Course Schedule

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• CSCI-GA.1144-​001
  (2248) PAC II*  Mohamed Zahran T 6:00-8:30PM ONLINE
  

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

  
  
  Prerequisites: CSCI-GA 1133 or departmental permission.
• CSCI-GA.1170-​001
  DS-GA.1170
  (2249) Fundamental Algorithms  Yevgeniy Dodis T 7:10-9:00PM ONLINE
  

  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-​011
  (22500) Programming Languages  Yuxin Deng
  Jing Liu T 1:15-3:05PM 16 Qi Xia 917 Additional information: Open to NYU Shanghai GoLocal students
  

  Discusses the design, use, and implementation of imperative, object-oriented, and functional programming languages. The topics covered include scoping, type systems, control structures, functions, modules, object orientation, exception handling, and concurrency. A variety of languages are studied, including C++, Java, Ada, Lisp, and ML, and concepts are reinforced by programming exercises.

  
  
  Prerequisites: Students taking this class should already have substantial programming experience.
• CSCI-GA.2110-​012
  (22501) Programming Languages Recitation  Yuxin Deng
  Jing Liu T 10:45-11:35AM 16 Qi Xia 917 Additional information: Open to NYU Shanghai GoLocal students
  

  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.2421-​001
  MATH-GA 2020-001
  (2256) Numerical Methods II  Leslie Greengard T 5:10-7:00PM ONLINE
  Numerical linear algebra. Approximation theory. Quadrature rules and numerical integration. Nonlinear equations and optimization. Ordinary differential equations. Elliptic equations. Iterative methods for large, sparse systems. Parabolic and hyperbolic equations.
  
  Prerequisites: Corequisite: linear algebra.
• CSCI-GA.3033-​004
  (22506) Special Topics: Statistical Natural Language Processing  Ankur Parikh T 5:10-7:00PM ONLINE
  

  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-​052
  (22507) Special Topics: Advanced Machine Learning  Mehryar Mohri T 5:10-7:00PM ONLINE
  

  This course introduces and discusses advanced topics in machine learning. The objective is both to present some key topics not covered by basic graduate ML classes such as Foundations of Machine Learning, and to bring up advanced learning problems that can serve as an initiation to research or to the development of new techniques relevant to applications.

• CSCI-GA.3033-​077
  (3050) Special Topics: Big Data and ML Systems  Aurojit Panda T 5:10-7:00PM ONLINE
  

  This class will discuss recent research into using cluster computing for data processing and machine learning. The focus of the course will be on understanding systems and performance challenges resulting from changing workloads, the emergence of new hardware (such as NVMe, SmartNICs, etc.), and the emergence of new security and privacy requirements, and understanding how systems address these challenges. The main focus of the course is on how these changes are exposed to programmers and users, and how they can be exploited for performance. Topics we plan to cover include:

   

  * How both commercial and research system are changing in response to changes in

    distributed storage including the wider adoption of blob stores like S3 and

    the availability of new hardware like Intel Optane.

   

  * How scheduling is impacted by the move to machine learning and reinforcement learning

    workloads.

   

  * How are people using serverless, and what technical challenges need to be addressed

    in these environments?

   

  * Tracing and debugging in cluster computing: how are people debugging both correctness

    and performance problems in these environments.

   

  * How are systems evolving to handle privacy requirements imposed by laws such as GDPR

    and CCPA?

   

  The class will require reading research papers, presenting papers, working on programming

  labs, and completing a significant final project.

  
  
  Prerequisites: The class does require an undergraduate-level knowledge in operating systems, programming languages, algorithms, linear algebra, probability and statistics. If you are new to these concepts, then this class may be advanced for you.
• CSCI-GA.3033-​091
  (22511) Special Topics: Introduction to Deep Learning Systems  Parijat Dube T 7:10-9:00PM ONLINE
  

  The course will cover several topics related to Deep Learning (DL) systems and their performance. 

  Both algorithmic and system related building blocks of DL systems will be covered including DL training algorithms, network architectures, and best practices for performance optimization. We will study hyperparameter choices, scalable distributed DL training, Kubernetes based DL system stack on cloud, tools and benchmarks for performance evaluation of DL systems, transfer learning etc. Emphasis will be on getting working knowledge of tools and techniques for performance evaluation of DL systems. The students will gain practical experience working on different stages of DL life cycle, including model development, testing, and deployment. The assignments will be mostly hands-on involving standard DL frameworks (Tensorflow, Pytorch) and open source technologies.

  
  
  Prerequisites: An introductory machine learning course. Knowledge of python is preferred but not necessary.
• CSCI-GA.3033-​256
  CS-GY.6923-SHAN
  (25936) Special Topics: Machine Learning  Bruno Abrahao T 1:15-3:15PM 1555 Century 206 Additional information: Open to NYU Shanghai GoLocal students
  

  Topics vary each semester.

