Course Schedule

Current semester Fall 2016, and future semesters are now available to view.

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Number

Name

Professor(s)

Meet Time

Room

CSCI-GA.1133-001
(1129) PAC I* Evan Korth
Office Hours T 6:30-9:00PM CIWW 201

An accelerated introduction to the fundamental concepts of computer science for students who lack a formal background in the field. Topics include algorithm design and program development; data types; control structures; subprograms and parameter passing; recursion; data structures; searching and sorting; dynamic storage allocation and pointers; abstract data types, such as stacks, queues, lists, and tree structures; generic packages; and an introduction to the principles of object-oriented programming. The primary programming language used in the course will be Java. Students should expect an average of 12-16 hours of programming and related course work per week.
CSCI-GA.1133-002
(1675) PAC I Recitation Jesse David Gumz W 7:10-8:00PM CIWW 201

An accelerated introduction to the fundamental concepts of computer science for students who lack a formal background in the field. Topics include algorithm design and program development; data types; control structures; subprograms and parameter passing; recursion; data structures; searching and sorting; dynamic storage allocation and pointers; abstract data types, such as stacks, queues, lists, and tree structures; generic packages; and an introduction to the principles of object-oriented programming. The primary programming language used in the course will be Java. Students should expect an average of 12-16 hours of programming and related course work per week.
CSCI-GA.1170-001
(1130) Fundamental Algorithms Alan Siegel
Office Hours T 5:10-7:00PM 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.1170-002
(1131) 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.1170-003
(23220) Fundamental Algorithms Yevgeniy Dodis
Office Hours W 5:10-7:00PM CIWW 517

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.1170-004
(23221) Fundamental Algorithms Recitation Aleksandr Golovnev F 6:10-7:00PM CIWW 517

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.1180-001
(2132) Mathematical Techniques For CS Applications Margaret Wright
Office Hours M 5:10-7:00PM CIWW 512

An introduction to theory, computational techniques, and applications of linear algebra, probability and statistics. These three areas of continuous mathematics are critical in many parts of computer science, including machine learning, scientific computing, computer vision, computational biology, natural language processing, and computer graphics. The course teaches a specialized language for mathematical computation, such as Matlab, and discusses how the language can be used for computation and for graphical output. No prior knowledge of linear algebra, probability, or statistics is assumed.
CSCI-GA.2110-001
(1132) Programming Languages Benjamin Goldberg
Office Hours W 5:10-7:00PM 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.2110-002
(1133) Programming Languages Recitation Deepti Verma 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.2110-003
(1916) Programming Languages Cory Plock
Office Hours M 5:10-7:00PM CIWW 201

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.2110-004
(1693) Programming Languages Recitation Daniel Wanghua Zhang F 5:10-6:00PM CIWW 517

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
(1134) Scientific Computing Aaditya Rangan R 5:10-7:00PM 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
(1135) Compiler Construction Eva Rose
Office Hours R 5:10-7:00PM CIWW 312
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.2180-001
(1918) Financial Software Projects Scott Burton
Office Hours M 7:10-9:00PM CIWW 512
The theme of this course is an "applied case study" and focuses on fixed income markets. Topics covered include an overview of the markets, the inner workings of an investment bank, the market players, and where software engineers fit in. Students will be grouped into small teams to build a financial application using practical software engineering principles. Each team will build a risk management framework, starting with basic components.

Prerequisites: It is assumed that the students can code in C++. No prior experience in the financial sector domain is required.
CSCI-GA.2246-001 Open Source Tools CANCELLED -
This course covers a brief history and philosophy of open source software, followed by an in-depth look at open source tools intended for developers. In particular, we will present an overview of the Linux operating system, command line tools (find, grep, sed), programming tools (GIT, Eclipse, DTrace), web and database tools (Apache, MySQL), and system administration tools. We will also cover scripting languages such as shell and Python.

Prerequisites: An understanding of modern operating systems and a working knowledge of a programming language, such as C, C++ or Java
CSCI-GA.2250-001
(1136) Operating Systems Hubertus Franke
Office Hours M 7:10-9:00PM CIWW 1302
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
(1710) Data Communications and Networks Jean-Claude Franchitti
Office Hours R 7:10-9:00PM CIWW 312

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.2270-001
(2055) Computer Graphics Daniele Panozzo
Office Hours M 7:10-9:00PM CIWW 312

Problems and objectives of computer graphics. Vector, curve, and character generation. Interactive display devices. Construction of hierarchical image list. Graphic data structures and graphics languages. Hidden-line problems; windowing, shading, and perspective projection. Curved surface generation display.

Prerequisites: CSCI-GA 1170 and CSCI-UA 140 (or an equivalent undergraduate course in linear algebra).
CSCI-GA.2271-001
(1920) Computer Vision Rob Fergus
Office Hours R 7:10-9:00PM CIWW 1302

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.2274-001
(18035) Advanced Computer Graphics Kenneth Perlin T 7:10-9:00PM 719BWY 1221

This is a capstone course based on computer graphics tools. The course covers a selection of topics that may include computer animation, gaming, geometric modeling, motion capture, computational photography, physically based simulation, scientific visualization, and user interfaces. Not all areas are available every semester; the choice of areas is determined by the instructor. The capstone project involves 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, CSCI-GA 2250 and CSCI-GA 2270
CSCI-GA.2390-001
(18036) Logic In Computer Science CANCELLED -
A beginning graduate-level course in mathematical logic with motivation provided by applications in computer science. There are no formal prerequisites, but the pace of the class requires that students can cope with a significant level of mathematical sophistication. Topics include propositional and first-order logic; soundness, completeness, and compactness of first-order logic; first-order theories; undecidability and Godel’s incompleteness theorem; and an introduction to other logics such as second-order and temporal logic.

