Course Schedule

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• CSCI-GA.1120-​001
  (3190) Introduction to Programming****  CANCELLED -
  

  This course introduces students to the fundamentals of computer programming as students design, write, and debug computer programs using the programming language Python. No knowledge of programming is assumed. Not open to graduate Computer Science, Information Systems, Mathematics or Scientific Computing students. For registration, please contact dhss@nyu.edu.

• CSCI-GA.1121-​001
  (3191) Working with Data****  CANCELLED -
  

  Students study the principles of relational database design and learn to build, populate, manipulate and query databases using SQL on datasets relevant to their interests. Students will also explore data presentation through data visualization. Not open to Graduate Computer Science, Information Systems, Mathematics or Scientific Computing students. For registration, please contact dhss@nyu.edu.

• CSCI-GA.1133-​001
  (2277) PAC I*  Evan Korth 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.1133-​002
  (2733) PAC I Recitation  Nolan Filter W 7:10-8:00PM 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
  (2278) Fundamental Algorithms  Alan Siegel 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.1170-​002
  DS-GA.1170
  (2279) Fundamental Algorithms Recitation  Alan Siegel R 5:10-6:00PM CIWW 109
  

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

  
  
  Prerequisites: At least one year of experience with a high-level language such as Pascal, C, C++, or Java; and familiarity with recursive programming methods and with data structures (arrays, pointers, stacks, queues, linked lists, binary trees).
• CSCI-GA.1170-​003
  DS-GA.1170
  (3131) Fundamental Algorithms  Alexander Alekseyev W 5:10-7:00PM CIWW 517
  

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

  
  
  Prerequisites: At least one year of experience with a high-level language such as Pascal, C, C++, or Java; and familiarity with recursive programming methods and with data structures (arrays, pointers, stacks, queues, linked lists, binary trees).
• CSCI-GA.1170-​004
  DS-GA.1170
  (3132) Fundamental Algorithms Recitation  Sreyas Mohan F 6:10-7:00PM CIWW 517
  

  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.1180-​001
  (19698) Mathematical Techniques For CS Applications  Remi Imbach M 5:10-7:00PM CIWW 512
  An introduction to theory, computational techniques, and applications of linear algebra, probability and statistics. These three areas of continuous mathematics are critical in many parts of computer science, including machine learning, scientific computing, computer vision, computational biology, natural language processing, and computer graphics. The course teaches a specialized language for mathematical computation, such as Matlab, and discusses how the language can be used for computation and for graphical output. No prior knowledge of linear algebra, probability, or statistics is assumed.
• CSCI-GA.2110-​001
  (2280) Programming Languages  Thomas Wies W 5:10-7:00PM CIWW 109
  

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

  
  
  Prerequisites: Students taking this class should already have substantial programming experience.
• CSCI-GA.2110-​002
  (2281) Programming Languages Recitation  Zvonimir Pavlinovic R 6:10-7:00PM CIWW 109
  

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

  
  
  Prerequisites: Students taking this class should already have substantial programming experience.
• CSCI-GA.2110-​003
  (2886) Programming Languages  Cory Plock M 5:10-7:00PM CIWW 312
  

  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-​004
  (2742) Programming Languages Recitation  Stephanie Carrera F 5:10-6:00PM Wav 366
  

  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.2112-​001
  MATH-GA 2043-001
  (2282) Scientific Computing   Jonathan Goodman R 5:10-7:00PM CIWW 1302
  Methods for numerical applications in the physical and biological sciences, engineering, and finance. Basic principles and algorithms; specific problems from various application areas; use of standard software packages.
  
  Prerequisites: Multivariate calculus and linear algebra. Some programming experience recommended.
• CSCI-GA.2130-​001
  (19699) Compiler Construction  Eva Rose R 5:10-7:00PM CIWW 312
  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
  (2283) Operating Systems  Hubertus Franke M 7:10-9:00PM CIWW 1302
  The topics covered include a review of linkers and loaders and the high-level design of key operating systems concepts such as process scheduling and synchronization; deadlocks and their prevention; memory management, including (demand) paging and segmentation; and I/O and file systems, with examples from Unix/Linux and Windows. Programming assignments may require C, C++, Java, or C#.
• CSCI-GA.2262-​001
  (2753) Data Communications and Networks  Jean-Claude Franchitti R 7:10-9:00PM CIWW 312
  

  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.2270-​001
  (2953) Computer Graphics   Daniele Panozzo M 7:10-9:00PM 194M 307
  

  Problems and objectives of computer graphics. Vector, curve, and character generation. Interactive display devices. Construction of hierarchical image list. Graphic data structures and graphics languages. Hidden-line problems; windowing, shading, and perspective projection. Curved surface generation display.

