Course Schedule

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

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Number

Name

Professor(s)

Meet Time

Room

CSCI-GA.1144-001
(2254) PAC II* Mohamed Zahran
Office Hours T 6:00-8:30PM CIWW 312

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

Prerequisites: CSCI-GA 1133 or departmental permission.
CSCI-GA.1144-002
(2763) PAC II Recitation Scott Buckfelder R 7:10-8:00PM CIWW 312

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

Prerequisites: CSCI-GA 1133 or departmental permission.
CSCI-GA.1170-001
(2255) Fundamental Algorithms Joel Spencer
Office Hours M 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
(2256) Fundamental Algorithms Recitation Ojas Deshpande
Office Hours R 8:10-9:00PM 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
(23572) Fundamental Algorithms Recitation Vladimir Kobzar
Office Hours F 5:10-6:00PM CIWW 312

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
(2257) Programming Languages Benjamin Goldberg
Office Hours W 7:10-9:00PM 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
(2258) Programming Languages Recitation Paul Fisher
Office Hours R 7:10-8:00PM 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.2130-001
(2259) Compiler Construction Eva Rose
Office Hours
Alexander Alekseyev M 7:10-9:00PM CIWW 202
This is a capstone course based on compilers and modern programming languages. The topics covered include structure of one-pass and multiple-pass compilers; symbol table management; lexical analysis; traditional and automated parsing techniques, including recursive descent and LR parsing; syntax-directed translation and semantic analysis; run-time storage management; intermediate code generation; introduction to optimization; and code generation. The course includes a special compiler-related capstone project, which ties together concepts of algorithms, theory (formal languages), programming languages, software engineering, computer architecture, and other subjects covered in the MS curriculum. This project requires a substantial semester-long programming effort, such as construction of a language compilation or translation system that includes lexical and syntactic analyzers, a type checker, and a code generator.

Prerequisites: CSCI-GA 1170, CSCI-GA 2110, and CSCI-GA 2250.
CSCI-GA.2246-001
(19194) Open Source Tools Jeffrey Korn
Office Hours M 7:10-9:00PM 60 Fifth Ave C12
This course covers a brief history and philosophy of open source software, followed by an in-depth look at open source tools intended for developers. In particular, we will present an overview of the Linux operating system, command line tools (find, grep, sed), programming tools (GIT, Eclipse, DTrace), web and database tools (Apache, MySQL), and system administration tools. We will also cover scripting languages such as shell and Python.

Prerequisites: An understanding of modern operating systems and a working knowledge of a programming language, such as C, C++ or Java
CSCI-GA.2250-001
(2260) Operating Systems Hubertus Franke
Office Hours M 7:10-9:00PM CIWW 109
The topics covered include a review of linkers and loaders and the high-level design of key operating systems concepts such as process scheduling and synchronization; deadlocks and their prevention; memory management, including (demand) paging and segmentation; and I/O and file systems, with examples from Unix/Linux and Windows. Programming assignments may require C, C++, Java, or C#.
CSCI-GA.2250-002
(3147) Operating Systems Allan Gottlieb
Office Hours R 5:10-7:00PM CIWW 109
The topics covered include a review of linkers and loaders and the high-level design of key operating systems concepts such as process scheduling and synchronization; deadlocks and their prevention; memory management, including (demand) paging and segmentation; and I/O and file systems, with examples from Unix/Linux and Windows. Programming assignments may require C, C++, Java, or C#.
CSCI-GA.2262-001
(2261) Data Communications and Networks Jean-Claude Franchitti
Office Hours R 5:10-7:00PM CIWW 101

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.2421-001
MATH-GA 2020-001
(2262) Numerical Methods II Leslie Greengard
Office Hours T 5:10-7:00PM CIWW 202

This course will cover fundamental methods that are essential for the numerical solution of differential equations. It is intended for students familiar with ODE and PDE and interested in numerical computing; computer programming assignments form an essential part of the course. The course will introduce students to numerical methods for (1) nonlinear equations, Newton's method; (2) ordinary differential equations, Runge-Kutta and multistep methods, convergence and stability; (3) finite difference, finite element and integral equation methods for elliptic partial differential equations; (4) fast solvers, multigrid methods; and (5) parabolic and hyperbolic partial differential equations.

Text: LeVeque, R. (2007). Classics in Applied Mathematics [Series]. Finite Difference Methods for Ordinary and Partial Differential Equations. Philadelphia, PA: Society for Industrial and Applied Mathematics

Prerequisites: Numerical linear algebra, elements of ODE and PDE.
CSCI-GA.2433-001
(2263) Database Systems Zvi Kedem
Office Hours T 7:10-9:00PM 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.2440-001
(2264) Software Engineering Jean-Claude Franchitti
Office Hours M 7:10-9:00PM CIWW 312
This is a capstone course focusing on large-scale software development. This course presents modern software engineering techniques and examines the software life cycle, including software specification, design, implementation, testing, and maintenance. Object-oriented design methods are also considered. Software engineering projects involve creation of a large-scale software system and require some or all of the following elements: formation of a small team, project proposal, literature review, interim report, project presentation, and final report.