Prerequisites: Strong mathematical background and instructor permission for master’s students
CSCI-GA.2420-001
MATH-GA 2010-001
(1137) Numerical Methods I Georg Stadler
Office Hours R 5:10-7:00PM CIWW 101
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
(1705) Database Systems Zvi Kedem
Office Hours T 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.2434-001
(1138) Advanced Database Systems Dennis Shasha
Office Hours T 5:10-7:00PM CIWW 101
This is a capstone course emphasizing large-scale database systems. This course studies the internals of database systems as an introduction to research and as a basis for rational performance tuning. Topics include concurrency control, fault tolerance, operating system interactions, query processing, and principles of tuning. Database capstone projects involve topics such as design, concurrency control, interactions, and tuning. These projects include 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.2560-001
(2053) Artificial Intelligence Ernest Davis
Office Hours R 5:10-7:00PM CIWW 202

There are many cognitive tasks that people do easily and almost unconsciously but that have proven extremely difficult to program on a computer. Artificial intelligence is the problem of developing computer systems that can carry out these tasks. This course covers problem solving and state space search; automated reasoning; probabilistic reasoning; planning; and knowledge representation.
CSCI-GA.2566-001
(1921) Foundations Of Machine Learning Mehryar Mohri
Office Hours T 5:10-7:00PM CIWW 102

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.2569-001
DS-GA.1005-001
(23251) Inference and Representation David Sontag
Office Hours
Joan Bruna M 5:10-7:00PM CIWW 1302

This course covers graphical models, causal inference, and advanced topics in statistical machine learning.

Prerequisites: DS-GA 1004
CSCI-GA.2569-002
DS-GA.1005-002
(23252) Inference and Representation Lab Rahul Gopalkrishnan W 7:10-8:00PM 194M 306

This course covers graphical models, causal inference, and advanced topics in statistical machine learning.

Prerequisites: DS-GA 1004
CSCI-GA.2580-001
(18037) Web Search Engines Cong Yu
Office Hours
Fernando Diaz M 5:10-7:00PM CIWW 312

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.2930-002
MATH-GA 2830-002
(2347) Advanced Topics in Applied Math: Mathematics of Data Science Afonso Bandeira
Office Hours W 11:00-12:50PM CIWW 1302

A mostly self-contained research-oriented and fast-paced course designed for PhD students with an interest in doing research in theoretical aspects of algorithms that aim to extract information from data. These often lie in overlaps of (Applied) Mathematics with: Computer Science, Electrical Engineering, Statistics, and/or Operations Research. Each lecture will feature either one or two Mathematical Open Problem(s) with relevance in Data Science. The main mathematical tools used will be Probability and Linear Algebra, and a basic familiarity with these subjects is required. There will also be some (although knowledge of these tools is not assumed) Graph Theory, Representation Theory, Applied Harmonic Analysis, among others. The topics treated will include Dimension reduction, Manifold learning, Sparse recovery, Random Matrices, Approximation Algorithms, Community detection in graphs, and several others.
CSCI-GA.2945-001
MATH-GA.2011-001
(1139) Adv Topics Num. Analysis: Approximation Computational Fluid Dynamics Aleksandar Donev
Office Hours R 9:00-10:50AM CIWW 512
Topics vary each semester.

Prerequisites: Topics determine prerequisites.
CSCI-GA.2945-002
MATH-GA.2011-002
(21432) Adv Topics Num. Analysis: Numerical Optimization Margaret Wright
Office Hours T 5:10-7:00PM CIWW 202
Topics vary each semester.

Prerequisites: Topics determine prerequisites.
CSCI-GA.2945-003
MATH-GA.2011-003
(21433) Adv Topics Num. Analysis: Exploring ODEs Lloyd N. Trefethen TR 1:25-3:15PM CIWW 1302

The course is intended for Courant Institute graduate students who are either mathematics students on the applied half of the spectrum or computer science students with an interest in numerical computation. ODEs, the starting point of analysis and dynamics, are one of the two foundation stones of applied mathematics (the other is linear algebra). This course will deepen your appreciation of them fundamentally.

This course will be based on a new textbook that I am 2/3 of the way through writing, Exploring ODEs, with coauthors Toby Driscoll and Asgeir Birkisson. The book aims to be interesting and informative for every applied or numerical mathematician. Its unusual missions are to be numerically-enabled, but not a numerical book and mathematically mature, but not technically advanced. To get an idea, including the table of contents, take a look at the talk I gave about the book project posted here.

The course will be assessed by homework assignments. These will be computational (working in Chebfun), but will be about behavior of ODEs, not about algorithms or numerical analysis.
CSCI-GA.2945-004
MATH-GA.2011-004
(21434) Adv Topics Num. Analysis: Finite Elements Olof Widlund
Office Hours T 9:00-10:50AM CIWW 512

This course will provide an introduction to the finite element method and its theoretical foundation.

