Course Schedule

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Number

Name

Professor(s)

Meet Time

Room

CSCI-GA.1133-001
(2742) PAC I* Nolan Filter
Office Hours T 6:30-9:00PM CIWW 201

An accelerated introduction to the fundamental concepts of computer science for students who lack a formal background in the field. Topics include algorithm design and program development; data types; control structures; subprograms and parameter passing; recursion; data structures; searching and sorting; dynamic storage allocation and pointers; abstract data types, such as stacks, queues, lists, and tree structures; generic packages; and an introduction to the principles of object-oriented programming. The primary programming language used in the course will be Java. Students should expect an average of 12-16 hours of programming and related course work per week.
CSCI-GA.1170-001
DS-GA.1170
(2743) Fundamental Algorithms Yevgeniy Dodis
Office Hours T 5:10-7:00PM CIWW 109

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

Prerequisites: At least one year of experience with a high-level language such as Pascal, C, C++, or Java; and familiarity with recursive programming methods and with data structures (arrays, pointers, stacks, queues, linked lists, binary trees).
CSCI-GA.2434-001
(2750) Advanced Database Systems Dennis Shasha
Office Hours T 5:10-7:00PM CIWW 101
This is a capstone course emphasizing large-scale database systems. This course studies the internals of database systems as an introduction to research and as a basis for rational performance tuning. Topics include concurrency control, fault tolerance, operating system interactions, query processing, and principles of tuning. Database capstone projects involve topics such as design, concurrency control, interactions, and tuning. These projects include some or all of the following elements: formation of a small team, project proposal, literature review, interim report, project presentation, and final report.

Prerequisites: CSCI-GA 1170, CSCI-GA 2110, and CSCI-GA 2250.
CSCI-GA.2565-001
(23839) Machine Learning Rajesh Ranganath
Office Hours T 7:10-9:00PM 60 Fifth Ave 110

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

Prerequisites: Undergraduate course in linear algebra and strong programming skills for implementation of algorithms studied in class. Strong knowledge of probability. Recommended: knowledge of vector calculus, elementary statistics.
CSCI-GA.2630-001
(3749) Foundations of Networks and Mobile Systems* Lakshminarayanan Subramanian
Office Hours T 9:00-10:50AM Tisch 201 Additional information: Open only to students in the MS-CEI program.

The class will begin with introductory concepts of network protocols across different layers of the network stack including routing, transport, naming, addressing and connect them to the core building blocks of the Internet. The second part of the class will focus on networking concepts in the evolution of Webbased systems, providing an introduction to datacenter networks, clouds, middle boxes (proxies, firewalls) and next generation networks. The third part of the class will focus on the fundamental concepts in wireless networks, cellular networks and mobile devices with a specific focus on mobile programming and applications, 802.11 evolution, mobile services and the evolution of cellular networks.
CSCI-GA.2630-002
(3898) Foundations of Networks and Mobile Systems Lab* Lakshminarayanan Subramanian
Office Hours T 11:00-11:50AM Tisch 201 Additional information: Open only to students in the MS-CEI program.

The class will begin with introductory concepts of network protocols across different layers of the network stack including routing, transport, naming, addressing and connect them to the core building blocks of the Internet. The second part of the class will focus on networking concepts in the evolution of Webbased systems, providing an introduction to datacenter networks, clouds, middle boxes (proxies, firewalls) and next generation networks. The third part of the class will focus on the fundamental concepts in wireless networks, cellular networks and mobile devices with a specific focus on mobile programming and applications, 802.11 evolution, mobile services and the evolution of cellular networks.
CSCI-GA.2945-001
MATH-GA.2011-001 Advanced Topics In Numerical Methods: Monte Carlo Methods Jonathan Weare T 3:20-5:10PM CIWW 1302

This class primarily concerns the design and analysis of Monte Carlo sam-pling techniques for the estimation of averages with respect to high dimen-sional probability distributions. Standard simulation tools such as importance sampling, sequential importance sampling, Gibbs and Metropolis-Hastings sampling, Langevin dynamics, and hybrid Monte Carlo will be introduced along with basic theoretical concepts regarding their convergence to equilibrium. Particular attention will be paid to the major complicating issues like conditioning and rare events along with methods to address them (e.g. tempering, interacting particle methods, and free-energy methods).
CSCI-GA.3033-005
(25093) Special Topics: Big Data Application Development Suzanne McIntosh
Office Hours T 7:10-9:00PM CIWW 317

This is an introductory course on Spark programming, Spark architecture, Spark SQL, Spark Streaming, and integration of Spark with the Hadoop ecosystem for developing Big Data analytics applications. The course project can be completed with Scala or Python, and Spark. This course covers technologies that integrate well with Spark in the creation of Big Data analytics applications.