  
  
  Prerequisites: CSCI-GA 1170 and CSCI-UA 140 (or an equivalent undergraduate course in linear algebra).
• CSCI-GA.2271-​001
  (2887) Computer Vision   Rob Fergus R 7:10-9:00PM Silv 405
  

  Basic techniques of computer vision and image processing. General algorithms for image understanding problems. Study of binary image processing, edge detection, feature extraction, motion estimation, color processing, stereo vision, and elementary object recognition. Mathematical, signal processing, and image processing tools. Relation of computer vision algorithms to the human visual system.

  
  
  Prerequisites: CSCI-GA 1170
• CSCI-GA.2274-​001
  (3069) Advanced Computer Graphics  Kenneth Perlin T 7:10-9:00PM 60 Fifth Ave 261
  

  This is a capstone course based on computer graphics tools. The course covers a selection of topics that may include computer animation, gaming, geometric modeling, motion capture, computational photography, physically based simulation, scientific visualization, and user interfaces. Not all areas are available every semester; the choice of areas is determined by the instructor. The capstone project involves 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, CSCI-GA 2250 and CSCI-GA 2270
• CSCI-GA.2420-​001
  MATH-GA 2010-001
  (2284) Numerical Methods I   Michael Overton M 5:10-7:00PM CIWW 1302
  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.2433-​001
  DS-GA.2433-001
  (2749) Database Systems  Zvi Kedem M 5:10-7:00PM CIWW 109
  Database system architecture. Modeling an application and logical database design. The relational model and relational data definition and data manipulation languages. Design of relational databases and normalization theory. Physical database design. Concurrency and recovery. Query processing and optimization.
• CSCI-GA.2434-​001
  (2285) Advanced Database Systems  Dennis Shasha 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.2566-​001
  (2888) Foundations Of Machine Learning  Mehryar Mohri T 5:10-7:00PM CIWW 102
  

  This course introduces the fundamental concepts and methods of machine learning, including the description and analysis of several modern algorithms, their theoretical basis, and the illustration of their applications. Many of the algorithms described have been successfully used in text and speech processing, bioinformatics, and other areas in real-world products and services. The main topics covered are probability and general bounds; PAC model; VC dimension; perceptron, Winnow; support vector machines (SVMs); kernel methods; decision trees; boosting; regression problems and algorithms; ranking problems and algorithms; halving algorithm, weighted majority algorithm, mistake bounds; learning automata, Angluin-type algorithms; and reinforcement learning, Markov decision processes (MDPs).

  
  
  Prerequisites: CSCI-GA 1180.
• CSCI-GA.2630-​001
  (19693) Foundations of Networks and Mobile Systems  Lakshminarayanan Subramanian T 5:10-7:00PM CIWW 317 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
  (21875) Foundations of Networks and Mobile Systems Lab  Lakshminarayanan Subramanian T 7:10-8:00PM CIWW 317 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.2820-​001
  (19694) DevOps and Agile Methodologies  John Rofrano W 5:10-7:00PM CIWW 102
  

  This course uses a project­ based learning approach towards the study of DevOps as a cultural change in Information Technology organizations, and the supporting development tools and automation technologies required to implement it successfully. Students study the principles of DevOps, and as part of an agile development team, each student is involved in planning, designing, building, testing, and deploying one or more cloud native microservices into a Platform as a Service cloud by utilizing a DevOps Pipeline that they will create.

• CSCI-GA.2820-​002
  (21876) DevOps and Agile Methodologies Lab  John Rofrano W 7:10-8:00PM CIWW 102
  

  This course uses a project­ based learning approach towards the study of DevOps as a cultural change in Information Technology organizations, and the supporting development tools and automation technologies required to implement it successfully. Students study the principles of DevOps, and as part of an agile development team, each student is involved in planning, designing, building, testing, and deploying one or more cloud native microservices into a Platform as a Service cloud by utilizing a DevOps Pipeline that they will create.