Self-adjoint elliptic problem and calculus of variation. Sobolev spaces, Poincare's and Friedrichs' inequalities. Triangulations of bounded domains in two and three dimensions. Lagrange and Hermite finite elements, which are conforming in H^1. The biharmonic problem and H^2 conforming elements.

Error bounds for basic finite element methods: Cea's lemma and the result of Aubin and Nitsche. Nonconforming finite elements: the lemmas due to Strang. Isoparametric elements and spectral elements. Compressible and almost incompressible elasticity. Mixed methods and the inf-sup condition due to Babuska and Brezzi. Incompressible Stokes. Raviart-Thomas elements and other elements conforming in H(div). Nedelec elements and other conforming elements in H(curl). Solving the large linear and non-linear systems of algebraic equations resulting from finite element approximations. An introduction to domain decomposition and multigrid algorithms.
CSCI-GA.2965-001
(1140) Heuristic Problem Solving Dennis Shasha
Office Hours T 7:10-9:00PM CIWW 101
This course revolves around several problems new to computer science (derived from games or puzzles in columns for Dr. Dobb’s Journal, Scientific American, and elsewhere). The idea is to train students to face a new problem, read relevant literature, and come up with a solution. The solution entails winning a contest against other solutions. The winner receives candy. The best solutions become part of an evolving “Omniheurist” Web site that is expected to get many visitors over the years. The course is for highly motivated, mathematically adept students. It is open to supported Ph.D. students and well-qualified master’s students. Class size has been around 10 in the past, and instructor and students have all gotten to know one another very well. Algorithmic and programming knowledge is the main prerequisite. It also helps to be familiar with a rapid prototyping language such as Matlab, Mathematica, K, or Python, or to be completely fluent in some other language.

Prerequisites: CSCI-GA 1170 and an ability to prototype algorithms rapidly.
CSCI-GA.3033-001
(1141) Special Topics: Production Quality Software Michael Schidlowsky
Office Hours W 5:10-7:00PM CIWW 317

In this course we study the craft of software engineering. The semester begins with a thorough review of the Java Language and Virtual Machine, emphasizing library components and language features most relevant to most development projects. Later lectures cover more sophisticated features in the language like concurrency and thread-safety, writing tests, properly designing classes and Object-Oriented programs, and design patterns. Certain non-technical topics are critical to successful software development and are reinforced throughout the semester. These include writing readable code, the long-term consequences of bugs, the psychology of human motivation, successfully developing and reinforcing habits, what science knows about human productivity and drive, and how to motivate ourselves and our team. Lessons are reinforced with weekly assignments that are meticulously graded. Some submissions are critiqued, line-by-line, in classroom code reviews. The end of the semester includes a lecture on how to best prepare for interviews and write an effective resume, incorporating techniques from world-class athletes and performers on how to optimally perform under extreme stress.
CSCI-GA.3033-002
(1142) Special Topics: Distributed Systems Jinyang Li
Office Hours W 7:10-9:00PM CIWW 317

Distributed systems help programmers aggregate the resource of many networked computers to construct highly available and scalable services, such as peta-byte storage, massively parallel computation. This class teaches the abstractions, design and implementation techniques that allow you to build fast, scalable, fault-tolerant distributed systems. Topics include concurrency and consistency, fault tolerance, distributed transactions, and several case studies of distributed systems. This class is a graduate-level course, but advanced undergraduate students are welcome! The course consists of lectures and a series of programming labs.
CSCI-GA.3033-003
(1143) Special Topics: Music Software Projects Scott Burton
Office Hours F 4:00-5:50PM CIWW 312

Did you ever wonder why there are 12 notes in the western music scale? Or how the intervals between notes came to be? When were the first musical scales developed or "discovered" and how (and why) have they been modified since? Who were the key innovators of western music theory over the last few centuries?

It is not uncommon for software developers to have an affinity for music. After all, the creation of both software and music is part art and part science. Further, music and computing are built upon fundamental mathematical principles. While it is not required to understand music theory to be a good player, understanding why we are constrained to a certain set of notes is an enlightening topic - for musicians and non-musicians alike.

This course is for students interested in both music and software construction!
CSCI-GA.3033-004
(1144) Special Topics: Graphics Processing Units (GPUs): Architecture & Programming Mohamed Zahran
Office Hours T 5:10-7:00PM CIWW 317

In this course, we will cover architectural aspects and capabilities of modern GPUs (graphics processing unit) and will learn the architecture and the programming of GPUs to solve different type of problems. Many computations can be performed much faster on the GPU than on a traditional processor. This is why GPUs are present now in almost all computers; and the majority of Top 500 supercomputers in the world are built around GPUs. GPUs are no longer restricted to graphics applications but are now used for a diverse set of applications and domains. This introduces the concept of general-purpose GPUs or GPGPUs, which is the main subject of this course.
CSCI-GA.3033-005
(1145) Special Topics: Principles of Software Security Patrick Cousot
Office Hours M 7:10-9:00PM CIWW 201