Students are required to complete weekly reading and programming assignments and demonstrate mastery of course topics by developing a final project using Spark.

Prerequisites: Prerequisites include experience with Hadoop, which commonly comes from having completed the Realtime and Big Data Analytics course. There will be a review of Apache Hadoop, but students should have experience with Hadoop MapReduce and HDFS.
CSCI-GA.3033-008
(3386) Special Topics: Statistical Natural Language Processing Ankur Parikh
Office Hours T 5:10-7:00PM CIWW 512

In this course we will examine some of the core tasks in natural language processing, starting with simple word-based models for text classification and building up to more complex models for syntactic parsing, machine translation, question answering, and text generation. The course will cover a variety of statistical and machine learning approaches including recent advances in deep learning. In addition to the core topics, we will discuss recent research progress in the area such as unsupervised pretraining and adversarial examples. This course assumes a good background in basic probability as well as interest in building real systems.
CSCI-GA.3033-027
(26031) Special Topics: Bayesian Machine Learning Andrew Gordon Wilson
Office Hours T 5:10-7:00PM CIWW 102

This course aims to provide students with a strong grasp of the fundamental principles underlying Bayesian model construction and inference. We will go into particular depth on Gaussian process and probabilistic deep learning models. The course will be comprised of three units, alongside a major research project component. 1. Model Construction and Inference: Parametric models, support, inductive biases, gradient descent, sum and product rules, graphical models, exact inference, approximate inference (Laplace approximation, variational methods, MCMC), model selection and hypothesis testing, Occam's razor, non-parametric models. 2. Gaussian Processes: From finite basis expansions to infinite bases, kernels, function-space modelling, marginal likelihood, non-Gaussian likelihoods, Bayesian optimization. 3. Bayesian Deep Learning: Fully connected, convolutional, and recurrent networks, generative models, normalizing flows, loss surfaces, deep kernel learning, subspace inference.

Prerequisites: A strong foundation in basic linear algebra, probability, statistics, multivariable calculus, and programming. A careful reading of the first three chapters of Christopher Bishop's Pattern Recognition and Machine Learning (2006) before class starts. Prior courses on machine learning are strongly recommended.
CSCI-GA.3205-001
(3754) Applied Cryptography & Network Security Constantine Christakos
Office Hours T 7:10-9:00PM CIWW 312
This course first introduces the fundamental mathematical cryptographic algorithms, focusing on those that are used in current systems. To the extent feasible, the mathematical properties of the cryptographic algorithms are justified, using elementary mathematical tools. Second, actual security mechanisms and protocols, mainly those employed for network traffic that rely on the previously introduced cryptographic algorithms, are presented. The topics covered include introduction to basic number-theoretical properties, public/private and symmetric key systems, secure hash functions, digital signature standards, digital certificates, IP security, e-mail security, Web security, and stand-alone computer privacy and security tools.
CSCI-GA.3520-001
(2757) Honors Analysis of Algorithms Subhash Khot
Office Hours TR 9:30-10:45AM CIWW 101
Design of algorithms and data structures. Review of searching, sorting, and fundamental graph algorithms. In-depth analysis of algorithmic complexity, including advanced topics on recurrence equations and NP-complete problems. Advanced topics on lower bounds, randomized algorithms, amortized algorithms, and data structure design as applied to union-find, pattern matching, polynomial arithmetic, network flow, and matching.

Prerequisites: Permission of the instructor for master’s students.
CSCI-GA.3850-001
(21583) PhD Seminar: Cryptography** Yevgeniy Dodis
Office Hours T 12:30-3:15PM CIWW 412
Graduate seminars serve as loosely structured forums for exploring research topics from broad areas of computer science. They are designed to foster dialogue by bringing together faculty and students from a given area and to encourage the exchange of ideas. As such, they bridge the gap between more structured course offerings and informal research meetings. Subject matter varies by section.

Prerequisites: Permission of the instructor.
CSCI-UA.0002-001
(7925) Intro To Computer Programming (No Prior Experience) Nathan Hull
Office Hours TR 12:30-1:45PM CIWW 202

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

Prerequisites: Three years of high school mathematics or equivalent. No prior computing experience is assumed. Students with any programming experience should consult with the department before registering. Students 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.0002-002
(7926) Intro To Computer Programming (No Prior Experience) Craig Kapp
Office Hours TR 11:00-12:15PM 60 Fifth Ave 150

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

Prerequisites: Three years of high school mathematics or equivalent. No prior computing experience is assumed. Students with any programming experience should consult with the department before registering. Students 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.0002-006
(7929) Intro To Computer Programming (No Prior Experience) Shaheer Mohammed Haroon
Office Hours TR 9:30-10:45AM 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 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.0002-009
(9321) Intro To Computer Programming (No Prior Experience) Saadia Lgarch
Office Hours TR 3:30-4:45PM CIWW 517

