MATH-UA 211 and 212), and Linear Algebra (MATH-UA 140), or permission of instructor.
CSCI-UA.0472-001
(7644) Artificial Intelligence Ernest Davis
Office Hours TR 2:00-3:15PM CIWW 202
Many cognitive tasks that people can do easily and almost unconsciously have proven extremely difficult to program on a computer. Artificial intelligence tackles the problem of developing computer systems that can carry out these tasks. Focus is on three central areas in AI: representation and reasoning, machine learning, and natural language processing.

Prerequisites: Computer Systems Organization (CSCI-UA 201) and Basic Algorithms (CSCI-UA 310).
CSCI-UA.0478-001
MATH-UA.0243
(19195) Introduction To Cryptography Victor Shoup
Office Hours MW 9:30-10:45AM CIWW 312
An introduction to the principles and practice of cryptography and its application to network security. Topics include symmetric-key encryption (block ciphers, modes of operations, AES), message authentication (pseudorandom functions, CBC-MAC), public-key encryption (RSA, ElGamal), digital signatures (RSA, Fiat-Shamir), and authentication applications (identification, zero-knowledge).

Prerequisites: Basic Algorithms (CSCI-UA 310).
CSCI-UA.0480-001
(5895) Special Topics: Computer Vision Rob Fergus
Office Hours TR 11:00-12:15PM CIWW 202
Detailed course descriptions are available when advanced topics are announced each semester. Typical offerings include, but are not limited to, Bioinformatics, Building Robots, Computer Graphics, Machine Learning, Network Programming, Computer Vision, and Multimedia for Majors.

Prerequisites: Topics determine prerequisites.
CSCI-UA.0480-002
(5896) Special Topics: iPhone Programming Nathan Hull
Office Hours MW 3:30-4:45PM CIWW 317
Detailed course descriptions are available when advanced topics are announced each semester. Typical offerings include, but are not limited to, Bioinformatics, Building Robots, Computer Graphics, Machine Learning, Network Programming, Computer Vision, and Multimedia for Majors.

Prerequisites: Topics determine prerequisites.
CSCI-UA.0480-003
(5897) Special Topics: Parallel Computing Mohamed Zahran
Office Hours TR 9:30-10:45AM CIWW 317
Detailed course descriptions are available when advanced topics are announced each semester. Typical offerings include, but are not limited to, Bioinformatics, Building Robots, Computer Graphics, Machine Learning, Network Programming, Computer Vision, and Multimedia for Majors.

Prerequisites: Topics determine prerequisites.
CSCI-UA.0480-004
(7992) Special Topics: Algorithmic Problem Solving Brett Bernstein
Office Hours
Sean McIntyre MW 3:30-4:45PM CIWW 512
Detailed course descriptions are available when advanced topics are announced each semester. Typical offerings include, but are not limited to, Bioinformatics, Building Robots, Computer Graphics, Machine Learning, Network Programming, Computer Vision, and Multimedia for Majors.

Prerequisites: Topics determine prerequisites.
CSCI-UA.0521-001
(5898) Undergraduate Research STAFF -
The student is supervised by a faculty member actively engaged in research, possibly leading to results publishable in the computer science literature. A substantial commitment to this work is expected. The research project may be one or two semesters, to be determined in consultation with the faculty supervisor. Students taking this course for honors in computer science are required to write an honors thesis. All other students need to submit a write-up of the research results at the conclusion of the project.

Prerequisites: Permission of the department.
CSCI-UA.0998-001
(5899) Independent Study STAFF -

Students majoring in the department are permitted to work on an individual basis under the supervision of a full-time faculty member in the department if they have maintained an overall GPA of 3.0 and a GPA of 3.5 in computer science and have a study proposal that is approved by the director of undergraduate studies. Students are expected to spend about three to six hours a week on their project.

Prerequisites: Permission of the department. Does not satisfy the major elective requirement.

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**

Indicates controlled enrollment (permission number required for registration). Contact Santiago Pizzini (pizzini@cs.nyu.edu).
***

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