Course Schedule

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Number

Name

Professor(s)

Meet Time

Room

CSCI-GA.1144-002
(3039) PAC II Recitation Richik Jaiswal
Office Hours 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.1170-004
DS-GA.1170
(3536) Fundamental Algorithms Recitation Shravas Rao 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.2110-002
(2636) Programming Languages Recitation Thomas Wies
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.2262-001
(2639) 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.2620-001
(3076) Networks and Mobile Systems Anirudh Sivaraman
Office Hours R 7:10-9:00PM 60 Fifth Ave C12

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.2945-003
MATH-GA.2012-003
(20917) Adv Topics Num Analysis: Numerical Optimization Margaret Wright
Office Hours R 5:10-7:00PM CIWW 312

Many problems in science, engineering, medicine, and business involve optimization, in which we seek to optimize a mathematical measure of goodness subject to constraints. This course will survey widely used methods for continuous optimization, focusing on both theoretical foundations and implementation as software.

The course will cover: linear programming (including the simplex method and interior-point methods); line search and trust region methods for unconstrained optimization; methods for convex and nonconvex quadratic programming; and penalty, barrier, augmented agrangian, and interior-point methods for convex and nonconvex constrained optimization. In all cases, attention will be paid to numerical issues.

Prerequisites: Students are expected to be comfortable with numerical linear algebra and multivariate calculus, and to have programming experience (preferably in Matlab). Students without all elements of this background are likely to have difficulty with the course material.
CSCI-GA.3033-002
(3126) Special Topics: Social Networks Bhubaneswar Mishra
Office Hours R 7:10-9:00PM CIWW 512

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, and LinkedIn, etc. connect small groups of friends; amazon, eBay, etc. provide opportunities for trading, etc, BitCoins, Ethereum, etc. allow parties to make financial and contractual transactions . 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., and have evolved with the dynamics of evolutionary games (particularly Signaling Games). 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, and mechanism designed to interact strategically: SmartContractss, Costly Signaling, Credible and Noncredible Threats, Model Checking and Verification, Safety and Liveness, Recommenders and Verifiers, Deception, Market mechanisms (pricing and auction), Privacy and Trust… Exampled Systems: Bit-coins, Zcash, Ripple, Stellar, Ethereum, Solidity, Rholang, DAO (Distributed Companies), Cyber Security (M-coins), Information Finance Markets (WealthFront, etc.), Market Microstructure, ICO/STO/ITO, GDPR, OpenLaw, OpenZeplin, ...
CSCI-GA.3033-005
(2649) Special Topics: Big Data Application Development Suzanne McIntosh
Office Hours R 7:10-9:00PM CIWW 101

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

Prerequisites: Students should have experience using Hadoop (HDFS and MapReduce). In addition, students should have: strong programming skills in Java, Python, or C/C++; coursework in operating systems, networking, and algorithms; familiarity with Linux commands.
CSCI-GA.3033-010
(3354) Special Topics: Cloud Computing Jean-Claude Franchitti
Office Hours R 7:10-9:00PM CIWW 102

This is a capstone course.

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.

Similar functionalities are provided on the AWS, Google Cloud (GCP), and Microsoft Azure platforms. Additional aPaaS platforms of interest Oracle aPaaS, Red Hat OpenShift, Salesforce App Cloud, and SAP Hana Cloud Platform (HCP).
CSCI-GA.3033-018
(3361) Special Topics: Geometric Modeling Daniele Panozzo
Office Hours R 5:10-7:00PM 60 Fifth Ave C12

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-UA 140 (or an equivalent undergraduate course in linear algebra)
CSCI-GA.3033-025
(20912) Special Topics: Cloud and Machine Learning I-Hsin Chung
Office Hours
Seetharami Seelam R 5:10-7:00PM CIWW 201

This is a capstone course.

