Course Schedule

Current semester Fall 2017, and future semesters are now available to view.

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Number

Name

Professor(s)

Meet Time

Room

CSCI-GA.1120-001
(17296) Introduction to Programming**** Joseph Versoza
Office Hours R 4:55-7:35PM 60 Fifth Ave C10

This course introduces students to the fundamentals of computer programming as students design, write, and debug computer programs using the programming language Python. No knowledge of programming is assumed. Not open to graduate Computer Science, Information Systems, Mathematics or Scientific Computing students. For registration, please contact dhss@nyu.edu.
CSCI-GA.1121-001
(17297) Working with Data**** Deena Engel T 6:20-9:00PM 60 Fifth Ave C10

Students study the principles of relational database design and learn to build, populate, manipulate and query databases using SQL on datasets relevant to their interests. Students will also explore data presentation through data visualization. Not open to Graduate Computer Science, Information Systems, Mathematics or Scientific Computing students. For registration, please contact dhss@nyu.edu.
CSCI-GA.1133-001
(1127) 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
(1612) PAC I Recitation Derek Obrien 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
DS-GA.1170
(1128) 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
DS-GA.1170
(1129) 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
DS-GA.1170
(2277) Fundamental Algorithms Amir Shpilka
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
DS-GA.1170
(2278) Fundamental Algorithms Recitation Siddharth Krishna 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.2110-001
(1130) 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
(1131) Programming Languages Recitation Paul Fisher 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
(1796) Programming Languages Cory Plock
Office Hours M 5:10-7:00PM 60 Fifth Ave C10

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
(1623) Programming Languages Recitation Priyanka Suresh F 5:10-6:00PM 60 Fifth Ave C10

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
(1132) Scientific Computing Leslie Greengard
Office Hours 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
(1133) Compiler Construction CANCELLED -
This is a capstone course based on compilers and modern programming languages. The topics covered include structure of one-pass and multiple-pass compilers; symbol table management; lexical analysis; traditional and automated parsing techniques, including recursive descent and LR parsing; syntax-directed translation and semantic analysis; run-time storage management; intermediate code generation; introduction to optimization; and code generation. The course includes a special compiler-related capstone project, which ties together concepts of algorithms, theory (formal languages), programming languages, software engineering, computer architecture, and other subjects covered in the MS curriculum. This project requires a substantial semester-long programming effort, such as construction of a language compilation or translation system that includes lexical and syntactic analyzers, a type checker, and a code generator.

Prerequisites: CSCI-GA 1170, CSCI-GA 2110, and CSCI-GA 2250.
CSCI-GA.2250-001
(1134) 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
(1636) 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
(1887) Computer Graphics Daniele Panozzo
Office Hours M 7:10-9:00PM 60 Fifth Ave C10

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
(1798) 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
(2098) Advanced Computer Graphics Kenneth Perlin T 7:10-9:00PM 60 Fifth Ave 261

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.2420-001
MATH-GA 2010-001
(1135) 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
DS-GA.2433-001
(1632) Database Systems Zvi Kedem
Office Hours W 5:10-7:00PM CIWW 101
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
(1136) Advanced Database Systems Dennis Shasha
Office Hours T 5:10-7:00PM 60 Fifth Ave 150
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.2566-001
(1799) 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 Inference and Representation 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.2591-001
(17670) Advanced Topics in Natural Language Processing Ralph Grishman
Office Hours M 5:10-7:00PM 60 Fifth Ave C12

The design of systems that can learn by reading. Ontology and knowledge base. Principal processing components: text segmentation, lexical analysis, name recognition and classification, parsing and syntactic regularization, word sense disambiguation, predicate-argument analysis, reference resolution, discourse structure. Joint inference methods. Knowledge acquisition strategies.

This is a project-oriented, team-organized course in which students will take responsibility for one or two processing components: selecting methods, making class presentations, creating and maintaining code. A good working knowledge of corpus-trained methods for these components is required (using log-linear or deep models). Implementation will be in Java, so good programming skills in Java are needed, along with a commitment to meeting javadoc documentation standards.

The tentative target is to read articles from Wikipedia.