Prerequisites: CSCI-GA 1170, CSCI-GA 2110, and CSCI-GA 2250
CSCI-GA.2520-001
BIOL-GA 1127-001
(2265) Bioinformatics and Genomes Richard Bonneau F 1:00-3:45PM Silv 411
The recent explosion in the availability of genome-wide data such as whole genome sequences and microarray data led to a vast increase in bioinformatics research and tool development. Bioinformatics is becoming a cornerstone for modern biology, especially in fields such as genomics. It is thus crucial to understand the basic ideas and to learn fundamental bioinformatics techniques. The emphasis of this course is on developing not only an understanding of existing tools but also the programming and statistics skills that allow students to solve new problems in a creative way.
CSCI-GA.2580-001
(2983) Web Search Engines Ernest Davis
Office Hours M 5:10-7:00PM CIWW 102

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

Prerequisites: Recommend CSCI-GA 1180.
CSCI-GA.2590-001
(2764) Natural Language Processing Ralph Grishman
Office Hours T 5:10-7:00PM 60 Fifth Ave 110

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

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

Prerequisites: Some facility with Java and Python and a knowledge of the elements of probability and statistics is expected.
CSCI-GA.2620-001
(2817) Networks and Mobile Systems Lakshminarayanan Subramanian
Office Hours R 7:10-9:00PM 60 Fifth Ave C10

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

Prerequisites: CSCI-GA 1170, CSCI-GA 2110, and CSCI-GA 2250.
CSCI-GA.2945-001
MATH-GA.2012-001
(2266) Adv Topics Num. Analysis: High Performance Computing Georg Stadler
Office Hours R 5:10-7:00PM CIWW 512
This class will be an introduction to the fundamentals of parallel scientific computing. We will establish a basic understanding of modern computer architectures (CPUs and accelerators, memory hierarchies, interconnects) and of parallel approaches to using and programming these machines (distributed and shared memory parallelism: MPI, OpenMP, OpenCL). Issues such as load balancing, communication, and synchronization will be covered and illustrated in the context of parallel numerical algorithms. Since a prerequisite for good parallel performance is good serial performance, this aspect will also be addressed. Along the way you will be exposed to important tools for high performance computing such as debuggers, schedulers, visualization, and version control systems.

This will be a hands-on class, with several computing homework assignments, in which you will explore material by yourself and try things out. There will be a larger final project at the end. Students who have code they want to parallelize or speed up are encouraged to attend, and use that for their final project.

Text: Besides various online resources, we will use:
- "Parallel Programming for Multicore and Cluster Systems" by T. Rauber and G. Ruenger, Springer, 2nd edition (2013). Available online in the institute.
Prerequisites: (serial) programming experience with C/C++ (I will use C in class) or FORTRAN, basic knowledge of command line UNIX tools, and some familiarity with numerical methods.
CSCI-GA.2945-002
MATH-GA.2012-002
(2267) Adv Topics Num. Analysis: Monte Carlo Jonathan Goodman
Office Hours M 5:10-7:00PM CIWW 317

First half: An introduction to practical Monte Carlo methods, with some of the basic theory, with applications to statistical physics and chemistry, and to Bayesian statistics. Pseudo random number generators. Direct sampling methods, including mappings and rejection. Markov chain Monte Carlo (MCMC), Metropolis Hastings, detailed balance, partial resampling/heat bath. Basic MCMC theory, including Perron Frobenius and the ergodic theorem, the Markov chain central limit theorem, and the Kubo formula for auto-correlation time. Methods for estimating the auto-correlation time and estimating error bars for MCMC results.

Second half: More specialized topics depending on the interests and background of students in the class. Topics may include (a) advanced samplers: Hamiltonian samplers, affine invariant ensemble samplers, multi-level methods, adaptive samplers, (b) thermodynamic integration, (c) Bayesian model selection, (d) rare event simulation, (e) stochastic differential equations, (f) more theory: spectral gap, Poincare and Cheeger inequalities.

Assignments will include significant programming in Python as well as theoretical exercises. Assignments will emphasize elements of programming methodology relevant to Monte Carlo methods, including verification protocols and visualization methods. There will be a long term project done individually or in small groups.

Prerequisites: Students must have a good upper level undergraduate math background including linear algebra, probability, and multi-variate calculus. Course work in numerical computation is desirable. Students should be able to do numerical programming in Python, C/C++, Java, Fortran, R, or Matlab. Students without experience in Python will have to put in some extra effort in the first few weeks.
CSCI-GA.3033-001
(2268) Special Topics: Big Data Science Anasse Bari
Office Hours W 7:10-9:00PM 60 Fifth Ave C10

Data Science has recently gained a substantial interest in a variety of industries including healthcare, finance, manufacturing and marketing. It is positioned at the intersection point of computer science, data mining, machine learning, predictive analytics, business, statistics and domain expertise. It aims at finding hidden knowledge (patterns, models, associations) for the purpose of making better decisions. This course will introduce the basic fundamental concepts of the algorithms and the tools of extracting valuable insights from data with the ability to formulating and solving problems with it. Topics of this course include, but are not limited to: Basics of Data Analytics Project Lifecycle, Developing an Analytics Roadmap, Data Preprocessing, Data Analytics Use cases, Data Cleaning Algorithms, Feature Selection Algorithms, Introduction to Hadoop in Theory and in Practice, Algorithms for Finding Similar Data Items, Dimensionality Reduction techniques, Clustering Algorithms, Classification Algorithms, Introduction to Sentiment Analysis in short text (e.g Tweets), Mining Association Rules, Performance Measures, Ensemble Methods, Information retrieval systems and Recommendation Systems with applications in Bio-informatics, Text Mining and Social Network Analytics. This course will be complemented with hands-on experience of using data analytics tools that are widely used in the industry such as R, Weka, RapidMiner and others.
CSCI-GA.3033-002
(2886) Special Topics: Social Networks Bhubaneswar Mishra
Office Hours T 7:10-9:00PM CIWW 201

Social Networks is a specific example of many forms of networks that have become ubiquitous in our modern society. The World Wide Web enables information flows among vast number of humans; Facebook, Orkut, Friendster, diaspora, etc. connect small groups of friends; amazon, eBay, etc. provide opportunities for trading, etc. These networks determine our information, influence our opinions, and shape our political attitudes. They also link us, often through important but weak ties, to other humans. Their origin is biological: going back to quorumsensing, swarming, flocking, social grooming, gossip, etc. Yet, as we have connected our social networks to traditional human institutions (markets, justice systems, education, etc.) through new technologies, the underlying biology has become obscured, but not dormant. Economic markets also look much more like networks than anonymous marketplaces. Firms interact with the suppliers and customers in a Web-like supply chains. Systemic risk in financial markets often results from the counterparty risks created within this financial network. This course will introduce the tools for the study of networks. It will show how certain common principles permeate the functioning of these diverse networks: e.g., issues related to robustness, fragility, and interlinkages etc.

