Course Schedule

Current semester Spring 2026, and future semesters are now available to view.

View undergraduate course grid View graduate course grid

Number

Name

Professor(s)

Meet Time

Room

CSCI-GA.2110-001
(7419) Programming Languages Cory Plock M 4:55-6:55PM CIWW 109

Course Description:

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
(7422) Compiler Construction Sam Westrick M 10:15-12:15PM GCASL 388

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

Prerequisites: CSCI-GA 1170, CSCI-GA 2110, and CSCI-GA 2250.
CSCI-GA.2250-001
(7423) Operating Systems Hubertus Franke M 2:45-4:45PM GCASL 383

Course Description:

The topics covered include the high-level design of key operating systems concepts such OS structures; process scheduling and synchronization; deadlocks and their prevention; memory management, including (demand) paging; and I/O and file systems. The concepts will be shown in the context of Unix/Linux. The learning is facilitated with labs that implement some of these key design principles and algorithms in C/C++.

Prerequisites: None
CSCI-GA.2262-001
(7425) Data Communications and Networks Jean-Claude Franchitti M 7:10-9:10PM 60 Fifth Ave 150

Course Description:

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
(12950) Numerical Methods II Michael O'Neil MW 11:00-12:15PM CIWW 1302

Course Description:

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.2572-001
DS-GA.1008-001
(23239) Deep Learning Alfredo Canziani
Yann LeCun M 4:55-6:55PM 60 Fifth Ave 150

Course Description:

This course concerns the latest techniques in deep learning and representation learning, focusing on supervised and unsupervised deep learning, embedding methods, metric learning, convolutional net and recurrent nets, with applications to computer vision, natural language understanding, and speech recognition.

Prerequisites: DS-GA 1001 Intro to Data Science or a graduate-level machine learning course.
CSCI-GA.3033-099
DS-GA 3001-009
(23398) Special Topics in DS: Introduction to Computer Vision Jean Ponce M 7:10-9:10PM 19W4 102

Course Description:

This course aims to cover broad topics in computer vision, and is not primarily a deep learning course. We will cover topics in traditional computer vision such as camera geometry, image formation, segmentation, object recognition, classification, and detection.
CSCI-GA.3033-107
(7455) Special Topics: Cryptography of Blockchains Benedikt Bünz M 12:30-2:30PM 60 Fifth Ave C10

Course Description:

Blockchains are distributed systems that are secured using consensus protocols, game theoretic incentives and cryptographic primitives. This course is a deep dive into the different cryptography that is used in blockchains. We will dive into different basic and advanced cryptographic primitives such as signatures, accumulators and merkle trees, threshold cryptography, zero-knowledge proofs, and others and explore how they are applied in the blockchain field.

Prerequisites: Strong mathematical background, Introductory cryptography (CSCI-GA.3210-001) or similar. No knowledge of blockchains is required. The course is mostly self-contained. Contact instructor if unsure.
CSCI-GA.3033-132
MATH-GA.2011-001
(22484) Special Topics: Iterative Methods for Systems of Equations Florian Schaefer M 4:55-6:55PM CIWW 317

Course Description:

This class covers a wide range of iterative methods for solving linear and nonlinear systems of equations. Among the topics covered are fixed-point iterations, splitting methods, Krylov subspace methods, (multigrid) preconditioners, and Newton-type methods. The class will present the mathematical underpinnings of these methods and use them, together with numerical experimentation, to study their properties.

Prerequisites: Numerical Methods I is preferred.
CSCI-GA.3140-001
(7469) Abstract Interpretation Patrick Cousot M 4:55-6:55PM 60 Fifth Ave 202

Course Description:

Many numerical or symbolic problems are very hard or even undecidable meaning that no computer algorithm can solve them exactly in reasonable time and memory space. This course introduces the latest techniques in abstract interpretation, a powerful framework for automatically calculating approximate solutions of such difficult problems. The main emphasis will be on software verification and automatic analysis with a wide range of applications from compilers to social networks.