Prerequisites: Students should have solid programming skills in Java and should have successfully completed a graduate level course in natural language processing.
CSCI-GA.2945-001
MATH-GA.2011-001
(1137) Adv Topics Num. Analysis: Gaussian elimination, Random functions and random differential equations, Chebyshev series, Rational functions, Quadrature, and ODEs Lloyd N. Trefethen
Office Hours T 1:25-3:15PM CIWW 512
Gaussian elimination, Random functions and random differential equations, Chebyshev series, Rational functions, Quadrature, and ODEs

This six-week course will be structured in an unusual way. Each of our six meetings will be independent. At each meeting, the first hour will be a lecture aimed at anyone interested in numerical analysis at a high level, organized around a well-known topic and mixing historical perspectives, recent developments, and always some new mathematics. The second hour will be for enrolled students only, a hands-on work session making use of Chebfun.
- Lecture 1. Gaussian elimination
- Lecture 2. Random functions and random differential equations
- Lecture 3. Chebyshev series
- Lecture 4. Rational functions
- Lecture 5. Quadrature
- Lecture 6. ODEs
CSCI-GA.2945-002
MATH-GA.2011-002
(2248) Adv Topics Num. Analysis: Integral Equations and Fast Algorithms Michael O'Neil
Office Hours R 1:25-3:15PM CIWW 512

This course will cover many of the standard PDEs from classical mathematical physics, including the Laplace equation, the Helmholtz equation, Maxwell’s equations, Stokes’ equation, and their alternative integral equation formulation. Numerically solving these associated integral equations requires a special set of tools, in particular, quadrature for singular functions and fast algorithms for the resulting dense matrices. Numerical methods for each of these aspects will be presented (e.g. singular quadrature, fast multipole methods, iterative solvers, and fast direct solvers), and open problems in the field will be discussed.
CSCI-GA.2965-001
(1138) Heuristic Problem Solving Dennis Shasha
Office Hours T 7:10-9:00PM 60 Fifth Ave C14
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
(1139) 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
(1140) Special Topics: Distributed Systems Jinyang Li
Office Hours W 7:10-9:00PM CIWW 101

Large-scale distributed systems are the core software infrastructure underlying cloud computing. These systems consist of tens of thousands of networked computers working together to provide unprecedented performance and fault-tolerance. Examples include distributed databases (e.g. Google's Spanner, Amazon's S3 and Dynamo), distributed computation frameworks (e.g. Hadoop/Spark and TensorFlow) or even decentralized currency system (e.g. BitCoin). This class teaches the abstractions, design and implementation techniques that allow you to understand and build such distributed systems.
Topics include multithreading, network programming, consistency, naming, fault tolerance, and security and several case studies of distributed systems.

This class is a graduate-level course, but undergraduate students are welcome! The course consists of lectures and a series of programming labs.

This class satisfies the Ph.D. breadth requirement in Systems and also serves as a M.S. capstone course.

Prerequisites: 1. Undergraduate Operating Systems or Computer Systems Organization; 2. Extensive programming experience
CSCI-GA.3033-003
(1141) Special Topics: Music Software Projects Scott Burton
Office Hours W 7:10-9:00PM 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
(1142) 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. This course serves as a capstone for the MSCS program.
CSCI-GA.3033-006
(1144) 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
(1145) Special Topics: Social Multiplayer Games Yoav Zibin
Office Hours R 5:10-7:00PM 60 Fifth Ave C04

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
(1889) Special Topics: Statistical Natural Language Processing Ankur Parikh
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.
CSCI-GA.3033-011
(2000) 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
(1998) Special Topics: Vision Meets Machine Learning Davi Geiger
Office Hours R 5:10-7:00PM CIWW 201

The course will introduce basic ideas of Multiscale Image Representations (Wavelets - Affine Groups) and Machine Learning (Deep Learning with Variational Auto Encoders, GAN, RNN). Then, the course will be "hands on", with small groups programming/developing projects that integrate the basic ideas above to perform "computer vision tasks" (the evaluation is based on projects). The tasks will be in the topics of Motion, Scene Segmentation, Object Classification, Human Actions.

Prerequisites: Students who take this class should have familiarity with linear algebra, probability, and calculus.
CSCI-GA.3033-014
(2107) Special Topics: DevOps John Rofrano
Office Hours
Nikolai Joukov
Harigovind Ramasamy W 5:10-7:00PM CIWW 102

DevOps is more than just a fusion of development and operations. It is the cultural change that embraces Agile methodology, Lean Manufacturing, Social Coding, Behavior Driven and Test Driven Development, with 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 loosely coupled microservices require DevOps automation to manage the often complex production pipelines. DevOps allows businesses to move with increased agility and stability so that they can innovate at scale.