This course exposes students to various cloud computing models and introduces them to performing machine learning on the cloud. The course material introduces students to various cloud providers including Amazon AWS, Google GCE, and IBM Cloud and their machine learning service capabilities. Students will learn how to build cloud systems for machine learning, the application characteristics, and develop hands-on experience with programming machine learning applications on these cloud platforms.

Prerequisites: CSCI-GA 1170, CSCI-GA 2110, and CSCI-GA 2250. Basic understudying of operating systems and computer architecture, ability to program in at least one of c/c++, go, or Python languages. Basic understanding of cloud computing systems.
CSCI-GA.3850-004
(2659) 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-UA.0002-002
(9930) 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 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.
CSCI-UA.0002-004
(7842) Intro To Computer Programming Adam Meyers
Office Hours TR 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 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.
CSCI-UA.0002-008
(9651) 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 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.
CSCI-UA.0002-010
(9421) 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 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.
CSCI-UA.0002-011
(19582) Intro To Computer Programming Saadia Lgarch
Office Hours TR 3:30-4:45PM CIWW 512

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 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.
CSCI-UA.0004-002
(7846) Intro to Web Design & Computer Principles Amos Bloomberg
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.0004-007
(9795) Intro to Web Design & Computer Principles Adam Scher
Office Hours TR 8:00-9:15AM 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.0060-001
(7848) Database Design And Web Implementation Deena Engel
Office Hours TR 2:00-3:15PM CIWW 102
Introduces principles and applications of database design. Students learn to use a relational database system, learn web implementations of database designs, and write programs in SQL. Students explore principles of database design and apply those principles to computer systems in general and in their respective fields of interest.

Prerequisites: Introduction to Computer Programming (CSCI-UA 2) and Introduction to Web Design & Computer Principles (CSCI-UA 4).
CSCI-UA.0061-002
(9423) Web Development And Programming Nathan Hull TR 2:00-3:15PM CIWW 202
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 (CSCI-UA 2) and Introduction to Web Design & Computer Principles (CSCI-UA 4).
CSCI-UA.0101-001
(7849) Intro To Computer Science Suzanne McIntosh
Office Hours TR 11:00-12:15PM Silv 414
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 (CSCI-UA 2) or departmental permission assessed by placement exam.
CSCI-UA.0101-002
(7850) Intro To Computer Science Teseo Schneider
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 (CSCI-UA 2) or departmental permission assessed by placement exam.
CSCI-UA.0102-004
(7855) Data Structures - Recitation Nicholas Greenquist
Office Hours 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).
CSCI-UA.0102-005
(7856) Data Structures Anasse Bari
Office Hours TR 9:30-10:45AM 60 Fifth Ave 150
Use and design of data structures, which organize information in computer memory. Stacks, queues, linked lists, binary trees: how to implement them in a high-level language, how to analyze their effect on algorithm efficiency, and how to modify them. Programming assignments.

Prerequisites: Introduction to Computer Science (CSCI-UA 101).
CSCI-UA.0102-007
(9425) Data Structures Anasse Bari
Office Hours TR 2:00-3:15PM Silv 401
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).
CSCI-UA.0201-003
(9753) Computer Systems Organization Joanna Klukowska
Office Hours TR 9:30-10:45AM CIWW 109
Covers the internal structure of computers, machine (assembly) language programming, and the use of pointers in high-level languages. Topics include the logical design of computers, computer architecture, the internal representation of data, instruction sets, and addressing logic, as well as pointers, structures, and other features of high-level languages that relate to assembly language. Programming assignments are in both assembly language and other languages.