Traditionally, computer security is enforced by the operating system, which uses special hardware support to ensure security properties at application boundaries. However, the proliferation of successful attacks, such as viruses, worms, SQL injection, and cross-site scripting, shows that traditional approaches to security are insufficient. Adversaries exploit weaknesses both in the operating system itself, bypassing any protection mechanisms, and more and more frequently at the application level, where the operating system provides very limited guarantees. In this class we consider how programming language techniques can be used to fill the security gap by defending against application-level attacks. The approach is based on the static analysis of the program source to certify security properties.
CSCI-GA.3033-006
(1146) Special Topics: Realtime and Big Data Analytics Suzanne McIntosh
Office Hours R 7:10-9:00PM CIWW 102

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 and Linux will be useful.
CSCI-GA.3033-007
(1147) Special Topics: Social Multiplayer Games Yoav Zibin
Office Hours R 5:10-7:00PM CIWW 517

The course will teach how to develop online casual multiplayer games using open technologies such as HTML5, JavaScript, Typescript, AngularJS, Ionic, Bootstrap, PhoneGap, Grunt, and testing using Karma, Jasmine, Protractor. Students will build several turn based games and submit them to Google play store. There is no final exam, only assignments. The course will also teach about artificial-intelligence for games, ranking systems, physics-based engines, and integrating with social platforms. The course will not concern with 3D graphics.
CSCI-GA.3033-008
(2057) Special Topics: Statistical Natural Language Processing Slav Petrov
Office Hours T 5:10-7:00PM CIWW 512

In this course we will examine some of the core tasks in natural language processing, starting with simple word-based models for text classification and building up to rich, structured models for syntactic parsing and machine translation. In each case we will discuss recent research progress in the area and how to design efficient systems for practical user applications. There will be a focus on corpus-driven methods that make use of supervised and unsupervised machine learning methods and algorithms. We will explore statistical approaches based on graphical models and neural networks. In the course assignments, which will be updated this year to include more neural network modeling, you will construct basic systems and then improve them through a cycle of error analysis and model redesign. This course assumes a good background in basic probability and a strong ability and interest in building real systems. The class is open to graduate as well as undergraduate students.
CSCI-GA.3033-011
(2337) Special Topics: Predictive Analytics Anasse Bari
Office Hours W 7:10-9:00PM CIWW 102

Predictive analytics is the art and science of extracting useful information from historical data and present data for the purpose of predicting future trends. In this course, students will have an introduction to the phases of the analytics lifecycle and a basic understanding of a variety of tools and machine learning techniques to analyze data to discover forward insights. Several techniques will be introduced; including data pre-processing techniques, data clustering algorithms, data classification algorithms, association rules data mining algorithms, recommender systems, etc.

Applications from bio-informatics, social networks analytics, and text mining will be covered. Highlights from industrial use cases will be covered to demonstrate how Predictive Analytics relates to improving business performance and impacting better decisions. This is an introductory course that will provide students with basic skills of the new generation of data scientists that will allow them to structure, analyze and derive useful insights from data that could help make better decisions.
CSCI-GA.3033-012
(2335) Special Topics: Advanced Computer Vision Davi Geiger R 5:10-7:00PM CIWW 201

This is a hands-on course that goes over some basic aspects of computer vision and selected topics which students develop their own algorithms for. The topics that will be covered are feature representation and detection (wavelets), stereo vision (matching), symmetry, and recognition (learning). There is a final project where students present a computer vision system. Basic knowledge of linear algebra and algorithms is required.
CSCI-GA.3033-014
(18098) Special Topics: DevOps John Rofrano
Office Hours
Nikolai Joukov
Harigovind Ramasamy W 5:10-7:00PM CIWW 512

DevOps is more than just a fusion of development and operations. It is the cultural change that embraces Agile methodology, Social Coding, Test Drive Development, new tools to provide Continuous Integration, Testing, and Delivery, and a fundamental shift in what it means to “move into production”. Developers are empowered to “fail fast” and deploy early and often. Cloud Computing is at the heart of this movement. Cloud Native applications built from microservices require DevOps to manage the often complex production pipeline. DevOps allows businesses to move with increased agility and stability.

Upon completing this course students will be able to work as an Agile team and setup a DevOps pipeline to continuously integrate their code changes and deploy Cloud Native applications that they write. They will also gain an understanding of what it means for Enterprise IT to use DevOps to become Cloud Native and operate at scale. Topics covered will include: Social Coding, Creating RESTful Microservices, IBM Bluemix. Watson Services, Docker, Cloud Foundry, GitHub, ZenHub, Travis CI, Jenkins, Vagrant, Test Drive Development, Python Flask, Node.js, Redis, Cloudant, Ansible, Chef, Puppet. Students will be given access to IBM Bluemix and Watson Services for the duration of the course and will be deploying their homework there. This course is 50% lecture and 50% hand-on so come prepared to learn by doing.
CSCI-GA.3033-015
(18099) Special Topics: Rapid Prototyping, Lean Engineering & Agile Development Evan Korth
Office Hours W 7:10-9:00PM CIWW 202

Agile software development is a group of software development methods in which requirements and solutions evolve through collaboration between self-organizing, cross-functional teams. In this class, students learn agile practices in software product development, and build up a new leadership toolbox for driving innovation and change, and improve their ability to lead high-performing teams and organizations. Based on iterative and incremental development, students learn adaptive planning, evolutionary development and delivery, a time-boxed iterative approach, encouraging rapid and flexible response to change. Student teams will work on software projects proposed by members of the class.