Prerequisites: Some facility with logic, sets, linear algebra, graphs, formal languages, mathematical proofs, and programming languages is expected.
CSCI-UA.0002-001
(11090) Intro To Computer Programming (No Prior Experience) Craig Kapp MW 8:00-9:15AM CIWW 109

Course Description:

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
(11092) Intro To Computer Programming (No Prior Experience) Khye Borg Liew MW 8:00-9:15AM Online

Course Description:

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
(11094) Intro To Computer Programming (No Prior Experience) Jiri Motejlek MW 11:00-12:15PM CIWW 202

Course Description:

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
(11096) Intro To Computer Programming (No Prior Experience) Karl Rosenberg MW 12:30-1:45PM GCASL 269

Course Description:

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
(11098) Intro To Computer Programming (No Prior Experience) Khye Borg Liew MW 2:00-3:15PM Online

Course Description:

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 Intro To Computer Programming (No Prior Experience) CANCELLED MW 9:30-10:45AM

Course Description:

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
(11102) Intro to Web Design & Computer Principles Alvaro Olsen MW 8:00-9:15AM CIWW 101

Course Description:
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
(11104) Intro to Web Design & Computer Principles Mark Ramos MW 11:00-12:15PM CIWW 312

Course Description:
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
(11107) Intro to Web Design & Computer Principles Alvaro Olsen MW 3:30-4:45PM GCASL 361

Course Description:
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.0061-001
(11109) Web Development And Programming Craig Kapp MW 2:00-3:15PM 194M 206

Course Description:

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 Intro To Computer Science CANCELLED MW 8:00-9:15AM

Course Description:

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
(11113) Intro To Computer Science Tobias Blickhan MW 9:30-10:45AM 60 Fifth Ave 110

Course Description:

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
(11116) Intro To Computer Science Hilbert Gene Locklear MW 12:30-1:45PM GCASL 279

Course Description:

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

Prerequisites: Introduction to Computer Programming (No Prior Experience) (CSCI-UA 2) or Introduction to Computer Programming (Limited Prior Experience) (CSCI-UA 3), or a score of 3 on the AP Computer Science exam (scores of 4 and 5 are acceptable prerequisites for students who wish to take CSCI-UA 101 before entering CSCI-UA 102; they will forfeit the AP credit), or departmental permission assessed by placement exam.
CSCI-UA.0101-008
(11118) Intro To Computer Science Candido Cabo MW 2:00-3:15PM Silv 208

Course Description:

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.0101-010
(11120) Intro To Computer Science Gezim Hakramaj MW 3:30-4:45PM CIWW 101

Course Description:

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.0102-010
(11122) Data Structures Joanna Klukowska MW 9:30-10:45AM CIWW 109

Course Description:

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.0102-040
(11150) Data Structures Romain Cosson MW 11:00-12:15PM CIWW 317

Course Description:

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.0102-060
(11158) Data Structures Alan Amin MW 12:30-1:45PM CIWW 317

Course Description:

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
(11166) Computer Systems Organization Douglas Moody MW 9:30-10:45AM CIWW 101

Course Description:

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
(11172) Computer Systems Organization Alexander Johnson MW 3:30-4:45PM Silv 411

Course Description:

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

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

Prerequisites: CSCI-UA.0102
CSCI-UA.0201-007
(11176) Computer Systems Organization Jinyang Li MW 2:00-3:15PM CIWW 109

Course Description:

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
(11951) Operating Systems Michael Walfish MW 11:00-12:15PM CIWW 109

Course Description:

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
(11952) Basic Algorithms Nir Bitansky MW 9:30-10:45AM 19UP 102

Course Description:

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
(11187) Basic Algorithms Amir Abboud MW 12:30-1:45PM GCASL 383

Course Description:

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.0310-007
(11191) Basic Algorithms CANCELLED MW 3:30-4:45PM

Course Description:

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

Prerequisites: Data Structures (CSCI-UA 102); Discrete Mathematics (MATH-UA 120); and either Calculus I (MATH-UA 121) OR Mathematics for Economics I (MATH-UA 211).
CSCI-UA.0380-001
(11203) Topics of General Interest: Drawing on the Web Joshua Clayton MW 3:30-4:45PM CIWW 312

Course Description:

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, CSCI-UA.0004
CSCI-UA.0467-002
(11233) Applied Internet Technology Joseph Versoza MW 12:30-1:45PM CIWW 109

Course Description:

Applied Internet Technology is a practical introduction to creating modern web applications. It covers full-stack (that is, every aspect of building a database driven web application: server programming, database implementation, frontend markup, styling and interactivity) web development. It includes topics such as database and data model design, web application architecture, separation of logic and presentation, handling user input and processing form data, managing asynchronous processes, strategies for creating real-time web applications, and handling client-side interactivity. Students will use current server and client-side web frameworks and libraries to build dynamic, data-driven sites. Various applications to support development will also be introduced, such as version control, static analysis tools, and build systems.