Upon completing this course students will know from hands-on experience how to work as an Agile team, socially code, and setup a DevOps pipeline to continuously integrate and test their code changes and deploy the 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, Behavior Driven and Test Driven Development, Python Flask, Redis, Cloudant, Ansible, SaltStack, Chef, Puppet. Students will be given access to IBM Bluemix and Watson Services for the duration of the course and will be submitting their homework on GitHub and deploying their homework to Bluemix. This course is 50% lecture and 50% hand-on so come prepared to learn by doing.

Prerequisites: Programming in either Python, Ruby, Java, or other modern OO programming language. The course will be taught using Python.
CSCI-GA.3033-015
(2108) Special Topics: Rapid Prototyping, Lean Engineering & Agile Development CANCELLED -

Topics vary each semester.

Prerequisites: Prerequisites vary according to topic.
CSCI-GA.3033-016
(2305) Special Topics: Big Data and ML Systems Lakshminarayanan Subramanian
Office Hours T 7:10-9:00PM CIWW 101

This class aims to cover introductory and recent concepts in big data and machine learning systems. The class will focus on a broad spectrum of big data computational problems, algorithms and platforms. The class will be centered around several big data case studies in commercial use to understand big data and machine learning tasks across different domains and provide an in-depth understanding of the problems and algorithms used in each domain. From the computational platform perspective, this class covers popular and widely used commercial platforms including Hadoop and Mapreduce variants, Spark, streaming platforms, Tensorflow, ML platforms (MLBase, MxNet) and GPU platforms. The goal of this class is to educate students about the algorithms and systems techniques used to build scalable big data and ML platforms and how these platforms are used in the real world.

This class covers the following broad topics:
a. Cloud Infrastructure Blocks: AWS, Mapreduce, Hadoop, Yarn
b. Big Data Algorithms: searching and indexing large data sets, implementing standard statistical algorithms, similar items, nearest neighbors, graph mining, network analytics, dimensionality reduction
c. Big Data Computation Platforms: Spark, TensorFlow, MLBase, MLib, MxNet, GPU computing
d. Scalable ML Algorithms: Implementing deep learning algorithms, graph and network analytics, scalable vision algorithms, scalable NLP algorithms
e. Domain Specific Applications and Case Studies: vision analytics engines, NLP analytics engines, search and graph analytics
CSCI-GA.3033-017
(2320) Special Topics: Multicore Programming Christopher Mitchell
Office Hours M 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
- Strategies to debug and benchmark multi-threaded programs

Students will be expected to have experience with a programming-intensive course. Students must have previous experience with C++, but no experience writing multi-threaded C++ programs is necessary. The course will include lectures, homework, cumulative labs, a final project, and a midterm and final exam.
CSCI-GA.3033-018
(17298) Special Topics: Big Data Application Development Suzanne McIntosh
Office Hours M 5:10-7:00PM CIWW 201

This course covers Scala, Spark programming, Spark architecture, Spark Streaming, and integration of Spark with the Hadoop ecosystem for developing Big Data applications. In addition, it covers the technologies that integrate well with Spark in the creation of Big Data applications. Students are required to complete weekly reading and/or programming assignments and demonstrate mastery of course topics by developing a final project using Scala, Spark, and complementary Hadoop tools.

Prerequisites: Successful completion of the Realtime and Big Data Analytics course is a prerequisite for registering for this course. In addition, students should have: strong programming skills in Java, Python, or C++; experience using Hadoop; coursework in operating systems, networking, and algorithms; familiarity with Linux commands.
CSCI-GA.3033-019
(17299) Special Topics: Cryptocurrencies and Decentralized Ledgers Joseph Bonneau
Office Hours T 7:10-9:00PM 60 Fifth Ave 150

Bitcoin, Ethereum, and other systems using decentralized ledgers (blockchains) have quickly grown to valuations of tens of billions of dollars. Their future potential has captured the imagination of researchers working on applications as diverse as banking and finance, voting, law, corporate governance, gambling and online gaming. This course will cover the technical concepts underlying these systems: append-only ledgers, decentralized consensus, smart contracts and zero-knowledge proof systems. Students will gain working knowledge of both Bitcoin and Ethereum through practical assignments. The course will also survey the wide variety of potential future applications.