Prerequisites: CSCI-GA 2110 Programming Languages
CSCI-GA.3033-016
(24637) Special Topics: Foundations of Networking and Mobile Systems Lakshminarayanan Subramanian T 7:10-9:00PM CIWW 517

This is an introductory course that would expose students to the fundamentals of computer networks and mobile systems. This class has no specific prerequisites. The class will begin with introductory concepts of network protocols across different layers of the network stack including routing, transport, naming, addressing and connect them to the core building blocks of the Internet. The second part of the class will focus on networking concepts in the evolution of Web-based systems, providing an introduction to data-center networks, clouds, middle boxes (proxies, firewalls) and next-generation networks. The third part of the class will focus on the fundamental concepts in wireless networks, cellular networks and mobile devices with a specific focus on mobile programming and applications, 802.11 evolution, mobile services and the evolution of cellular networks. The final part of the class will focus on current and trending developments in networks and mobile systems.

Students who have taken CSCI-GA 2620 Networks and Mobile Systems or Networks and Distributed Systems are not eligible to take this course for credit.
CSCI-GA.3033-017
(25139) Special Topics: Multicore Programming Christopher Mitchell
Office Hours R 7:10-9:00PM CIWW 512

Through the 1990s, processors got faster and faster, but around the turn of the millennium, CPUs started to reach physical limits. To drive innovation and produce more powerful computers, manufacturers began to pack multiple cores into each processor. However, most software is conceived by the programmer as a linear progression of instructions. Compilers can find some parallelization opportunities, but that’s not enough to take full advantage of multiple cores. Programmers must take much of the responsibility for making their programs exploit multiple cores, and this course discusses many modern techniques:

- aspects of the architecture of modern machines
- Classic and modern algorithms for coordination and synchronization
- Data structures that exploit and extract performance from multiple cores
- Current and future programming techniques and best practices for multiple cores

Students will be expected to have experience with a programming-intensive course, as well as some experience with C/C++. The course will include lectures, homework, labs, a final project, and a final exam.
CSCI-GA.3205-001
(2054) Applied Cryptography & Network Security Zvi Kedem
Office Hours W 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.3210-001
MATH-GA 2170-001
(1728) Introduction To Cryptography Oded Regev
Office Hours M 11:00-12:50PM CIWW 517
The primary focus of this course is on definitions and constructions of various cryptographic objects, such as pseudorandom generators, encryption schemes, digital signature schemes, message authentication codes, block ciphers, and others, time permitting. The class tries to understand what security properties are desirable in such objects, how to properly define these properties, and how to design objects that satisfy them. Once a good definition is established for a particular object, the emphasis will be on constructing examples that provably satisfy the definition. Thus, a main prerequisite of this course is mathematical maturity and a certain comfort level with proofs. Secondary topics, covered only briefly, are current cryptographic practice and the history of cryptography and cryptanalysis.

Prerequisites: Strong mathematical background
CSCI-GA.3250-001 Honors Operating Systems CANCELLED -
Operating-system structure. Processes. Process synchronization. Language mechanisms for concurrency. Deadlocks: modeling, prevention, avoidance, and recovery. Memory management. File-system interface. Secondary storage. Distributed systems: layered system design, managing distributed processes, distributed shared memory, fault-tolerance. CPU scheduling. Queuing and performance: analysis of single M/M/1 queue and others. Protection and security. Advanced security concepts: threat monitoring, encryption, and public keys.

Prerequisites: Permission of the instructor for master’s students
CSCI-GA.3520-001
(1148) Honors Analysis of Algorithms Subhash Khot
Office Hours TR 9:30-10:45AM CIWW 317
Design of algorithms and data structures. Review of searching, sorting, and fundamental graph algorithms. In-depth analysis of algorithmic complexity, including advanced topics on recurrence equations and NP-complete problems. Advanced topics on lower bounds, randomized algorithms, amortized algorithms, and data structure design as applied to union-find, pattern matching, polynomial arithmetic, network flow, and matching.

Prerequisites: Permission of the instructor for master’s students.
CSCI-GA.3812-001
(1149) Information Technology Projects * Jean-Claude Franchitti
Office Hours M 6:10-9:10PM 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.3813-002
(1151) Adv Lab MS * STAFF -

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
(1152) Adv Lab MS * STAFF -

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
(1153) Adv Lab MS * STAFF -

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
(1154) Adv Lab PhD ** STAFF -

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
(1155) Adv Lab PhD ** STAFF -

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
(1156) Adv Lab PhD ** STAFF -

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
(1157) Adv Lab PhD ** STAFF -

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
(1158) Master's Thesis Research * STAFF -

Prerequisites: Approval of a faculty adviser and the Director of Graduate Studies for the M.S. programs.
CSCI-GA.3850-001
(1159) 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
(1160) PhD Seminar: Formal Methods** Thomas Wies
Office Hours W 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
(1924) PhD Seminar: Machine Learning** Mehryar Mohri
Office Hours T 3:45-5:00PM CIWW 1302
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
(1161) PhD Thesis Research ** STAFF -

Prerequisites: Permission of the thesis adviser or director of graduate studies for the Ph.D. program.
CSCI-GA.3870-001
(19709) Internship In Computer Science MS* Faculty -

Participation in a programming project or research project conducted outside of the classroom in a governmental, commercial, or academic setting. Open only to graduate students with permission of the Director of Graduate Studies (DGS). Students must submit a brief written description of their work to the DGS before starting the internship and submit a written summary of their work when it is completed. MS students may take this course a maximum of two times. PhD students who wish to take this course more than four times need to request a special permission and provide adequate academic justification.