Prerequisites: Computer Systems Organization (CSCI-UA 201). Students who complete Applied Internet Technology (CSCI-UA 467) with a C or better are not eligible to take Web Development and Programming (CSCI-UA 61).
CSCI-UA.0470-001
(11209) Object Oriented Programming Hasan Aljabbouli MW 9:30-10:45AM Online

Course Description:

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.0472-001
(11953) Artificial Intelligence Ernest Davis MW 11:00-12:15PM Online

Course Description:
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.0473-001
(11956) Fundamentals of Machine Learning Kyunghyun Cho MW 11:00-12:15PM GCASL C95

Course Description:

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 185). Students may take any of the following courses in place of MATH-UA 185: Theory of Probability (MATH-UA 333), Mathematical Statistics (MATH-UA 334), Honors Theory of Probability (MATH-UA 338) OR Data Analysis (MA-UY 2224).
CSCI-UA.0475-001
(11229) Predictive Analytics Ahmad Emad MW 8:00-9:15AM GCASL 361

Course Description:

Predictive analytics is the art and science of extracting useful information from historical data and present data for the purpose of predicting future trends. In this course, students will be introduced to the phases of the analytics life-cycle and will gain an understanding of a variety of tools and machine learning algorithms for analyzing data and discovering forward insights. Several techniques will be introduced including: data preprocessing techniques, data reduction algorithms, data clustering algorithms, data classification algorithms, uplifting algorithms, association rules, data mining algorithms, recommender systems, and more. This course aims to provide students with skills of the new generation of data scientists that will allow them to structure, analyze and derive useful insights from data that could help make better decisions.

Prerequisites: Computer Systems Organization (CSCI-UA 201), Basic Algorithms (CSCI-UA 310), and Linear Algebra (MATH-UA 140) or Honors Linear Algebra (MATH-UA 148).
CSCI-UA.0479-001
(11961) Data Management and Analysis Joseph Versoza MW 11:00-12:15PM CIWW 101

Course Description:

Extracting, transforming and analyzing data in myriad formats. Using traditional relational databases as well as non-relational databases to store, manipulate, and query data. Students write custom programs, create queries, and use data analysis tools and libraries on a wide array of data sets. Additional topics: data modeling, cloud databases and API programming.

Prerequisites: Data Structures (CSCI-UA 102). Students that complete Data Management and Analysis (CSCI-UA 479) with a C or better are not eligible to take Database Design and Implementation (CSCI-UA 60).
CSCI-UA.0479-003
(11962) Data Management and Analysis Matthew Zeidenberg MW 3:30-4:45PM 60 Fifth Ave 150

Course Description:

Extracting, transforming and analyzing data in myriad formats. Using traditional relational databases as well as non-relational databases to store, manipulate, and query data. Students write custom programs, create queries, and use data analysis tools and libraries on a wide array of data sets. Additional topics: data modeling, cloud databases and API programming.

Prerequisites: Data Structures (CSCI-UA 102). Students that complete Data Management and Analysis (CSCI-UA 479) with a C or better are not eligible to take Database Design and Implementation (CSCI-UA 60).
CSCI-UA.0480-061
(11217) Special Topics: Open Source Software Development Joanna Klukowska MW 12:30-1:45PM 60 Fifth Ave 110

Course Description:

This course prepares students to become active participants in open source projects. It begins with an overview of the philosophy and brief history of open source development, followed by an in-depth look at different types of open source projects and the study of various tools involved in open source development. In particular, it covers the collaborative nature of open source projects, community structure, version control systems, licensing, intellectual property, types of contributions (programming and non-programming) and the tool-chains that enable such contributions. The students are expected to contribute to existing open source projects.

Prerequisites: CSCI-UA.0201
CSCI-UA.0480-062
(17479) Special Topics: Computer Networks Jinkun Geng MW 3:30-4:45PM 194M 206

Course Description:

This course will introduce students to computer networks, using today's Internet as an example. Topics covered include socket programming, routing, forwarding, reliable transmission, congestion control, and medium access control. The course will involve a good deal of programming in Python. Familiarity with programming, algorithms, and basic probability is expected. Prerequisites: Computer Systems Organization (CSCI-UA 201), Basic Algorithms (CSCI-UA.0310), and Discrete Mathematics (Math UA 120); or permission of the department.

Prerequisites: CSCI-UA.0201
CSCI-UA.0480-076
(17344) Special Topics: Technology, Law, and Policy CANCELLED MW 3:30-4:45PM

Course Description:
Detailed course descriptions are available when advanced topics are announced each semester. Typical offerings include, but are not limited to, Bioinformatics, Building Robots, Computer Graphics, Machine Learning, Network Programming, Computer Vision, and Multimedia for Majors.

Prerequisites: Topics determine prerequisites.

*

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.