• CSCI-GA.2830-​001
  (19695) The Lean Launch Pad  Evan Korth
  Frank Rimalovski R 10:00-12:00PM 16WP 106 Additional information: Open only to students in the MS-CEI program.
  

  This course is based on Steve Blank’s Lean LaunchPad curriculum. This course provides real world, hands­ on learning on what it’s like to actually start a high­ tech company. This is a practical class – essentially a lab, not a theory or “book” class. The goal, within the constraints of a classroom and a limited amount of time, is to create an entrepreneurial experience for students with all of the pressures and demands of the real world in an early stage start up. Students will talk to customers, partners, competitors, as they encounter the chaos and uncertainty of how a startup actually works. They will work in teams learning how to turn a great idea into a great company. They will learn how to use a business model to brainstorm each part of a company and customer development to get out of the classroom to see whether anyone would want/use their product. Finally, based on the customer and market feedback gathered, students will use agile development to rapidly iterate their products to build something customers would actually use and buy. Each day will be a new adventure outside the classroom as students test each part of their business model and then share the hard earned knowledge with the rest of the class.

• CSCI-GA.2830-​002
  (21877) The Lean Launch Pad Lab  Andrew Dempsey R 12:10-1:00PM 16WP 106 Additional information: Open only to students in the MS-CEI program.
  

  This course is based on Steve Blank’s Lean LaunchPad curriculum. This course provides real world, hands­ on learning on what it’s like to actually start a high­ tech company. This is a practical class – essentially a lab, not a theory or “book” class. The goal, within the constraints of a classroom and a limited amount of time, is to create an entrepreneurial experience for students with all of the pressures and demands of the real world in an early stage start up. Students will talk to customers, partners, competitors, as they encounter the chaos and uncertainty of how a startup actually works. They will work in teams learning how to turn a great idea into a great company. They will learn how to use a business model to brainstorm each part of a company and customer development to get out of the classroom to see whether anyone would want/use their product. Finally, based on the customer and market feedback gathered, students will use agile development to rapidly iterate their products to build something customers would actually use and buy. Each day will be a new adventure outside the classroom as students test each part of their business model and then share the hard earned knowledge with the rest of the class.

• CSCI-GA.2945-​001
  MATH-GA.2011-001
  (2286) Adv Topics Num. Analysis: Computational Inverse Problems  Georg Stadler W 5:10-7:00PM CIWW 202
  Topics vary each semester.
  
  Prerequisites: Topics determine prerequisites.
• CSCI-GA.2945-​002
  MATH-GA.2011-002
  (3120) Adv Topics Num. Analysis: TBA  Lloyd N. Trefethen T 1:25-3:15PM CIWW 512
  Topics vary each semester.
  
  Prerequisites: Topics determine prerequisites.
• CSCI-GA.2945-​004
  MATH-GA.2011-003
  (23367) Adv Topics Num. Analysis: Computational Fluid Dynamics  Aleksandar Donev R 3:20-5:05PM CIWW 1302
  Topics vary each semester.
  
  Prerequisites: Topics determine prerequisites.
• CSCI-GA.2965-​001
  (2287) Heuristic Problem Solving  Dennis Shasha M 5:10-7:00PM CIWW 517
  This course revolves around several problems new to computer science (derived from games or puzzles in columns for Dr. Dobb’s Journal, Scientific American, and elsewhere). The idea is to train students to face a new problem, read relevant literature, and come up with a solution. The solution entails winning a contest against other solutions. The winner receives candy. The best solutions become part of an evolving “Omniheurist” Web site that is expected to get many visitors over the years. The course is for highly motivated, mathematically adept students. It is open to supported Ph.D. students and well-qualified master’s students. Class size has been around 10 in the past, and instructor and students have all gotten to know one another very well. Algorithmic and programming knowledge is the main prerequisite. It also helps to be familiar with a rapid prototyping language such as Matlab, Mathematica, K, or Python, or to be completely fluent in some other language.
  