Prerequisites: Discrete math and linear algebra
CSCI-GA.3033-003
(2269) 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.3033-004
(2270) Special Topics: Social Multiplayer Games Yoav Zibin
Office Hours T 5:10-7:00PM 60 Fifth Ave C10

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.3033-005
(2271) Special Topics: Realtime & Big Data Analytics Suzanne McIntosh
Office Hours R 7:10-9:00PM CIWW 101

This course will introduce technologies and architectures at the foundation of the Big Data movement. These technologies facilitate the scalable storage, management, and processing of vast quantities of data. We will explore the tools enabling the acquisition of near realtime data in the social domain and the fusion of those data when in flight and at rest. 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.3033-006
(19195) Special Topics: Search Engine Architecture Matthew Doherty
Office Hours W 5:10-7:00PM CIWW 1302

A new class of system architectures is needed to address the challenges posed by massively data-intensive problems. The goal of this course is to develop a fast, highly-scalable and highly-available search engine. We will combine elements of information retrieval, natural language processing, machine learning and distributed systems with a focus on practical implementation. While web search will be addressed specifically, we will see that the principles studied in this course are common to a variety of data-intensive applications.

Prerequisites: CSCI-GA 1170 Fundamental Algorithms, CSCI-GA 2110 Programming Languages, CSCI-GA 2250 Operating Systems, and working knowledge of Python.
CSCI-GA.3033-007
(2984) Special Topics: Advanced Machine Learning Mehryar Mohri
Office Hours T 5:10-7:00PM CIWW 101

This course introduces and discusses advanced topics in machine learning. The objective is both to present some key topics not covered by basic graduate ML classes such as Foundations of Machine Learning, and to bring up advanced learning problems that can serve as an initiation to research or to the development of new techniques relevant to applications.
CSCI-GA.3033-008
(2908) Special Topics: .Net Web Application Development Cory Plock
Office Hours M 5:10-7:00PM 60 Fifth Ave C10

This course introduces the concepts and tools necessary for building robust web applications using the Microsoft .NET Framework. Among the topics explored will be the multi-language .NET architecture, build and deployment process, the C# programming language, Entity Framework, Model-View-Controller (MVC) design pattern, web services, Git version control, and the Azure cloud platform. This is a hands-on project-based course where students will build a fully functional web solution.

Prerequisites: Programming languages, object-oriented programming, relational databases, and data structures.
CSCI-GA.3033-010
(19197) Special Topics: Cloud Computing Jean-Claude Franchitti
Office Hours R 7:10-9:00PM CIWW 102

This course provides a hands-on comprehensive study of Cloud concepts and capabilities across the various Cloud service models including Infrastructure as a Service (IaaS), Platform as a Service (PaaS), Software as a Service (SaaS), and Business Process as a Service (BPaaS).

The IaaS topics start with a detailed study of the evolution of infrastructure migration approaches from VMWare/Xen/KVM virtualization, to adaptive virtualization, and Cloud Computing / on-demand resources provisioning. Mainstream Cloud infrastructure services and related vendor solutions are also covered in detail.

The PaaS topics cover a broad range of Cloud vendor platforms including AWS, Red Hat's OpenShift, Cloud Foundry, Apache Stratos, Microsoft Azure, Eucalyptus, OpenStack and others as well as a detailed study of related platform services such as storage capabilities that leverage Google Storage, Amazon S3, Amazon Dynamo, or other facilities meant to provide Cloud resources management and monitoring capabilities.

The course will focus in particular on mainstream Application Platform as a Service (aPaaS), which is a PaaS offering that leverages container services (e.g., Docker) and microservices architectures aimed at facilitating application development, deployment and execution in the cloud. In addition to encapsulating infrastructure resources, aPaaSs include services such as those for data management (including NoSQL and in-memory data services), BPM and decision-engine services, API Management for hybrid integration, and user interfaces. As an example, Cloud foundation offerings provided on top of modern aPaaS such as IBM's Bluemix Liberty for Java include a collection of Watson analytics, big data, mobile, security, IoT, integration, DevOps, Blockchain, as well as other functionality. Additional aPaaS platforms of interest include Google App Engine, Microsoft Azure App Service, Oracle aPaaS,
Red Hat OpenShift, Salesforce App Cloud, and SAP Hana Cloud Platform (HCP).

The SaaS and aPaaS/PaaS topics covered in the course will familiarize students with the use of vendor-maintained applications and processes available on the Cloud on a metered on-demand basis in multi-tenant environments.

Through hands-on assignments and projects, students will learn how to configure and program IaaS services. They will also learn how to develop Cloud-based software applications on top of various Cloud platforms, how to integrate application-level services built on heterogeneous Cloud platforms, and how to leverage SaaS, aPaaS, and BPaaS solutions to build comprehensive end-to-end business solutions on the Cloud.

Prerequisites: Some programming experience in mainstream languages such as Java, Python, C#, or C++.
CSCI-GA.3033-011
(3113) Special Topics: Rigorous Software Development CANCELLED -

Software is increasingly pervading our lives and is now routinely deployed in safety and security critical systems. While this technological progress benefits society greatly, it also creates a new threat: software errors with severe consequences including health hazards, financial repercussions, and security vulnerabilities. How can one ensure that software works reliably? Program Verification studies mathematical methods to answer this question. In the last decade, sophisticated verification tools have been developed that assist software engineers in building reliable software. In this course, we will explore these tools. We will learn how they are used to enable rigorous software development, and we will study the algorithms that work under their hoods. The course will be accompanied by programming projects making use of these tools and that implement some of their core algorithms.
CSCI-GA.3033-013
(19198) Special Topics: DevOps John Rofrano
Office Hours W 7:10-9:00PM CIWW 317

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.3033-016
(19201) Special Topics: Virtual Machines: Concepts and Applications Mohamed Zahran
Office Hours W 5:10-7:00PM CIWW 312

Virtualization technology from VMware, IBM, Xen, Microsoft, and others is an indication of the importance of this technology, especially in this era where almost everything is in the cloud. Virtualization became the IT world's hottest trend in recent years. Have you ever wondered how you can run multiple operating systems on a single physical system and share the underlying hardware resources? How does your operating system see a hardware that differs from the actual hardware, and why do we need to do so? What is a virtual server? Virtual machine is the answer to all that and much more. In this course we will study the design and implementation of virtual machines, virtual machine monitors (aka hypervisors), as well other recent trends in virtualization. We will study virtual machines across the disciplines that use them: operating systems, programming languages, and computer architecture.