Section 1 is for Master's students. Section 2 is for Ph.D. students.

Prerequisites: Permission of Director of Graduate Studies.
CSCI-GA.3870-002
(19710) Internship in Computer Science PhD* Faculty -

Participation in a programming project or research project conducted outside of the classroom in a governmental, commercial, or academic setting. Open only to graduate students with permission of the Director of Graduate Studies (DGS). Students must submit a brief written description of their work to the DGS before starting the internship and submit a written summary of their work when it is completed. MS students may take this course a maximum of two times. PhD students who wish to take this course more than four times need to request a special permission and provide adequate academic justification.

Section 1 is for Master's students. Section 2 is for Ph.D. students.

Prerequisites: Permission of Director of Graduate Studies.
CORE-UA.0109-001 Quantitative Reasoning: Mathematics and Computing Joanna Klukowska
Office Hours MW 9:30-10:45AM 7E12 125

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: RECITATION Sebastian Herscher R 9:30-10:45AM Tisch LC19

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
(6142) Intro To Computer Programming Syed Salahuddin TR 12:30-1:45PM 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.0002-002
(6143) Intro To Computer Programming Craig Kapp
Office Hours TR 11:00-12:15PM CIWW 312

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
(6144) Intro To Computer Programming Abraham Rubenstein
Office Hours MW 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.0002-004 Intro To Computer Programming Deena Engel TR 2:00-3:15PM CIWW 202

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
(6146) Intro To Computer Programming Michell Cardona
Office Hours MW 9:30-10:45AM CIWW 201

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
(6147) Intro To Computer Programming Joshua Clayton
Office Hours TR 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.0002-007
(6148) Intro To Computer Programming Adam Meyers
Office Hours MW 8:00-9:15AM 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
(7900) Intro To Computer Programming Joseph Versoza
Office Hours MW 12:30-1:45PM 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
(7902) Intro To Computer Programming Jerry Waxman
Office Hours TR 3:30-4:45PM 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.0002-010 Intro To Computer Programming Craig Kapp
Office Hours 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.0002-011
(8249) Intro To Computer Programming Adam Meyers
Office Hours TR 8:00-9:15AM 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.0002-012
(9202) Intro To Computer Programming Amos Bloomberg
Office Hours MW 11:00-12:15PM CIWW 312

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
(6149) Intro to Web Design & Computer Principles Lee-Sean Huang
Office Hours MW 3:30-4:45PM 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.0004-002
(6150) Intro to Web Design & Computer Principles Alvaro Olsen
Office Hours TR 12:30-1:45PM 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.0004-003
(6151) Intro to Web Design & Computer Principles Joshua Clayton
Office Hours MW 11:00-12:15PM 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
(6152) Intro to Web Design & Computer Principles Nathan Hull
Office Hours TR 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.0004-005
(7689) 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.0004-006
(7901) Intro to Web Design & Computer Principles Joshua Clayton
Office Hours TR 2:00-3:15PM 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.0004-007
(8130) Intro to Web Design & Computer Principles Adam Scher 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
(7938) Database Design And Web Implementation Deena Engel MW 11:00-12:15PM CIWW 512

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.0060-002
(8723) Database Design And Web Implementation Amos Bloomberg
Office Hours MW 2:00-3:15PM CIWW 201

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
(6153) Web Development And Programming Sana Odeh
Office Hours MW 12:30-1:45PM CIWW 101

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.0061-002
(8480) Web Development And Programming Sana Odeh
Office Hours TR 3:30-4:45PM CIWW 517

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.0101-001
(6154) Intro To Computer Science Anasse Bari
Office Hours TR 9:30-10:45AM CIWW 202

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
(6155) Intro To Computer Science Amos Bloomberg
Office Hours TR 11:00-12:15PM CIWW 201

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
(6156) Intro To Computer Science Anasse Bari
Office Hours MW 11:00-12:15PM 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
(6157) Intro To Computer Science Randy Shepherd
Office Hours MW 3:30-4:45PM CIWW 202

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
(7744) Intro To Computer Science Randy Shepherd
Office Hours TR 3:30-4:45PM CIWW 512

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
(7930) Intro To Computer Science Douglas Moody
Office Hours MW 9:30-10:45AM CIWW 317

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
(8134) Intro To Computer Science Candido Cabo
Office Hours MW 12:30-1:45PM CIWW 201

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.0101-008 Intro To Computer Science CANCELLED 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.0101-009
(19675) Intro To Computer Science Brett Peterson
Office Hours MW 8:00-9:15AM 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.0102-001
(6158) Data Structures Ernest Davis
Office Hours MW 9:30-10:45AM CIWW 101