  Prerequisites: CSCI-GA 1170 and an ability to prototype algorithms rapidly.
• CSCI-GA.3033-​001
  (2288) Special Topics: Production Quality Software  Michael Schidlowsky W 5:10-7:00PM CIWW 317
  

  In this course we study the craft of software engineering holistically. The semester begins with a thorough review of Java and the Java Virtual Machine. We concentrate on library components and language features that are most commonly used.  Later lectures cover more advanced topics including concurrency and thread-safety, object-oriented programming, design patterns, and testing. The course also covers non-technical topics critical to software development like developing and reinforcing salutary engineering habits, communicating effectively, and addressing issues of productivity and drive in engineering teams.  Lessons are reinforced with bi-weekly assignments that are carefully graded with the aim of providing as much critical feedback as possible.  Some student submissions are critiqued in classroom code reviews.

• CSCI-GA.3033-​002
  (2289) Special Topics: Distributed Systems  Aurojit Panda W 7:10-9:00PM CIWW 101
  

  Large-scale distributed systems lie at the core of application domains such as cloud computing, internet of things, large multiplayer games, etc. These application domains make use of systems such as distributed databases (e.g., Google's Spanner, Amazon's Dynamo, etc.), large scale analytics frameworks (e.g., Hadoop, Spark and TensorFlow), distributed locking systems (e.g., Paxos, etcd, etc.), and others. In this class we will look at how to construct these distributed systems, in particular looking at why this is more complex than building applications running on a single machine, and present abstraction and design techniques for building distributed systems. We will focus on a solving a variety of common problems in these systems including consensus, consistency, naming, fault tolerance, etc.

  This is a graduate-level course, but undergraduates are welcome! The course itself will consist of a series of lectures and will require reading research papers.

  This class satisfies the Ph.D. breadth requirement in Systems and also serves as a M.S. capstone course.

  
  
  Prerequisites: 1. Undergraduate Operating Systems or Computer Systems Organization; 2. programming experience; 3. mathematical maturity or the willingness to work through simple proofs.
• CSCI-GA.3033-​004
  (2291) Special Topics: Graphics Processing Units (GPUs): Architecture & Programming  Mohamed Zahran W 5:10-7:00PM CIWW 201
  

  In this course, we will cover architectural aspects and capabilities of modern GPUs (graphics processing unit) and will learn the architecture and the programming of GPUs to solve different type of problems. Many computations can be performed much faster on the GPU than on a traditional processor. This is why GPUs are present now in almost all computers; and the majority of Top 500 supercomputers in the world are built around GPUs. GPUs are no longer restricted to graphics applications but are now used for a diverse set of applications and domains. This introduces the concept of general-purpose GPUs or GPGPUs, which is the main subject of this course. This course serves as a capstone for the MSCS program.

• CSCI-GA.3033-​006
  (2292) Special Topics: Realtime and Big Data Analytics  Suzanne McIntosh R 7:10-9:00PM CIWW 102
  

  This course will introduce technologies at the foundation of the Big Data movement that have facilitated scalable management of vast quantities of data collected through realtime and near realtime sensing. We will also explore the tools enabling the acquisition of near realtime data in the social domain, the fusion of those data when in flight and at rest, and their meaningful representation in graphical visualizations. Students are required to complete weekly reading and/or programming assignments and demonstrate mastery of course topics by developing and demonstrating an analytics project of their choosing. Class time will be set aside for project proposal and final demo.

  
  
  Prerequisites: CSCI-GA 2250 or equivalent Operating Systems course; programming experience in C/C++, Java, or Python for assignments and final project; CSCI-GA 2262, CSCI-GA 2620, or undergraduate course in networks. A familiarity with databases and Linux will be useful.
• CSCI-GA.3033-​008
  (2955) Special Topics: Statistical Natural Language Processing  Ankur Parikh 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 rich, structured models for syntactic parsing, machine translation, and question answering. 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 and how to design efficient systems for practical user applications. This course assumes a good background in basic probability as well as interest in building real systems.

• CSCI-GA.3033-​011
  (3031) Special Topics: Predictive Analytics  Anasse Bari W 7:10-9:00PM CIWW 202
  

  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 have an introduction to the phases of the analytics lifecycle and a basic understanding of a variety of tools and machine learning techniques to analyze data to discover forward insights. Several techniques will be introduced; including data pre-processing techniques, data clustering algorithms, data classification algorithms, association rules data mining algorithms, recommender systems, etc.