Prerequisites: Operating Systems CSCI-GA.2250
CSCI-GA.3033-017
(19315) Special Topics: Abstract Interpretation Patrick Cousot
Office Hours M 5:10-7:00PM 60 Fifth Ave C12
Modern societies are increasingly dependent upon the proper functioning of computer systems. Hardware and software safety and security is critical in many applications of computer science (for example in cyber-physical systems such as avionics, medical devices, automotive/transportation, but also in enterprise and service software such as accounting, banking, trading, social networking, etc.).

Yet, computer programs are riddled with flaws that at best are inconvenient and annoying, and at worst, have extremely damaging consequences. The Heartbleed buffer over-read security bug in the open-source OpenSSL cryptography library is a recent example among thousands of other less advertised ones.

This situation is specific to computer science since in other engineering disciplines engineers are penally responsible for there errors while programmers are not, and so no computer scientist is compelled to use best practices. A direct consequence is the use of cheap and ineffective practices such as debugging. "Program testing can be used very effectively to show the presence of bugs but never to show their absence" (E. W. Dijkstra).

In software and hardware engineering, formal methods aim at using the rigor of mathematics for the specification, development, and verification of reliable and robust software and hardware systems. Formal methods are now part of the academic and industry standards as shown for example by the DO-178 C primary document for certifying all commercial software-based aerospace systems. In particular, the DO-333 supplement to the DO-178 C discusses the use of sound formal methods as part of a software life cycle. So a firm foundation in formal methods are now an integral part of the core knowledge of every high-level professional computer scientist.

The ultimate objective of formal methods is to verify the correctness of computer systems and to have this verification completely automated, using computers. This objective is hard to achieve because of undecidability: no computer can correctly answer with finite time and memory resources every question relative to the correctness of an arbitrary computer system. Therefore all automated formal methods have to make compromises to escape this inevitable limitation of the power (including any form of "intelligence") of computer systems.

All automated formal methods must provide answers in finite time on undecidable questions and so have limitations:
- Automated theorem proving requires human guidance and assistance, which may be an overwhelming task;
- Model-checking can only enumerate the behaviors of finite systems, and small enough to avoid time and memory explosion;
- Static program analysis may be unsound or not be precise enough to answer the desired questions.
A consequence of undecidability is that all automated formal verification methods will fail on infinitely many programs. Fortunately, automated formal verification methods will also succeed on infinitely many programs. By succeed, we mean that if a question about a program is answered then this answer can definitely be trusted. Not all formal methods can be trusted. For example program simulation, symbolic execution, or bounded model checking may be good at finding bugs but they are not sound formal verification methods.

It is therefore necessary to study formal methods not only as a recipe to get correct programs but also from a mathematical point of view to understand their respective principles. This is the role of abstract interpretation. Abstract interpretation originated from the need to formalize the soundness and generalize dataflow analysis and typing performed by compilers into fully automated program verification (and is often limited to this understanding). It turned out that the principles recognized by abstract interpretation where able to establish the foundations of all formal methods (preferably sound, but also to study the origin of unsoundness in incorrect ones).

The general idea is that to state anything formal on a computer system, it is necessary to rigorously define its semantics that is a model of all its possible behaviors in any possible execution environment. Then reasoning on the computer system is done on an abstraction of the properties of this semantics, which has to be derived, often by calculational design, from the semantics. Most often an inductive reasoning is needed, and possible thanks to abstract induction. So the study of formal methods amounts to the study of the abstractions that they are built upon. Examples of applications of the theory of abstract interpretation involve SMT solvers ¹, proof methods ², and static analysers ³;

The course will put an emphasis on the use of abstract interpretation to design proof methods and static analyzers, which now become part of the practice of companies developing huge softare (like Facebook, Google, Microsoft, Spotify, Uber, etc, see for example CodeContracts or Infer).
CSCI-GA.3033-018
(19316) Special Topics: Geometric Modeling Daniele Panozzo
Office Hours R 5:10-7:00PM 60 Fifth Ave C10

Recent advances in 3D digital geometry processing have created a plenitude of novel concepts for the mathematical representation and interactive manipulation of geometric models. This course covers some of the latest developments in geometric modeling and digital geometry processing. Topics include surface modeling based on polygonal meshes, surface reconstruction, mesh improvement, mesh parametrization, discrete differential geometry, interactive shape editing, skinning animation, architectural and structure-aware geometric modeling, shape modeling with an eye on 3D printing. The students will learn how to design, program and analyze algorithms and systems for interactive 3D shape modeling and digital geometry processing.

Prerequisites: Basic knowledge of Computer Graphics, experience with C++ programming. Some background in geometric computing is helpful, but not necessary.
CSCI-GA.3033-019
(19317) Special Topics: Practical Computer Security Thitima Srivatanakul
Office Hours R 5:10-7:00PM CIWW 202

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. Its main topics include: security policy and management, requirements for secure software, security analysis, secure programming techniques, human factors and usability, e-commerce security, mobile platform security, economics of security and legal and ethical issues. Course project and assignments may require Java, C#, and/or scripting languages.