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
(6159) Data Structures - Recitation Shuai Mu 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.0102-003
(6160) Data Structures Joanna Klukowska
Office Hours TR 11:00-12:15PM CIWW 101

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
(6161) Data Structures - Recitation Abtin Rahimian W 12:30-1:45PM 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
(6162) Data Structures Joanna Klukowska
Office Hours MW 2:00-3:15PM 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.0102-006
(8218) Data Structures - Recitation Abtin Rahimian M 12:30-1:45PM 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.0102-007
(9171) Data Structures Chee Yap
Office Hours TR 8:00-9:15AM CIWW 102

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.0102-008
(9172) Data Structures - Recitation Qi Feng W 8:00-9:15AM CIWW 101

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
(6163) Computer Systems Organization Mohamed Zahran
Office Hours 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
(6164) Computer Systems Organization - Recitation Nikita Sharma R 8:00-9:15AM 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
(7931) Computer Systems Organization Mohamed Zahran
Office Hours TR 3:30-4:45PM CIWW 102

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.0201-004
(17361) Computer Systems Organization - Recitation Nikita Sharma T 8:00-9:15AM 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.0201-005
(17362) Computer Systems Organization Jinyang Li
Office Hours MW 3:30-4:45PM CIWW 312

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.0201-006
(17363) Computer Systems Organization - Recitation Hassan Mujtaba Zaidi W 8:00-9:15AM CIWW 312

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
(6165) Operating Systems Allan Gottlieb
Office Hours TR 2:00-3:15PM 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
(6166) Basic Algorithms Yevgeniy Dodis
Office Hours TR 3:30-4:45PM 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.0310-002
(6167) Basic Algorithms - Recitation Sandro Coretti W 3:30-4:45PM 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.0380-001
(6168) Topics of General Interest: Interactive Computing Craig Kapp
Office Hours MW 12:30-1:45PM CIWW 312

In this course students will learn how to develop interactive multimedia applications for both the desktop and the web. The course focuses on general programming techniques with an emphasis on the production of interactive graphical environments. In addition, a number of advanced topics will be covered including image processing, video games, simulations, basic computer vision, augmented reality and creating simple mashups using popular web services such as Flickr and Twitter.

Prerequisites: CSCI-UA.0002 or permission of Instructor.
CSCI-UA.0380-002 Topics of General Interest: Python for Applications CANCELLED -
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.0436-001
(6169) Computer Architecture Allan Gottlieb
Office Hours TR 3:30-4:45PM CIWW 101

The structure and design of computer systems. Basic logic modules and arithmetic circuits. Control unit design and structure of a simple processor; speed-up techniques. Storage technologies and structure of memory hierarchies; error detection and correction. Input/output structures, busses, programmed data transfer, interrupts, DMA, and microprocessors. Discussion of various computer architectures; stack, pipeline, and parallel machines; and multiple functional units. Not offered every academic year.

Prerequisites: <p>Computer Systems Organization (CSCI-UA 201) and Discrete Mathematics (MATH-UA 120).</p>
CSCI-UA.0470-001
(6170) Object Oriented Programming Randy Shepherd
Office Hours MW 2:00-3:15PM CIWW 312

Introduces the important concepts of object-oriented design and languages, including code reuse, data abstraction, inheritance, and dynamic overloading. Covers in depth those features of Java and C++ that support object-oriented programming and gives an overview of other object-oriented languages of interest. Significant programming assignments stressing object-oriented design. Not offered every academic year.

Prerequisites: Computer Systems Organization (CSCI-UA 201).
CSCI-UA.0480-001
(7937) Special Topics: Applied Internet Technology Joseph Versoza
Office Hours TR 9:30-10:45AM CIWW 101

A practical introduction to creating modern web applications. Covers full stack web development - including topics such as database / data model design, MVC architecture, templating, handling user input, asynchronous processing, and client side interactivity. Students will use current server and client side web frameworks to build dynamic, data-driven sites. Various tools to support development will also be introduced, such as version control and build systems. Basic knowledge of HTML and CSS and familiarity with command line tools are recommended.

Prerequisites: CSCI-UA.0201
CSCI-UA.0480-002
(8483) Special Topics: iOS Programming Nathan Hull
Office Hours MW 3:30-4:45PM CIWW 517

In this course, students will learn to create applications for Apple’s iOS on both the iPhone and the iPad using Objective-C, Apple's new programming language Swift, and the iOS SDK.

Since its introduction, the Apple iOS SDK has proved to be a powerful platform upon which to build sophisticated applications. Without actually having to own an iPhone or an iPad, students will be able to build and test their applications on Apple Macs using the freely available compiler and simulator, XCode. Students will become proficient in the object-oriented language Objective-C, Swift, Apple iOS Frameworks, and the XCode development environment. This is a new, dynamic, constantly-evolving topic, and students will be at the forefront a new technological advancement.

Prerequisites: CSCI-UA.0201
CSCI-UA.0480-003
(8219) Special Topics: Principles of Programming Languages Thomas Wies
Office Hours TR 11:00-12:15PM CIWW 512

Computing professionals have to learn new programming languages all the time. This course teaches the fundamental principles of programming languages that enable students to learn new languages quickly and help them decide which one is best suited for a given task. Students will learn new ways of viewing computation and programs, and new ways of approaching algorithmic problems, making them better programmers overall. Topics include recursion and induction, algebraic data types and pattern matching, higher-order functions, continuations and tail recursion, programming language syntax and semantics, type systems, and objects and classes. The course will explore this material by building interpreters for programming languages of increasing complexity. The course will thus be accompanied by extensive programming assignments.