  Applications from bio-informatics, social networks analytics, and text mining will be covered. Highlights from industrial use cases will be covered to demonstrate how Predictive Analytics relates to improving business performance and impacting better decisions. This is an introductory course that will provide students with basic 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.

• CSCI-GA.3033-​012
  (3029) Special Topics: Vision Meets Machine Learning  Davi Geiger R 5:10-7:00PM CIWW 201
  

  The course will introduce basic ideas of Multiscale Image Representations (Wavelets - Affine Groups) and Machine Learning (Deep Learning with Variational Auto Encoders, GAN, RNN). Then, the course will be "hands on", with small groups programming/developing projects that integrate the basic ideas above to perform "computer vision tasks" (the evaluation is based on projects). The tasks will be in the topics of Motion, Scene Segmentation, Object Classification, Human Actions.

  
  
  Prerequisites: Students who take this class should have familiarity with linear algebra, probability, and calculus.
• CSCI-GA.3033-​017
  (3147) Special Topics: Multicore Programming  Christopher Mitchell M 7:10-9:00PM CIWW 512
  

  Through the 1990s, processors got faster and faster, but around the turn of the millennium, CPUs started to reach physical limits. To drive innovation and produce more powerful computers, manufacturers began to pack multiple cores into each processor. However, most software is conceived by the programmer as a linear progression of instructions. Compilers can find some parallelization opportunities, but that’s not enough to take full advantage of multiple cores. Programmers must take much of the responsibility for making their programs exploit multiple cores, and this course discusses many modern techniques:

  • Aspects of the architecture of modern machines
  • Classic and modern algorithms for coordination and synchronization
  • Data structures that exploit and extract performance from multiple cores
  • Current and future programming techniques and best practices for multiple cores
  • Strategies to debug and benchmark multi-threaded programs

  Students will be expected to have experience with a programming-intensive course. Students must have previous experience with C++, but no experience writing multi-threaded C++ programs is necessary. The course will include lectures, homework, cumulative labs, a final project, and a midterm and final exam.

• CSCI-GA.3033-​019
  (3193) Special Topics: Cryptocurrencies and Decentralized Ledgers  Joseph Bonneau T 7:10-9:00PM Silv 208
  

  Bitcoin, Ethereum, and other systems using decentralized ledgers (blockchains) have quickly grown to valuations of hundreds of billions of dollars. Their future potential has captured the imagination of researchers working on applications as diverse as banking and finance, voting, law, corporate governance, gambling and online gaming. This course will cover the technical concepts underlying these systems: append-only ledgers, decentralized consensus, smart contracts and zero-knowledge proof systems. Students will gain working knowledge of both Bitcoin and Ethereum through practical assignments. The course will also survey the wide variety of potential future applications.

  
  
  Prerequisites: At least one year of experience with a high-level language such as Pascal, C, C++, or Java. An undergraduate course in cryptography or successful completion of CSCI-GA.3205 or CSCI-GA.3210 strongly recommended.
• CSCI-GA.3033-​020
  (3194) Special Topics: Practical Computer Security  Thitima Srivatanakul W 7:10-9:00PM CIWW 317
  

  This course teaches the security mindset and practical security concepts that are essential for software engineers, software developers, quality assurance testers and IT managers. The course discusses various attack techniques and defenses for real world applications and the security activities in the SDLC. Its main topics include: low-level exploits, web application security, malware, threat modeling, security requirements, secure coding practices, security & penetration testing, human factors and usability, mobile platform security, and legal and ethical issues. Course project and assignments may require Java, C, and/or scripting languages.

  
  
  Prerequisites: Programming experience in C/C++, Java and Javascript, and SQL; basic understanding of assembly language; working knowledge of web application development.
• CSCI-GA.3033-​021
  (21502) Special Topics: Machine Learning for Healthcare  Rajesh Ranganath T 7:10-9:00PM CIWW 312
  

  The course covers machine learning methods important for healthcare including causal inference, k-shot learning, time series models, and fairness. We will learn about important clinical questions and the data (such as from ICU monitors and imaging) that along with machine learning can help answer these questions. We will focus on recent work in machine learning for healthcare.