Prerequisites: CSCI-GA 1170, CSCI-GA 2110, and CSCI-GA 2250
CSCI-GA.3033-020
(19202) Special Topics: Integrating Machine Learning to Computer Vision Davi Geiger T 7:10-9:00PM CIWW 202

The course will investigate how Unsupervised Learning, Recurrent Networks, and Supervised Learning, are becoming the foundations of Computer Vision. We will study it through the vision topics of: Object Classification, Image Segmentation, Face Recognition, Stereo Vision, Motion, Action Recognition, and Image Annotation.
CSCI-GA.3812-001
(2272) Information Technology Projects * Evan Korth
Office Hours W 6:00-9:00PM CIWW 512

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 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
(2274) 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
(2275) 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
(2276) 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
(2277) 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
(2278) 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
(2279) 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
(2280) 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
(2281) 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
(2282) 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
(2283) 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
(2765) 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
(2284) PhD Thesis Research ** STAFF -

Prerequisites: Permission of the thesis adviser or director of graduate studies for the Ph.D. program.
CSCI-GA.3870-001
(19206) Internship In Computer Science MS* Faculty -

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

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

Prerequisites: Permission of Director of Graduate Studies.
CSCI-GA.3870-002
(19207) Internship in Computer Science PhD* Faculty -

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

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

Prerequisites: Permission of Director of Graduate Studies.
CSCI-UA.0002-001
(7165) Intro To Computer Programming Sofya Yuditskaya
Office Hours MW 2:00-3:15PM 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.0002-002
(19053) Intro To Computer Programming Joseph Versoza
Office Hours TR 11:00-12:15PM CIWW 312

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

Prerequisites: Three years of high school mathematics or equivalent. No prior computing experience is assumed. Students with any programming experience should consult with the department before registering. Students with any reported score on the Computer Science AP examination cannot enroll in this course; Albert will block them from registering for it. Students who have taken or are taking Introduction to Computer Science (CSCI-UA 101) will not receive credit for this course. Does not count toward the computer science major; serves as the prerequisite for students with no previous programming experience who want to continue into CSCI-UA 101 and pursue the major. Students may not receive credit for both CSCI-UA 2 and CSCI-UA 3.
CSCI-UA.0002-003
(7166) Intro To Computer Programming Craig Kapp
Office Hours MW 9:30-10:45AM CIWW 109

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

Prerequisites: Three years of high school mathematics or equivalent. No prior computing experience is assumed. Students with any programming experience should consult with the department before registering. Students with any reported score on the Computer Science AP examination cannot enroll in this course; Albert will block them from registering for it. Students who have taken or are taking Introduction to Computer Science (CSCI-UA 101) will not receive credit for this course. Does not count toward the computer science major; serves as the prerequisite for students with no previous programming experience who want to continue into CSCI-UA 101 and pursue the major. Students may not receive credit for both CSCI-UA 2 and CSCI-UA 3.
CSCI-UA.0002-004
(7167) 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.0002-005
(9555) Intro To Computer Programming Craig Kapp
Office Hours MW 12:30-1:45PM 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.0002-006
(7168) Intro To Computer Programming Jerry Waxman
Office Hours TR 3:30-4:45PM CIWW 317

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

Prerequisites: Three years of high school mathematics or equivalent. No prior computing experience is assumed. Students with any programming experience should consult with the department before registering. Students with any reported score on the Computer Science AP examination cannot enroll in this course; Albert will block them from registering for it. Students who have taken or are taking Introduction to Computer Science (CSCI-UA 101) will not receive credit for this course. Does not count toward the computer science major; serves as the prerequisite for students with no previous programming experience who want to continue into CSCI-UA 101 and pursue the major. Students may not receive credit for both CSCI-UA 2 and CSCI-UA 3.
CSCI-UA.0002-007
(7169) Intro To Computer Programming David Gochfeld
Office Hours MW 3:30-4:45PM CIWW 517

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

Prerequisites: Three years of high school mathematics or equivalent. No prior computing experience is assumed. Students with any programming experience should consult with the department before registering. Students with any reported score on the Computer Science AP examination cannot enroll in this course; Albert will block them from registering for it. Students who have taken or are taking Introduction to Computer Science (CSCI-UA 101) will not receive credit for this course. Does not count toward the computer science major; serves as the prerequisite for students with no previous programming experience who want to continue into CSCI-UA 101 and pursue the major. Students may not receive credit for both CSCI-UA 2 and CSCI-UA 3.
CSCI-UA.0002-008
(8557) Intro To Computer Programming Joseph Versoza
Office Hours TR 9:30-10:45AM 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.0002-009
(9556) Intro To Computer Programming Adam Meyers
Office Hours MW 8:00-9:15AM 60 Fifth Ave C10

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
(19054) Intro To Computer Programming Michell Cardona
Office Hours TR 8:00-9:15AM 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.0002-011
(9072) Intro To Computer Programming Shaun Axani
Office Hours TR 12:30-1:45PM 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.0002-012
(24196) 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.0004-001
(7170) Intro to Web Design & Computer Principles Joshua Clayton
Office Hours TR 11:00-12:15PM CIWW 102
Introduces students to both the practice of web design and the basic principles of computer science. The practice component covers not only web design but also current graphics and software tools. The principles section includes an overview of hardware and software, the history of computers, and a discussion of the impact of computers and the Internet.

Prerequisites: Three years of high school mathematics or equivalent. No prior computing experience is assumed. Students with computing experience should consult with the department before registering.
CSCI-UA.0004-002
(7171) Intro to Web Design & Computer Principles Alvaro Olsen
Office Hours MW 8:00-9:15AM 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
(7172) 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.0004-004
(8449) Intro to Web Design & Computer Principles Amos Bloomberg
Office Hours TR 9:30-10:45AM 60 Fifth Ave 150
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
(8558) Intro to Web Design & Computer Principles Craig Kapp
Office Hours TR 2:00-3:15PM 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.0004-006
(8762) Intro to Web Design & Computer Principles Lee-Sean Huang
Office Hours MW 11:00-12:15PM CIWW 202
Introduces students to both the practice of web design and the basic principles of computer science. The practice component covers not only web design but also current graphics and software tools. The principles section includes an overview of hardware and software, the history of computers, and a discussion of the impact of computers and the Internet.