Prerequisites: CSCI-UA.0201
CSCI-UA.0480-004
(8220) Special Topics: Intro to Social Networking Bhubaneswar Mishra
Office Hours TR 2:00-3:15PM CIWW 102

Social Networks is a specific example of many forms of networks that have become ubiquitous in our modern society. Their utilities have been enhanced by their ability to generate massive amount of personal data that need to be analyzed and disseminated quickly. The World Wide Web enables information flows among vast number of humans; Facebook, LinkedIn, 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. This course will introduce the tools, analytics and algorithms for the study of networks and their data. It will show how certain common principles permeate the functioning of these diverse networks: e.g., issues related to robustness, fragility, and interlinkages etc.

Prerequisites: CSCI-UA.0201
CSCI-UA.0480-005
(9167) Special Topics: Large Scale Web Applications Yair Sovran
Office Hours T 6:20-8:50PM Silv 408

This class will examine the challenges of scaling up a data-centric web application to serve millions of users. Students will learn and apply distributed computing concepts as they convert a simple monolithic web service to a scalable distributed architecture, with an emphasis on back-end components. Students will be introduced to the practice of scaling by distribution, and the exercises will have students apply a combination of popular open source technologies and code newly written by them, as they continue to augment the service. Lectures will cover topics such as Data models (Relational Databases vs No-SQL); Data partitioning; Caching; the RPC abstraction and RESTful APIs; distributed data processing pipelines; logging and monitoring; replication; and managed cloud technologies. We will also review existing popular systems that apply these concepts, as case studies. Topics: distributed computing, distributed storage systems, replication and consistency, Open Source technologies.

Prerequisites: CSCI-UA.0201
CSCI-UA.0480-006
(9181) Special Topics: Natural Language Processing Adam Meyers
Office Hours MW 11:00-12:15PM CIWW 101

Natural Language Processing (aka Computational Linguistics) is an inter-disciplinary field applying methodology of computer science and linguistics to the processing of natural languages (English, Chinese, Spanish, Japanese, etc.). Typical applications include: information extraction (automatically finding information from text); information retrieval (web searches and other applications involving the automatic selection of "relevant" documents); sentiment analysis (automatic extraction of opinions about a set of issues); and machine translation (automatically translating one natural language to another). Much of the best work in the field combines two methodologies: (1) automatically acquiring statistical information from one set of "training" documents to use as the basis for probabilistically predicting the distribution of similar information in new documents; and (2) using manually encoded linguistic knowledge. For example, many supervised methods of machine learning require: a corpus of text with manually encoded linguistic knowledge, a set of procedures for acquiring statistical patterns from this data and a transducer for predicting these same distinctions in new text. This class will cover linguistic, statistical and computational aspects of this exciting field.

Prerequisites: CSCI-UA.0201
CSCI-UA.0480-007
(21746) Special Topics: Applied Internet Technology Joseph Versoza
Office Hours MW 3:30-4:45PM CIWW 102

A practical introduction to creating modern web applications. Covers full stack web development - including topics such as database / data model design, MVC architecture, templating, handling user input, asynchronous processing, and client side interactivity. Students will use current server and client side web frameworks to build dynamic, data-driven sites. Various tools to support development will also be introduced, such as version control and build systems. Basic knowledge of HTML and CSS and familiarity with command line tools are recommended.

Prerequisites: CSCI-UA.0201
CSCI-UA.0520-001
(6171) Undergraduate Research Faculty -
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.0897-001
(9201) Internship Faculty -
An internship in computer science is an excellent complement to formal course work. We strongly recommend that students have some practical training along with their classroom experience, so they can explore different career options and gain hands-on experience. An internship is for majors only, and students must have maintained an overall GPA of 3.0 and a computer science GPA of 3.5. The internship will be graded.

Prerequisites: Restricted to declared computer science majors. Internship credit does not count toward major requirements, but does apply toward completion of the CAS degree.
CSCI-UA.0997-001
(6172) Independent Study Faculty -

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.
FRSEM-UA.0597-001
(20660) Problem Solving Dennis Shasha
Office Hours M 2:00-4:30PM Silv 507

Many problems in science, business, and politics require heuristics—problem-solving techniques that often work well but give imperfect guarantees. This course teaches heuristics as they apply to the design of scientific experiments, the resolution of economic or political negotiations, and the construction of engineering devices in hostile environments. Students will work in small teams that will solve puzzles, conduct experiments, and build strategies for a competitive auction game. Students will use and learn computational tools, such as Python. The intent is to make you better able to face complex problems in any field of study you choose.

Prerequisites: Some programming experience in Python, Java, Javascript, R, or C.

*

Indicates controlled enrollment (permission number required for registration). Contact your program advisor.
**

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

Indicates controlled enrollment (permission number required for registration). Contact the instructor.

Classroom Locations

Notice: This webpage is subject to change and will be revised and updated as necessary.