  
  
  Prerequisites: Prerequisites vary according to topic.
• CSCI-GA.3850-​001
  (3437) PhD Seminar: Cryptography**  Yevgeniy Dodis T 12:30-3:15PM ONLINE
  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
  (9297) Intro To Computer Programming (No Prior Experience)  Michell Cardona TR 8:00-9:15AM ONLINE
  

  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
  (7611) Intro To Computer Programming (No Prior Experience)  David Gochfeld TR 9:30-10:45AM ONLINE
  

  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
  (8680) Intro To Computer Programming (No Prior Experience)  Saadia Lgarch TR 12:30-1:45PM ONLINE
  

  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
  (9298) Intro To Computer Programming (No Prior Experience)  Joshua Clayton TR 2:00-3:15PM ONLINE
  

  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
  (9660) Intro To Computer Programming (No Prior Experience)  Saadia Lgarch TR 3:30-4:45PM ONLINE
  

  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.0003-​001
  (9994) Intro to Computer Programming (Limited Prior Experience)  Hasan Aljabbouli TR 11:00-12:15PM ONLINE
  

  This course introduces object-oriented programming, recursion, and other important programming concepts to students who already have had some exposure to programming in the context of building applications using Python. Students will design and implement Python programs in a variety of applied areas.

  
  
  Prerequisites: This course is intended for students with limited programming experience who have not placed into CSCI-UA.0101. Students may not receive credit for both CSCI-UA.0002 and CSCI-UA.0003.
• CSCI-UA.0004-​002
  (7614) Intro to Web Design & Computer Principles  Adam Scher TR 8:00-9:15AM ONLINE
  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
  (7615) Database Design And Implementation  Amos Bloomberg TR 2:00-3:15PM ONLINE
  

  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-​001
  (8597) Web Development And Programming  Craig Kapp T 6:20-8:50PM ONLINE
  

  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-​002
  (7617) Intro To Computer Science  Hilbert Gene Locklear TR 9:30-10:45AM ONLINE
  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
  (9299) Intro To Computer Science  Sana Odeh TR 12:30-1:45PM ONLINE
  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-​006
  (8927) Intro To Computer Science  Anasse Bari TR 2:00-3:15PM ONLINE
  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
  (22971) Intro To Computer Science  Evan Korth TR 3:30-4:45PM ONLINE
  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-​003
  (7621) Data Structures  Anasse Bari TR 9:30-10:45AM ONLINE
  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-​062 Data Structures - Recitation  TBA T 8:00-9:15AM ONLINE Additional information: Online Recitation for Section 5
  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-​064 Data Structures - Recitation  TBA T 3:30-4:45PM ONLINE Additional information: Online Recitation for Section 5
  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-​002
  (7625) Computer Systems Organization - Recitation  TBA T 9:30-10:45AM 60 Fifth Ave C12 Additional information: In-person recitation for Section 1
  Covers the internal structure of computers, machine (assembly) language programming, and the use of pointers in high-level languages. Topics include the logical design of computers, computer architecture, the internal representation of data, instruction sets, and addressing logic, as well as pointers, structures, and other features of high-level languages that relate to assembly language. Programming assignments are in both assembly language and other languages.
  
  Prerequisites: Data Structures (CSCI-UA 102).
• CSCI-UA.0201-​003
  (9181) Computer Systems Organization  Allan Gottlieb TR 9:30-10:45AM ONLINE
  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-​006
  (9428) Computer Systems Organization - Recitation  TBA T 11:00-12:15PM CIWW 109 Additional information: In-person recitation for Section 5
  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-​021
  (22976) Computer Systems Organization - Recitation  TBA T 9:30-10:45AM ONLINE Additional information: Online Recitation for Section 1
  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-​061
  (22977) Computer Systems Organization - Recitation  TBA T 11:00-12:15PM ONLINE Additional information: Online Recitation for Section 5
  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-​002
  (9422) Operating Systems  Allan Gottlieb TR 3:30-4:45PM ONLINE
  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
  (7627) Basic Algorithms  Victor Shoup TR 12:30-1:45PM ONLINE
  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
  (22978) Basic Algorithms  Joel Spencer TR 8:00-9:15AM ONLINE
  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
  (9021) 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
  (8681) Topics of General Interest: Drawing on the Web  Joshua Clayton TR 9:30-10:45AM ONLINE
  Detailed descriptions available when topics are announced. Typical offerings include Computing in the Humanities and Arts and Introduction to Flash Programming. Does not count toward the computer science major.
  
  Prerequisites: Topics determine prerequisites.
• CSCI-UA.0476-​001
  (10054) Processing Big Data for Analytics Applications  Ann Malavet TR 12:30-1:45PM ONLINE
  

  Introduces platforms, tools, and architectures that facilitate scalable management and processing of vast quantities of data. Explores open source tools enabling the efficient acquisition, distributed storage, and processing of big data. Provides hands-on experience with distributed processing Apache solutions such as Hadoop MapReduce, HBase, Hive, Impala, Pig, core Spark, Spark SQL, and Spark Streaming. Other Apache big data tools covered are Sqoop, Oozie, Zookeeper, Flume, and Kafka.

  
  
  Prerequisites: (CSCI-UA 201) Computer Systems Organization and (CSCI-UA 310) Basic Algorithms. Familiarity with Linux commands and SQL will be helpful but is not required.
• CSCI-UA.0480-​034
  (9425) Special Topics: Applied Internet Technology  Joseph Versoza TR 9:30-10:45AM ONLINE
  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.
• CSCI-UA.0480-​042
  (7631) Special Topics: Computer Vision  Davi Geiger TR 3:30-4:45PM ONLINE
  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.
• CSCI-UA.0480-​057
  (9542) Special Topics: Natural Language Processing  Adam Meyers TR 9:30-10:45AM ONLINE
  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.

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