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

Prerequisites: Three years of high school mathematics or equivalent. No prior computing experience is assumed. Students with any programming experience should consult with the department before registering. Students 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
(10509) Intro To Computer Programming (No Prior Experience) Na'im Tyson
Office Hours TR 8:00-9:15AM CIWW 201

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

Prerequisites: Three years of high school mathematics or equivalent. No prior computing experience is assumed. Students with any programming experience should consult with the department before registering. Students 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.0002-012
(9835) Intro To Computer Programming (No Prior Experience) Michell Cardona
Office Hours TR 8:00-9:15AM 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.0004-004
(7934) Intro to Web Design & Computer Principles Joshua Clayton
Office Hours TR 12:30-1:45PM Silv 401
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
(9320) Intro to Web Design & Computer Principles Lee-Sean Huang
Office Hours TR 2:00-3:15PM CIWW 201
Introduces students to both the practice of web design and the basic principles of computer science. The practice component covers not only web design but also current graphics and software tools. The principles section includes an overview of hardware and software, the history of computers, and a discussion of the impact of computers and the Internet.

Prerequisites: Three years of high school mathematics or equivalent. No prior computing experience is assumed. Students with computing experience should consult with the department before registering.
CSCI-UA.0004-007
(9479) Intro to Web Design & Computer Principles Adam Scher
Office Hours TR 8:00-9:15AM 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.0060-001
(9351) Database Design And Implementation Deena Engel
Office Hours TR 2:00-3:15PM CIWW 1302

Introduces principles and applications of database design. Students learn to use a relational database system, learn 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.0002).
CSCI-UA.0061-002
(9682) Web Development And Programming Sana Odeh
Office Hours TR 3:30-4:45PM CIWW 101

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

Prerequisites: Introduction to Computer Programming (CSCI-UA.0002) and Introduction to Web Design & Computer Principles (CSCI-UA.0004).
CSCI-UA.0101-001
(7936) Intro To Computer Science Anasse Bari
Office Hours TR 2:00-3:15PM CIWW 101
How to design algorithms to solve problems and how to translate these algorithms into working computer programs. Experience is acquired through projects in a high-level programming language. Intended primarily for computer science majors but also suitable for students of other scientific disciplines. Programming assignments.

Prerequisites: Introduction to Computer Programming (CSCI-UA 2) or departmental permission assessed by placement exam.
CSCI-UA.0101-002
(7937) Intro To Computer Science Amos Bloomberg
Office Hours TR 9:30-10:45AM 60 Fifth Ave 110
How to design algorithms to solve problems and how to translate these algorithms into working computer programs. Experience is acquired through projects in a high-level programming language. Intended primarily for computer science majors but also suitable for students of other scientific disciplines. Programming assignments.

Prerequisites: Introduction to Computer Programming (CSCI-UA 2) or departmental permission assessed by placement exam.
CSCI-UA.0101-003
(7938) Intro To Computer Science Teseo Schneider
Office Hours TR 3:30-4:45PM 25W 4th C-20
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.0101-008
(9970) Intro To Computer Science Nader Nassar
Office Hours TR 8:00-9:15AM CIWW 102
How to design algorithms to solve problems and how to translate these algorithms into working computer programs. Experience is acquired through projects in a high-level programming language. Intended primarily for computer science majors but also suitable for students of other scientific disciplines. Programming assignments.

Prerequisites: Introduction to Computer Programming (CSCI-UA 2) or departmental permission assessed by placement exam.
CSCI-UA.0102-002
(7941) Data Structures - Recitation Chandra Prakash Konkimalla T 12:30-1:45PM CIWW 109
Use and design of data structures, which organize information in computer memory. Stacks, queues, linked lists, binary trees: how to implement them in a high-level language, how to analyze their effect on algorithm efficiency, and how to modify them. Programming assignments.

Prerequisites: Introduction to Computer Science (CSCI-UA 101).
CSCI-UA.0102-003
(7942) Data Structures Anasse Bari
Office Hours TR 11:00-12:15PM CIWW 101
Use and design of data structures, which organize information in computer memory. Stacks, queues, linked lists, binary trees: how to implement them in a high-level language, how to analyze their effect on algorithm efficiency, and how to modify them. Programming assignments.

Prerequisites: Introduction to Computer Science (CSCI-UA 101).
CSCI-UA.0102-006
(9546) Data Structures - Recitation Justin Mae T 11:00-12:15PM CIWW 201
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
(9826) Data Structures Ernest Davis
Office Hours TR 2:00-3:15PM CIWW 202
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.0102-009
(10627) Data Structures Young Kun Ko
Office Hours TR 9:30-10:45AM CIWW 102
Use and design of data structures, which organize information in computer memory. Stacks, queues, linked lists, binary trees: how to implement them in a high-level language, how to analyze their effect on algorithm efficiency, and how to modify them. Programming assignments.