Prerequisites: Three years of high school mathematics or equivalent. No prior computing experience is assumed. Students with computing experience should consult with the department before registering.
CSCI-UA.0004-007
(10077) Intro to Web Design & Computer Principles Adam Scher
Office Hours TR 8:00-9:15AM CIWW 312
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
(7173) Database Design And Web Implementation Deena Engel TR 9:30-10:45AM 60 Fifth Ave 110

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

Prerequisites: Introduction to Computer Programming (No Prior Experience) (CSCI-UA 2) or Introduction to Computer Programming (Limited Prior Experience) (CSCI-UA 3). Students that have successfully completed Data Management and Analysis (CSCI-UA 479) are NOT eligible to take this course.
CSCI-UA.0060-002
(9073) Database Design And Web Implementation Amos Bloomberg
Office Hours MW 3:30-4:45PM CIWW 101

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
(8444) Web Development And Programming Nathan Hull
Office Hours 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.0061-002
(9074) Web Development And Programming Joshua Clayton
Office Hours MW 8:00-9:15AM 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
(7174) Intro To Computer Science Suzanne McIntosh
Office Hours TR 11:00-12:15PM 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
(7175) Intro To Computer Science Evan Korth
Office Hours MW 3:30-4:45PM CIWW 102

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

Prerequisites: Introduction to Computer Programming (No Prior Experience) (CSCI-UA 2) or Introduction to Computer Programming (Limited Prior Experience) (CSCI-UA 3), or a score of 3 on the AP Computer Science exam (scores of 4 and 5 are acceptable prerequisites for students who wish to take CSCI-UA 101 before entering CSCI-UA 102; they will forfeit the AP credit), or departmental permission assessed by placement exam.
CSCI-UA.0101-003
(19055) Intro To Computer Science Suzanne McIntosh
Office Hours MW 11:00-12:15PM 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.0101-004
(7176) Intro To Computer Science Evan Korth
Office Hours TR 2:00-3:15PM CIWW 317

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

Prerequisites: Introduction to Computer Programming (No Prior Experience) (CSCI-UA 2) or Introduction to Computer Programming (Limited Prior Experience) (CSCI-UA 3), or a score of 3 on the AP Computer Science exam (scores of 4 and 5 are acceptable prerequisites for students who wish to take CSCI-UA 101 before entering CSCI-UA 102; they will forfeit the AP credit), or departmental permission assessed by placement exam.
CSCI-UA.0101-005
(8560) Intro To Computer Science Candido Cabo
Office Hours MW 12:30-1:45PM CIWW 202

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

Prerequisites: Introduction to Computer Programming (No Prior Experience) (CSCI-UA 2) or Introduction to Computer Programming (Limited Prior Experience) (CSCI-UA 3), or a score of 3 on the AP Computer Science exam (scores of 4 and 5 are acceptable prerequisites for students who wish to take CSCI-UA 101 before entering CSCI-UA 102; they will forfeit the AP credit), or departmental permission assessed by placement exam.
CSCI-UA.0101-006
(9557) Intro To Computer Science Brett Peterson
Office Hours TR 8:00-9:15AM CIWW 201

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

Prerequisites: Introduction to Computer Programming (No Prior Experience) (CSCI-UA 2) or Introduction to Computer Programming (Limited Prior Experience) (CSCI-UA 3), or a score of 3 on the AP Computer Science exam (scores of 4 and 5 are acceptable prerequisites for students who wish to take CSCI-UA 101 before entering CSCI-UA 102; they will forfeit the AP credit), or departmental permission assessed by placement exam.
CSCI-UA.0101-007
(9012) Intro To Computer Science Douglas Moody
Office Hours MW 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.0102-001
(7177) Data Structures Joanna Klukowska
Office Hours TR 2:00-3:15PM 60 Fifth Ave 110

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
(7178) Data Structures - Recitation Abtin Rahimian
Office Hours
Sebastian Herscher 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.0102-003
(7179) Data Structures Joanna Klukowska
Office Hours MW 2:00-3:15PM 60 Fifth Ave 110

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
(7180) Data Structures - Recitation Abtin Rahimian
Office Hours
Sebastian Herscher R 8:00-9:15AM 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
(7181) Data Structures Anasse Bari
Office Hours TR 8:00-9:15AM 60 Fifth Ave 110

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
(9075) Data Structures - Recitation Qi Feng W 8:00-9:15AM 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.0102-007
(9076) Data Structures Anasse Bari
Office Hours TR 3:30-4:45PM 60 Fifth Ave 110

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
(9558) Data Structures - Recitation Qi Feng W 3:30-4:45PM CIWW 109

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

Prerequisites: Introduction to Computer Science (CSCI-UA 101), or a score of 4 or 5 on the AP Computer Science examination.
CSCI-UA.0201-001
(7182) Computer Systems Organization Randy Shepherd
Office Hours MW 12:30-1:45PM 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.0201-002
(7183) Computer Systems Organization - Recitation Hassan Mujtaba Zaidi
Office Hours T 8:00-9:15AM CIWW 109

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

Prerequisites: Data Structures (CSCI-UA 102).
CSCI-UA.0201-003
(9925) Computer Systems Organization Joanna Klukowska
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.0201-004
(9926) Computer Systems Organization - Recitation Hassan Mujtaba Zaidi
Office Hours M 3:30-4:45PM 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.0202-001
(7184) Operating Systems Allan Gottlieb
Office Hours TR 3:30-4:45PM CIWW 109

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

Prerequisites: Computer Systems Organization (CSCI-UA 201).
CSCI-UA.0310-001
(7185) Basic Algorithms Victor Shoup TR 2:00-3:15PM CIWW 109

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

Prerequisites: Data Structures (CSCI-UA 102); Discrete Mathematics (MATH-UA 120); and either Calculus I (MATH-UA 121) OR Mathematics for Economics I (MATH-UA 211).
CSCI-UA.0310-002
(7186) Basic Algorithms - Recitation Abhinav Tamaskar
Office Hours W 12:30-1:45PM CIWW 109