Prerequisites: At least one year of experience with a high-level language such as Pascal, C, C++, or Java. An undergraduate course in cryptography or successful completion of CSCI-GA.3205 or CSCI-GA.3210 strongly recommended.
CSCI-GA.3033-020
(17300) Special Topics: Practical Computer Security Thitima Srivatanakul
Office Hours W 7:10-9:00PM CIWW 317

This course teaches the security mindset and practical security concepts that are essential for software engineers, software developers, quality assurance testers and IT managers. The course discusses various attack techniques and defenses for real world applications and the security activities in the SDLC. Its main topics include: low-level exploits, web application security, malware, threat modeling, security requirements, secure coding practices, security & penetration testing, human factors and usability, mobile platform security, economics of security and legal and ethical issues. Course project and assignments may require Java, C, and/or scripting languages.

Prerequisites: Programming experience in C/C++ and Java; basic knowledge of command line UNIX tools; working knowledge of web application development.
CSCI-GA.3110-001
(18812) Honors Programming Languages Patrick Cousot
Office Hours TR 3:30-4:45PM 60 Fifth Ave C15
The course will introduce a panorama of programming languages concepts underlying the main programming language paradigms (such as imperative, functional, object-oriented, logic, concurrent, and scripting languages) and present in detail the formal methods (code semantics, specification, and verification) used in modern high quality assurance tools for software safety and security. A programming project (design and implementation of an interpreter/compiler for an dynamic object-oriented mini-language) will be programmed in OCaml, a multiparadigm language introduced at the beginning of the course.

Prerequisites: Permission of the instructor for master’s students
CSCI-GA.3210-001
MATH-GA 2170-001
(1652) 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.3520-001
(1146) 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
(1147) 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.3813-001
(1148) 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.3813-002
(1149) 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
(1150) 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
(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.3813-005
(1152) 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
(1153) 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
(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.3813-008
(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.3840-001
(1156) 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
(1157) PhD Seminar: Cryptography** CANCELLED -
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
(1158) PhD Seminar: Formal Methods** Thomas Wies
Office Hours R 11:00-12:30PM 60 Fifth Ave 446
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
(1801) 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
(1159) PhD Thesis Research ** STAFF -

Prerequisites: Permission of the thesis adviser or director of graduate studies for the Ph.D. program.
CSCI-GA.3870-001
(2176) Internship In Computer Science MS* STAFF -

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
(2177) Internship in Computer Science PhD* STAFF -

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
(8921) 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
(8922) Quantitative Reasoning: RECITATION Scott Floam 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
(6161) Intro To Computer Programming Nathan Hull
Office Hours TR 12:30-1:45PM 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.0002-002
(6162) Intro To Computer Programming Craig Kapp
Office Hours TR 11:00-12:15PM 60 Fifth Ave 150

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
(6163) Intro To Computer Programming David Gochfeld
Office Hours MW 3:30-4:45PM CIWW 102

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

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

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
(6165) Intro To Computer Programming Craig Kapp
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
(6166) Intro To Computer Programming Amos Bloomberg
Office Hours TR 9:30-10:45AM 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.0002-007
(6167) Intro To Computer Programming Adam Meyers
Office Hours MW 8:00-9:15AM 60 Fifth Ave 150

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
(7773) Intro To Computer Programming Joshua Clayton
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
(7775) Intro To Computer Programming Jerry Waxman
Office Hours TR 3:30-4:45PM CIWW 517

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

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

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
(8080) Intro To Computer Programming Adam Meyers
Office Hours MW 11:00-12:15PM 60 Fifth Ave 110

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
(8522) Intro To Computer Programming Michell Cardona
Office Hours TR 8:00-9:15AM 60 Fifth Ave 110

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
(6168) Intro to Web Design & Computer Principles Joshua Clayton
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
(6169) Intro to Web Design & Computer Principles Alvaro Olsen
Office Hours TR 12:30-1:45PM 60 Fifth Ave 110
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
(6170) Intro to Web Design & Computer Principles Lee-Sean Huang
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
(6171) Intro to Web Design & Computer Principles Jason Aston
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
(7595) 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
(7774) 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
(7974) Intro to Web Design & Computer Principles Adam Scher
Office Hours TR 8:00-9:15AM CIWW 101
Introduces students to both the practice of web design and the basic principles of computer science. The practice component covers not only web design but also current graphics and software tools. The principles section includes an overview of hardware and software, the history of computers, and a discussion of the impact of computers and the Internet.