  
  
  Prerequisites: CSCI-GA 2567/DS-GA 1003 Machine Learning; Basic knowledge of probability theory, statistics, and neural networks
• CSCI-GA.3033-​022
  (22529) Special Topics: High Performance Machine Learning  Alessandro Morari
  Giacomo Domeniconi R 7:10-9:00PM CIWW 201
  

  The field of High Performance Computing (HPC) is focused on the design and development of algorithms, methodologies, software and hardware to solve some of the biggest challenges in science. HPC is where cutting edge technology (GPUs, low latency interconnects, etc.) is applied to the solution of scientific and data-driven problems. One of the key ingredients to the current success of ML is the ability to perform computations on very large amounts of training data. Today, the application of HPC techniques to ML algorithms is a fundamental driver for the progress of Artificial Intelligence.  In this course, you will learn HPC techniques that are typically applied to supercomputing software, and how they are applied to obtain the maximum performance out of ML algorithms.
  
  Prerequisites:

  • Operating Systems and Computer Architecture: CSCI-GA 2250 or good understanding of Computer Architecture, C/C++ programming, OS design, process stack/heap, threads, file-system, IO, Networks.
  • Python and C languages: good programming skills in Python and C.
  • Machine Learning and Neural Networks Algorithms: The course is focused on the performance rather than the algorithmic aspects. A basic explanation of the algorithms will be part of the course. However, it is strongly recommended to start the course with a basic understanding of the following algorithms: logistic regression, neural networks, convolutional neural networks.

  Suggested resources:

  • Logistic Regression - tutorial
  • Neural Networks - short manuscript
  • Convolutional Neural Networks - tutorial
• CSCI-GA.3110-​001
  (3312) Honors Programming Languages  Patrick Cousot TR 3:30-4:45PM 60 Fifth Ave C15
  The course will introduce a panorama of programming languages concepts underlying the main programming language paradigms (such as imperative, functional, object-oriented, logic, concurrent, and scripting languages) and present in detail the formal methods (code semantics, specification, and verification) used in modern high quality assurance tools for software safety and security. A programming project (design and implementation of an interpreter/compiler for an dynamic object-oriented mini-language) will be programmed in OCaml, a multiparadigm language introduced at the beginning of the course.
  
  Prerequisites: Permission of the instructor for master’s students
• CSCI-GA.3205-​001
  (19700) Applied Cryptography & Network Security  Zvi Kedem W 5:10-7:00PM CIWW 101
  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.3210-​001
  MATH-GA 2170-001
  (2768) Introduction To Cryptography  Oded Regev M 11:00-12:50PM CIWW 512
  The primary focus of this course is on definitions and constructions of various cryptographic objects, such as pseudorandom generators, encryption schemes, digital signature schemes, message authentication codes, block ciphers, and others, time permitting. The class tries to understand what security properties are desirable in such objects, how to properly define these properties, and how to design objects that satisfy them. Once a good definition is established for a particular object, the emphasis will be on constructing examples that provably satisfy the definition. Thus, a main prerequisite of this course is mathematical maturity and a certain comfort level with proofs. Secondary topics, covered only briefly, are current cryptographic practice and the history of cryptography and cryptanalysis.
  
  Prerequisites: Strong mathematical background
• CSCI-GA.3520-​001
  (2294) Honors Analysis of Algorithms  Subhash Khot TR 9:30-10:45AM CIWW 317
  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.3812-​001
  (2295) Information Technology Projects *  Jean-Claude Franchitti M 6:10-9:10PM CIWW 317
  

  This is a capstone course that connects students directly with real-world information technology problems. The goal of this course is to teach the skills needed for success in real-world information technology via a combination of classroom lectures and practical experience with large projects that have been specified by local “clients.” The typical clients are primarily companies, but can also be government agencies or nonprofit organizations. Each project lasts for the entire semester and is designed to involve the full software project life cycle. Examples of such projects are development of software to solve a business problem, including specifying requirements, writing and testing prototype code, and writing a final report; and evaluation of commercial software to be purchased to address a business problem, including gathering requirements, designing an architecture to connect the new software with existing systems, and assessing the suitability of available software products.