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

Prerequisites: Data Structures (CSCI-UA 102); Discrete Mathematics (MATH-UA 120); and either Calculus I (MATH-UA 121) OR Mathematics for Economics I (MATH-UA 211).
CSCI-UA.0310-003
(7187) Basic Algorithms Alan Siegel
Office Hours MW 11:00-12:15PM 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.0310-004
(9077) Basic Algorithms - Recitation Alan Siegel
Office Hours F 11:00-12:15PM 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.0310-005
(24176) Basic Algorithms - Recitation Abhinav Tamaskar
Office Hours R 9:30-10:45AM CIWW 109

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

Prerequisites: Data Structures (CSCI-UA 102); Discrete Mathematics (MATH-UA 120); and either Calculus I (MATH-UA 121) OR Mathematics for Economics I (MATH-UA 211).
CSCI-UA.0330-001
MATH-UA.0144
(9228) Introduction to Computer Simulation Charles Peskin
Office Hours TR 11:00-12:15PM CIWW 512

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

Prerequisites: Calculus I (MATH-UA 121) or Math for Economics II (MATH-UA 212) and General Physics (PHYS-UA 11).
CSCI-UA.0330-002
(9229) Introduction to Computer Simulation Jinhyun Kim F 11:00-12:15PM CIWW 102

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

Prerequisites: Calculus I (MATH-UA 121) or Math for Economics II (MATH-UA 212) and General Physics (PHYS-UA 11).
CSCI-UA.0380-001
(8559) Topics of General Interest: Physical Computing Amos Bloomberg
Office Hours MW 12:30-1:45PM CIWW 201

This course takes interactive computing beyond the limitations of the mouse, the keyboard and the monitor. It brings the revolutionary power of the semiconductor away from the home and office and into the physical world of everyday life. We learn to program micro-controllers, which are single-chip computers that can easily fit in the palm of your hand. Through a variety of electronic sensors, we detect aspects of the physical world, such as light, sound, and touch, to input that data into our programs. The applications create meaningful output using lights, motors, and speakers. This course teaches hands-on electronics as students build projects using wires, circuits, and other components.

Prerequisites: Students must complete Introduction to Computer Programming (CSCI-UA 2) and Introduction to Web Design and Computer Principles (CSCI-UA 4) with a grade of C or better before taking this class.
CSCI-UA.0380-002
(8869) Topics of General Interest: Drawing on the Web Joshua Clayton
Office Hours TR 2:00-3:15PM CIWW 312

The Web is an intrinsically visual medium whose graphical capabilities are diverse and evolving. With the development of HTML5 and CSS3, there are now multiple ways to code images and animation natively in the browser. This course will provide a survey of current drawing techniques. We will create a series of Web-based projects that involve raster graphics, vector graphics, and interactivity using HTML, CSS, SVG, and JavaScript. Drawing on the Web builds upon foundations in Web design and computer programming with a focus on the range of graphics that can be coded into Web pages.

Prerequisites: Students must complete Introduction to Computer Programming (CSCI-UA 2) and Introduction to Web Design and Computer Principles (CSCI-UA 4) with a grade of C or better before taking this class.
CSCI-UA.0380-003
(9559) Topics of General Interest: Python for Applications CANCELLED -
Detailed descriptions available when topics are announced. Typical offerings include Computing in the Humanities and Arts and Introduction to Flash Programming. Does not count toward the computer science major.

Prerequisites: Topics determine prerequisites.
CSCI-UA.0421-001
(7188) Numerical Computing Michael Overton
Office Hours TR 9:30-10:45AM 60 Fifth Ave C12

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

Prerequisites: Computer Systems Organization (CSCI-UA 201), either Calculus I (MATH-UA 121) or both of Mathematics for Economics I and II (MATH-UA 211 and 212), and Linear Algebra (MATH-UA 140), or permission of instructor.
CSCI-UA.0453-001
(9562) Theory Of Computation Guy Kindler
Office Hours MW 3:30-4:45PM CIWW 201

A mathematical approach to studying topics in computer science, such as regular languages and some of their representations (deterministic finite automata, nondeterministic finite automata, regular expressions) and proof of nonregularity. Context-free languages and pushdown automata; proofs that languages are not context-free. Elements of computability theory. Brief introduction to NP-completeness.

Prerequisites: Basic Algorithms (CSCI-UA 310) and Computer Systems Organization (CSCI-UA.201).
CSCI-UA.0465-001
(23163) Introduction to Robotics Chee Yap
Office Hours TR 3:30-4:45PM CIWW 312

Robots are basically computers with sensors and actuators (motors) that interact with the physical world. Unmanned Autonomous Vehicles (UAV) including mobile robots and quadcopters are increasing being deployed in society. But these robots are only as good as the algorithms that run on them. This course looks at some basic algorithmic tasks that robots must solve: collision detection, motion planning, coordination, and the Simultaneous Localization and Mapping (SLAM) problem. Through such algorithms, we introduce students to elements of computational geometry, kinematics, dynamics and control theory. The course will be a mix of theory, algorithms and programming, culminating in a final project. Programming will be in Matlab (including Simulink) and C++/OpenGL programming. A reference is Peter Corke's Robotics Book based on Matlab. Not offered every academic year.

Prerequisites: <p>Operating Systems (CSCI-UA 202), Calculus I (MATH-UA 121) and Linear Algebra (MATH-UA 140).</p>
CSCI-UA.0470-001
(22984) Object Oriented Programming Thomas Wies
Office Hours MW 2:00-3:15PM CIWW 102

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.0473-001
(19060) Intro To Machine Learning Kyunghyun Cho
Office Hours MW 9:30-10:45AM 60 Fifth Ave C12

This exciting and fast-evolving field of computer science has many recent consumer applications (e.g., Microsoft Kinect, Google Translate, IPhone's Siri, digital camera face detection, Netflix recommendations, Google news) and applications within the sciences and medicine (e.g., predicting protein-protein interactions, species modeling, detecting tumors, personalized medicine). Students learn the theoretical foundations and how to apply machine learning to solve new problems.