Prerequisites: Introduction to Computer Science (CSCI-UA 101).
CSCI-UA.0102-012
(10721) Data Structures - Recitation Tulsi Jain T 9:30-10:45AM CIWW 202
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.0102-014
(21664) Data Structures - Recitation Samarth Tambad T 8:00-9:15AM CIWW 202
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
(9345) Computer Systems Organization Mohamed Zahran
Office Hours TR 3:30-4:45PM Silv 520
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
(7947) Operating Systems Michael Walfish
Office Hours TR 2:00-3:15PM CIWW 109
Covers the principles and design of operating systems. Topics include process scheduling and synchronization, deadlocks, memory management (including virtual memory), input/output, and file systems. Programming assignments.

Prerequisites: Computer Systems Organization (CSCI-UA 201).
CSCI-UA.0310-001
(7948) Basic Algorithms Victor Shoup
Office Hours TR 11:00-12:15PM CIWW 109
Introduction to the study of algorithms. Presents two main themes: designing appropriate data structures and analyzing the efficiency of the algorithms that use them. Algorithms studied include sorting, searching, graph algorithms, and maintaining dynamic data structures. Homework assignments, not necessarily involving programming.

Prerequisites: Data Structures (CSCI-UA 102) and Discrete Mathematics (MATH-UA 120).
CSCI-UA.0310-003
(10203) Basic Algorithms Ioannis Tselekounis
Office Hours TR 3:30-4:45PM CIWW 102
Introduction to the study of algorithms. Presents two main themes: designing appropriate data structures and analyzing the efficiency of the algorithms that use them. Algorithms studied include sorting, searching, graph algorithms, and maintaining dynamic data structures. Homework assignments, not necessarily involving programming.

Prerequisites: Data Structures (CSCI-UA 102) and Discrete Mathematics (MATH-UA 120).
CSCI-UA.0310-006
(10273) Basic Algorithms - Recitation Min Jae Song T 3:30-4:45PM CIWW 109
Introduction to the study of algorithms. Presents two main themes: designing appropriate data structures and analyzing the efficiency of the algorithms that use them. Algorithms studied include sorting, searching, graph algorithms, and maintaining dynamic data structures. Homework assignments, not necessarily involving programming.

Prerequisites: Data Structures (CSCI-UA 102) and Discrete Mathematics (MATH-UA 120).
CSCI-UA.0310-007
(10629) Basic Algorithms - Recitation Ishan Agarwal T 12:30-1:45PM CIWW 201
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.0380-001
(7950) Topics of General Interest: Interactive Computing Craig Kapp
Office Hours TR 3:30-4:45PM 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: CSCI-UA.0002 and CSCI-UA.0004, or instructor permission.
CSCI-UA.0472-001
(10755) Artificial Intelligence Ernest Davis
Office Hours TR 9:30-10:45AM 60 Fifth Ave 150
Many cognitive tasks that people can do easily and almost unconsciously have proven extremely difficult to program on a computer. Artificial intelligence tackles the problem of developing computer systems that can carry out these tasks. Focus is on three central areas in AI: representation and reasoning, machine learning, and natural language processing.

Prerequisites: Computer Systems Organization (CSCI-UA 201) and Basic Algorithms (CSCI-UA 310).
CSCI-UA.0480-002
(9684) Special Topics: iOS Programming Nathan Hull
Office Hours TR 3:30-4:45PM CIWW 512

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

Prerequisites: CSCI-UA.0201 with a grade of C or better
CSCI-UA.0480-003
(9547) Special Topics: Data Management and Analysis Joseph Versoza
Office Hours TR 11:00-12:15PM 60 Fifth Ave 110

Extracting, transforming and analyzing data in myriad formats with traditional relational databases as well as non-relational databases. Data modeling, cloud databases, and API programming. Garnering insights using Python and current data analysis tools and libraries.

Prerequisites: CSCI-UA.0201 with a grade of C or better
CSCI-UA.0480-005
(9823) Special Topics: Large Scale Web Applications Yair Sovran
Office Hours T 6:20-8:50PM Silv 208

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

Prerequisites: CSCI-UA.0201
CSCI-UA.0480-006
(9828) Special Topics: Natural Language Processing Adam Meyers
Office Hours TR 8:00-9:15AM 60 Fifth Ave C10

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

Prerequisites: CSCI-UA.0201 with a grade of C or better
CSCI-UA.0480-009
(10296) Special Topics: Parallel Computing Mohamed Zahran
Office Hours TR 12:30-1:45PM CIWW 102

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

*

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.