Prerequisites: Data Structures (CSCI-UA 102).
CSCI-UA.0201-005
(10278) Computer Systems Organization Allan Gottlieb 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.0202-001
(7859) Operating Systems Allan Gottlieb 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
(7860) Basic Algorithms Alan Siegel 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) and Discrete Mathematics (MATH-UA 120).
CSCI-UA.0310-004
(9426) Basic Algorithms - Recitation Erica Dominic R 9:30-10:45AM 12WV L120
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) and Discrete Mathematics (MATH-UA 120).
CSCI-UA.0310-005
(10144) Basic Algorithms Victor Shoup TR 12:30-1:45PM CIWW 101
Introduction to the study of algorithms. Presents two main themes: designing appropriate data structures and analyzing the efficiency of the algorithms that use them. Algorithms studied include sorting, searching, graph algorithms, and maintaining dynamic data structures. Homework assignments, not necessarily involving programming.

Prerequisites: Data Structures (CSCI-UA 102) and Discrete Mathematics (MATH-UA 120).
CSCI-UA.0330-001
MATH-UA.0144
(9508) Introduction to Computer Simulation Charles Peskin TR 11:00-12:15PM CIWW 317
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: A grade of C or higher in MATH-UA 121 Calculus I or MATH-UA 212 Math for Economics II (for Economics majors) and PHYS-UA 11 General Physics.
CSCI-UA.0380-001
(9091) Topics of General Interest: Drawing on the Web Joshua Clayton
Office Hours TR 2:00-3:15PM CIWW 312

In this course you will learn how to develop multimedia applications for both the desktop and the web. The course focuses on general programming techniques with an emphasis on the production of interactive graphical environments. In addition, a number of advanced topics will be covered including image processing, video games, simulations, basic computer vision, augmented reality (AR), virtual reality (VR) and data visualization techniques.

Prerequisites: Intro To Computer Programming (CSCI-UA 2) and Intro to Web Design & Computer Principles (CSCI-UA 4), or permission of Instructor
CSCI-UA.0421-001
(7863) Numerical Computing Michael Overton
Office Hours TR 9:30-10:45AM CIWW 312

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
(9654) Theory Of Computation Richard Cole
Office Hours TR 11:00-12:15PM 60 Fifth Ave C12
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).
CSCI-UA.0473-001
(9933) Intro To Machine Learning Kyunghyun Cho
Office Hours TR 9:30-10:45AM CIWW 102

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: Computer Systems Organization (CSCI-UA 201), Calculus I (MATH-UA 121), and Linear Algebra (MATH-UA 140). Prerequisite or co-requisite: Basic Algorithms (CSCI-UA 310). Recommended: MATH-UA 235 Probability and Statistics, MATH-UA 234 Mathematical Statistics
CSCI-UA.0480-004
(9093) Special Topics: Algorithmic Problem Solving Joanna Klukowska
Office Hours TR 12:30-1:45PM Silv 520

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: Computer Systems Organization (CSCI-UA 201) and Basic Algorithms (CSC-UA 310) with a grade of C or better. Student must also register for the Recitation – CSCI-UA.480-005.
CSCI-UA.0480-006
(9428) Special Topics: Computer Graphics Kenneth Perlin
Office Hours TR 11:00-12:15PM 194M 306

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 run in web browsers.

Prerequisites: CSCI-UA 201 Computer Systems Organization, CSCI-UA-310 (Basic Algorithms) and MATH-UA-140 (Linear Algebra) with grades of C or better, or departmental consent.
CSCI-UA.0480-007
(9653) Special Topics: Agile Software Development and DevOps Amos Bloomberg
Office Hours TR 12:30-1:45PM CIWW 109

Agile software development has come to describe a specific approach and toolset that allow for the requirements of a software project to change as a project progresses without disrupting schedules, budgets, and responsibilities. The field of DevOps, a portmanteau of development and operations has introduced further processes and infrastructure to automate many of the tasks required in such development. Together, Agile's methodology and DevOps' automation have increased the speed, robustness, and scalability with which software is developed today. Upon completion of this course, students will understand the core methodologies, technologies, and tools used for software engineering.

Prerequisites: CSCI-UA.0201 with a grade of C or better

*

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.
****

Indicates controlled enrollment (permission number required for registration). Contact dhss@nyu.edu for assistance.