Prerequisites: Data Structures (CSCI-UA.102), Linear Algebra (MATH-UA.140) and Probability and Statistics (MATH-UA.235). Students may take any of the following courses in place of MATH-UA.235: Theory of Probability (MATH-UA 233), Mathematical Statistics (MATH-UA 234), Honors Theory of Probability (MATH-UA 238) OR Data Analysis (MA-UY 2224).
CSCI-UA.0480-001
(7189) Special Topics: Computer Vision Davi Geiger TR 2:00-3:15PM CIWW 102

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 System Organization (CSCI-UA.0201) with a grade of C or better.
CSCI-UA.0480-002
(7190) Special Topics: iOS Programming Nathan Hull
Office Hours MW 3:30-4:45PM CIWW 317

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

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

Prerequisites: Computer System Organization (CSCI-UA.0201) with a grade of C or better.
CSCI-UA.0480-003
(7191) Special Topics: Parallel Computing Mohamed Zahran
Office Hours MW 2:00-3:15PM CIWW 109

Most of us have learned to program a single microprocessor (single core) using a high-level programming language like C/C++, Java, ... This is called sequential programming. We feel very comfortable with this because we think in a sequential way and give the machine statements to be executed in sequence. However, this has to change. A microprocessor with single core no longer exists in almost all computers we are using today (including your tablets and smart phones). Most of our devices are now multicore processors. A multicore processor contains several cores (called CPUs or cores) on-chip. To make the best use of these multicore chips we need to program them in-parallel. Sequential programming, for all platforms from smartphones to supercomputers, is falling out of fashion and taking back-seat to parallel programming. How to think in parallel? How to write code in parallel to make the best use of the underlying hardware? How is that new hardware different from the traditional one? What will the future be for the software and hardware? This is the topic of this course.

Prerequisites: Computer System Organization (CSCI-UA.0201) with a grade of C or better.
CSCI-UA.0480-004
(8561) Special Topics: Algorithmic Problem Solving John Zhang
Office Hours TR 3:30-4:45PM CIWW 101

Many of the top firms in the technological and financial sectors are using algorithmic problems as interview questions for assessing candidate skill. In this course we take this idea one step further and use algorithmic problem solving as way to hone programming skills. Students will use the material covered in the data structures and algorithms courses and learn new algorithmic techniques to solve challenging problems quickly. Each week will be devoted to a particular type of algorithm. Weekly problem sets will reinforce the lecture, and require students to implement their solutions in Java or C++.

Students completing this course will be well prepared to participate in programming competitions such as the ACM Inter-Collegiate Programming Contest, TopCoder, and Google's Code Jam.

Prerequisites: CSCI-UA.0201 Computer Systems Organization, CSCI-UA.0310 Basic Algorithms. Student must also register for Recitation section 005.
CSCI-UA.0480-005
(9078) Special Topics: Algorithmic Problem Solving - RECITATION Bowen Yu F 5:10-7:10PM CIWW 101

Many of the top firms in the technological and financial sectors are using algorithmic problems as interview questions for assessing candidate skill. In this course we take this idea one step further and use algorithmic problem solving as way to hone programming skills. Students will use the material covered in the data structures and algorithms courses and learn new algorithmic techniques to solve challenging problems quickly. Each week will be devoted to a particular type of algorithm. Weekly problem sets will reinforce the lecture, and require students to implement their solutions in Java or C++.

Students completing this course will be well prepared to participate in programming competitions such as the ACM Inter-Collegiate Programming Contest, TopCoder, and Google's Code Jam.

Prerequisites: CSCI-UA.0201 Computer Systems Organization, CSCI-UA.0310 Basic Algorithms. This is the required recitation for CSCI-UA.480-04.
CSCI-UA.0480-006
(9079) Special Topics: Computer Graphics Kenneth Perlin
Office Hours TR 11:00-12:15PM 60 Fifth Ave 150

There are many courses that can teach you how to use commercial computer graphics packages and APIs. This course, in contrast, will teach you how to build 3D computer graphics from the ground up. This will include 3D modeling, animation, and rendering. At the end of the semester you will have built your own complete working real-time 3D computer graphics systems that runs in web browsers.

Prerequisites: Computer System Organization (CSCI-UA.0201) with a grade of C or better.
CSCI-UA.0480-007
(9311) Special Topics: Advanced Computer Systems CANCELLED -

This course will deepen students' understanding of complex computer systems: how these systems work, how to approach a given system or proposal critically, and how to design and build systems. Topics will include the interface between computer hardware and software, concurrency and parallelism, performance analysis, virtual machines, sandboxing, distributed systems, networking and the Internet, and security. The work will include substantial implementation exercises, critical reading and in-class discussion of research papers, and a final project. Because of the close relationship among critical reading, critical thinking, and clear communication, there may also be exercises to build writing skill.

Prerequisites: CSCI-UA.0202 with a B or better and INSTRUCTOR APPROVAL - Please email Professor Walfish at mwalfish@cs.nyu.edu for approval.
CSCI-UA.0480-008
(9560) Special Topics: Applied Internet Technology Joseph Versoza
Office Hours MW 11:00-12:15PM 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: Computer System Organization (CSCI-UA.0201) with a grade of C or better.
CSCI-UA.0480-009
(9561) 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: Computer System Organization (CSCI-UA.0201) with a grade of C or better.
CSCI-UA.0480-010
(23635) Special Topics: Multicore Programming Christopher Mitchell
Office Hours W 6:20-8:50PM 60 Fifth Ave C12

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:

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

Students will be expected to have experience with a programming-intensive course, enjoy reading a reasonable number of academic papers, and have some experience with C/C++. The course will include lectures, homework, labs, a final project, and a final exam.

Prerequisites: CSCI-UA.0201

*

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.