Prerequisites: Three years of high school mathematics or equivalent. No prior computing experience is assumed. Students with computing experience should consult with the department before registering.
CSCI-UA.0060-001
(7809) Database Design And Web Implementation Deena Engel MW 11:00-12:15PM 60 Fifth Ave 150

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
(6172) Web Development And Programming Sana Odeh MW 3:30-4:45PM 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
(8240) Web Development And Programming Sana Odeh TR 3:30-4:45PM CIWW 512

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
(6173) Intro To Computer Science Anasse Bari
Office Hours TR 9:30-10:45AM 60 Fifth Ave 110

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
(6174) Intro To Computer Science Amos Bloomberg
Office Hours TR 11:00-12:15PM 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.0101-003
(6175) Intro To Computer Science Anasse Bari
Office Hours TR 3:30-4:45PM CIWW 102

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

Prerequisites: Introduction to Computer Programming (No Prior Experience) (CSCI-UA 2) or Introduction to Computer Programming (Limited Prior Experience) (CSCI-UA 3), or a score of 3 on the AP Computer Science exam (scores of 4 and 5 are acceptable prerequisites for students who wish to take CSCI-UA 101 before entering CSCI-UA 102; they will forfeit the AP credit), or departmental permission assessed by placement exam.
CSCI-UA.0101-004
(6176) Intro To Computer Science Amos Bloomberg
Office Hours MW 3:30-4:45PM 60 Fifth Ave 150

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
(7639) Intro To Computer Science Suzanne McIntosh
Office Hours MW 11:00-12:15PM CIWW 312

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
(7801) Intro To Computer Science Douglas Moody
Office Hours MW 9:30-10:45AM 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.0101-007
(7977) Intro To Computer Science Candido Cabo
Office Hours MW 12:30-1:45PM 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.0101-008
(8965) Intro To Computer Science Brett Peterson
Office Hours TR 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.0101-009 Intro To Computer Science CANCELLED -

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
(6177) Data Structures Ernest Davis
Office Hours MW 9:30-10:45AM 60 Fifth Ave 150

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
(6178) Data Structures - Recitation Yi-Hsiang (Joe) Kao F 2:00-3:15PM 60 Fifth Ave 150

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
(6179) 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
(6180) Data Structures - Recitation Neha Sharma 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.0102-005
(6181) 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
(8050) Data Structures - Recitation John Ortega T 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
(8508) Data Structures Evan Korth
Office Hours TR 9:30-10:45AM 60 Fifth Ave 150

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
(8509) Data Structures - Recitation Nolan Filter W 12:30-1:45PM 60 Fifth Ave 150

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
(6182) 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
(6183) Computer Systems Organization - Recitation Shuai Mu W 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
(7802) Computer Systems Organization Mohamed Zahran
Office Hours TR 3:30-4:45PM 60 Fifth Ave 150

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
(8712) Computer Systems Organization - Recitation Shuai Mu W 12:30-1:45PM 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
(8713) Computer Systems Organization Zhaoguo Wang
Office Hours MW 3:30-4:45PM 60 Fifth Ave C12

This section is a fast paced version of the regular CSO class. Students who are considering research in their senior year or graduate school should take this class.

This course aims to give students an understanding of what's "under the hood" in a modern computer system. Take this class to boost your confidence on a computer and to understand how everything works like never before! We'll cover basic topics including how machines represent and execute programs, how user program interact with the OS, as well as advanced topics including how to write networked and concurrent programs. These topics are supported by a series of challenging lab assignments in C.