  
  
  Prerequisites: For MS in IS students: Successful completion of CSCI-GA 1170 Fundamental Algorithms and two of the following three courses: CSCI-GA 2262 Data Communications & Networks; CSCI-GA 2250 Operating Systems; CSCI-GA 2433 Database Systems. For MS in CS students: Successful completion of CSCI-GA 1170 Fundamental Algorithms, CSCI-GA 2110 Programming Languages, and CSCI-GA 2250 Operating Systems. PERMISSION OF THE DEPARTMENT REQUIRED.
• CSCI-GA.3813-​001
  (2296) Adv Lab MS *  STAFF -
  

  Large-scale programming project or research in cooperation with a faculty member.

  
  
  Prerequisites: Permission of the faculty project supervisor and the Director of Graduate Studies.
• CSCI-GA.3813-​002
  (2297) Adv Lab MS *  STAFF -
  

  Large-scale programming project or research in cooperation with a faculty member.

  
  
  Prerequisites: Permission of the faculty project supervisor and the Director of Graduate Studies.
• CSCI-GA.3813-​003
  (2298) Adv Lab MS *  STAFF -
  

  Large-scale programming project or research in cooperation with a faculty member.

  
  
  Prerequisites: Permission of the faculty project supervisor and the Director of Graduate Studies.
• CSCI-GA.3813-​004
  (2299) Adv Lab MS *  STAFF -
  

  Large-scale programming project or research in cooperation with a faculty member.

  
  
  Prerequisites: Permission of the faculty project supervisor and the Director of Graduate Studies.
• CSCI-GA.3813-​005
  (2300) Adv Lab PhD **  STAFF -
  

  Large-scale programming project or research in cooperation with a faculty member.

  
  
  Prerequisites: Permission of the faculty project supervisor and the Director of Graduate Studies.
• CSCI-GA.3813-​006
  (2301) Adv Lab PhD **  STAFF -
  

  Large-scale programming project or research in cooperation with a faculty member.

  
  
  Prerequisites: Permission of the faculty project supervisor and the Director of Graduate Studies.
• CSCI-GA.3813-​007
  (2302) Adv Lab PhD **  STAFF -
  

  Large-scale programming project or research in cooperation with a faculty member.

  
  
  Prerequisites: Permission of the faculty project supervisor and the Director of Graduate Studies.
• CSCI-GA.3813-​008
  (2303) Adv Lab PhD **  STAFF -
  

  Large-scale programming project or research in cooperation with a faculty member.

  
  
  Prerequisites: Permission of the faculty project supervisor and the Director of Graduate Studies.
• CSCI-GA.3840-​001
  (2304) Master's Thesis Research *  STAFF -
  
  
  Prerequisites: Approval of a faculty adviser and the Director of Graduate Studies for the M.S. programs.
• CSCI-GA.3850-​004
  (2305) PhD Seminar: Formal Methods**  Thomas Wies R 11:00-12:30PM 60 Fifth Ave 446
  Graduate seminars serve as loosely structured forums for exploring research topics from broad areas of computer science. They are designed to foster dialogue by bringing together faculty and students from a given area and to encourage the exchange of ideas. As such, they bridge the gap between more structured course offerings and informal research meetings. Subject matter varies by section.
  
  Prerequisites: Permission of the instructor.
• CSCI-GA.3850-​006
  (2889) PhD Seminar: Machine Learning**  CANCELLED -
  Graduate seminars serve as loosely structured forums for exploring research topics from broad areas of computer science. They are designed to foster dialogue by bringing together faculty and students from a given area and to encourage the exchange of ideas. As such, they bridge the gap between more structured course offerings and informal research meetings. Subject matter varies by section.
  
  Prerequisites: Permission of the instructor.
• CSCI-GA.3860-​001
  (2306) PhD Thesis Research **  STAFF -
  
  
  Prerequisites: Permission of the thesis adviser or director of graduate studies for the Ph.D. program.
• CSCI-GA.3870-​001
  (3097) Internship In Computer Science MS*  STAFF -
  

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

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

  
  
  Prerequisites: Permission of Director of Graduate Studies.
• CSCI-GA.3870-​002
  (3098) Internship in Computer Science PhD*  STAFF -
  

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

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

  
  
  Prerequisites: Permission of Director of Graduate Studies.

• *
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• **
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• ***
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• ****
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