Prerequisites: You need to be comfortable with programming (e.g. in Java) and the UNIX environment.
CSCI-UA.0201-006
(8714) Computer Systems Organization - Recitation Chien-chin Huang R 12:30-1:45PM 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.0202-001
(6184) 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.0202-002
(18602) Operating Systems Yan Shvartzshnaider
Office Hours TR 2:00-3:15PM 60 Fifth Ave 110

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
(6185) Basic Algorithms Zvi Kedem
Office Hours MW 11:00-12:15PM CIWW 109

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

Prerequisites: Data Structures (CSCI-UA 102); Discrete Mathematics (MATH-UA 120); and either Calculus I (MATH-UA 121) OR Mathematics for Economics I (MATH-UA 211).
CSCI-UA.0310-002
(6186) Basic Algorithms - Recitation Isaac Henrion F 11:00-12:15PM 19W4 101

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

Prerequisites: Data Structures (CSCI-UA 102); Discrete Mathematics (MATH-UA 120); and either Calculus I (MATH-UA 121) OR Mathematics for Economics I (MATH-UA 211).
CSCI-UA.0310-003
(18599) Basic Algorithms Victor Shoup
Office Hours TR 3:30-4:45PM 60 Fifth Ave 110

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.0310-004
(18600) Basic Algorithms - Recitation Abhinav Tamaskar F 12:30-1:45PM 60 Fifth Ave 150

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.0310-005
(22082) Basic Algorithms Gleb Pogudin
Office Hours MW 11:00-12:15PM CIWW 102

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.0310-006
(22083) Basic Algorithms - Recitation Ojas Deshpande F 12:30-1:45PM CIWW 101

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
(6187) 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: Intro To Computer Programming (CSCI-UA 2) and Intro to Web Design & Computer Principles (CSCI-UA 4), or permission of Instructor
CSCI-UA.0436-001
(6188) 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
(6189) Object Oriented Programming Thomas Wies
Office Hours MW 2:00-3:15PM Silv 206

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 Special Topics: TBA CANCELLED -

An introduction to the field of computer vision. Basic concepts will be covered such as edge detection, stereo vision, motion, color, texture and recognition.

Prerequisites: Computer Systems Organization (CSCI-UA 201)
CSCI-UA.0480-002
(8243) 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 iPhone 3G using Objective-C and the iPhone SDK. Since its introduction this past summer, the Apple SDK has been revealed to be a powerful platform upon which to build sophisticated applications for the iPhone. Without actually having to own an iPhone, students will be able to build and test their applications on Intel Apple Macs using the freely available compiler and simulator. In addition to the development tools, students will become proficient in the object-oriented language Objective-C, the Apple iPhone Framework, and the principles of Cocoa development. This is a new, dynamic, constantly-evolving topic, and students will be at the forefront of a new technological advancement.

Prerequisites: CSCI-UA.0201
CSCI-UA.0480-003
(8051) Special Topics: Applied Internet Technology Joseph Versoza
Office Hours TR 11:00-12:15PM 60 Fifth Ave 110

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.0480-004
(8052) Special Topics: Intro to Social Networking Bhubaneswar Mishra
Office Hours TR 2:00-3:15PM CIWW 1302

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
(8505) Special Topics: Large Scale Web Applications Yair Sovran
Office Hours T 6:20-8:50PM Silv 401

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
(8513) Special Topics: Natural Language Processing Adam Meyers
Office Hours TR 8:00-9:15AM 60 Fifth Ave C10

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
(9171) Special Topics: Applied Internet Technology Joseph Versoza
Office Hours MW 3:30-4:45PM CIWW 109

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.0480-008
(18603) Special Topics: Computer Graphics Jeremie Dumas
Office Hours TR 9:30-10:45AM CIWW 202

This course provides an introduction to the field of Computer Graphics. The course will cover the basic mathematical concepts, study the interaction of light with geometry, and implement basic rendering algorithms such as ray tracing and rasterization. At the end of the semester, students will have built their own raytracer, and developed a real-time 3D computer graphics system using the OpenGL 4 graphics API.

Prerequisites: CSCI-UA 201 Computer Systems Organization, CSCI-UA-310 (Basic Algorithms) and MATH-UA-140 (Linear Algebra), or departmental consent.
CSCI-UA.0480-009
(24518) Special Topics: Computer Networks Anirudh Sivaraman
Office Hours MW 12:30-1:45PM 60 Fifth Ave C15

This course will introduce students to computer networks, using today's Internet as an example. Topics covered include socket programming, routing, forwarding, reliable transmission, congestion control, and medium access control. The course will involve a reasonable amount of programming in Python, and familiarity with programming is expected.

Prerequisites: Computer Systems Organization (CSCI-UA 201) and Basic Algorithms (CSCI-UA.0310) or permission of the department
CSCI-UA.0520-001 Undergraduate Research N/A -
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 Internship N/A -
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 Independent Study N/A -

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
(9075) 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.