Course Schedule

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• CSCI-GA.1170-​001
  DS-GA.1170
  (2633) Fundamental Algorithms  Alexander Alekseyev
  Office Hours M 5:10-7:00PM Silv 405
  

  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.2130-​001
  (2637) Compiler Construction  Eva Rose
  Office Hours M 7:10-9:00PM CIWW 202
  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
  (2638) Operating Systems  Hubertus Franke
  Office Hours M 7:10-9:00PM CIWW 109
  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.2440-​001
  (2642) Software Engineering   Jean-Claude Franchitti
  Office Hours M 7:10-9:00PM CIWW 317
  This is a capstone course focusing on large-scale software development. This course presents modern software engineering techniques and examines the software life cycle, including software specification, design, implementation, testing, and maintenance. Object-oriented design methods are also considered. Software engineering projects involve creation of a large-scale software system and require 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.2560-​001
  (3538) Artificial Intelligence   Ernest Davis
  Office Hours M 5:10-7:00PM CIWW 102
  There are many cognitive tasks that people do easily and almost unconsciously but that have proven extremely difficult to program on a computer. Artificial intelligence is the problem of developing computer systems that can carry out these tasks. This course covers problem solving and state space search; automated reasoning; probabilistic reasoning; planning; and knowledge representation.
• CSCI-GA.2572-​001
  DS-GA.1008-001
  (23069) Deep Learning  Yann LeCun M 4:55-6:35PM CIWW 109
  

  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.2945-​001
  MATH-GA.2012-001
  (2644) Adv Topics Num Analysis: High Performance Computing  Georg Stadler
  Dhairya Malhotra M 5:10-7:00PM CIWW 1302
  

  This class will be an introduction to the fundamentals of parallel scientific computing. We will establish a basic understanding of modern computer architectures (CPUs and accelerators, memory hierarchies, interconnects) and of parallel approaches to programming these machines (distributed vs. shared memory parallelism: MPI, OpenMP, OpenCL/CUDA). Issues such as load balancing, communication, and synchronization will be covered and illustrated in the context of parallel numerical algorithms. Since a prerequisite for good parallel performance is good serial performance, this aspect will also be addressed. Along the way you will be exposed to important tools for high performance computing such as debuggers, schedulers, visualization, and version control systems. This will be a hands-on class, with several parallel (and serial) computing assignments, in which you will explore material by yourself and try things out. There will be a larger final project at the end. You will learn some Unix in this course, if you don't know it already. Prerequisites for the course are (serial) programming experience with C/C++ (I will use C in class) or FORTRAN, and some familiarity with numerical methods.

• CSCI-GA.2945-​002
  MATH-GA.2012-002
  (2645) Adv Topics Num Analysis: Immersed Boundary Method  Charles Peskin M 11:00-12:50PM CIWW 1302
  

  The immersed boundary (IB) method is a general framework for the computer simulation of flows with immersed elastic boundaries and/or complicated geometry. It was originally developed to study the fluid dynamics of heart valves, and it has since been applied to a wide variety of problems in biofluid dynamics, such as wave propagation in the inner ear, blood clotting, fish swimming, and insect flight.

  Non-biological applications include sails, parachutes, flows of suspensions, and two-fluid or multifluid problems. Topics to be covered include: mathematical formulation of fluid-structure interaction in Eulerian and Lagrangian variables with the Dirac delta function as the link between these two kinds of variables; discretization of the structure, fluid, and interaction equations, including energy-based discretization of the structure equations, finite difference discretization of the fluid equations, and IB delta functions with specified mathematical properties; an IB method with an exactly divergence-free interpolated velocity field; IB methods for immersed boundaries with non-trivial mass and for fluids with non-uniform density and viscosity; IB methods for immersed filaments with bend and twist; and a stochastic IB method for thermally fluctuating hydrodynamics within biological cells.

  Course requirements include homework assignments and a computing project, but no exam. Students may collaborate on the homework and on the computing project, and are encouraged to present the results of their computing projects to the class.

  Text:

  The Immersed Boundary Method, lecture notes by Charles S. Peskin. These notes will be supplemented by selected publications on the topics of the course.

  
  
  Prerequisites: Familiarity with numerical methods and fluid dynamics.
• CSCI-GA.2945-​004
  MATH-GA.2012-004
  (24010) Adv Topics Num Analysis: Stochastic modeling and uncertainity quantification in complex systems  Benjamin Peherstorfer
  Office Hours M 1:25-3:15PM CIWW 517
  

  As physical and time domains of partial differential equations (PDEs) can be resolved with ever higher accuracy, the quality of numerical simulations of physical phenomena increasingly tends to be limited by noisy and incomplete data that insufficiently describe boundary conditions, coefficients, and other parameters of the problem setups. This course provides an introduction to the stochastic modeling of these data uncertainties as random coefficients and random forcing terms of PDEs and discusses dimensionality reduction methods for efficiently estimating moments of the solutions of the corresponding stochastic PDEs. The first part focuses on stochastic modeling and sampling (Karhunen-Loeve expansion, polynomial chaos expansion, stochastic Galerkin, (multilevel) Monte Carlo, stochastic collocation, sparse grids). The second part discusses dimensionality reduction techniques to make estimation of moments of the PDE solutions computationally tractable (proper orthogonal decomposition, a posteriori error estimation and error control of reduced models, empirical interpolation).

• CSCI-GA.3033-​008
  (3136) Special Topics: .Net Web Application Development  Cory Plock
  Office Hours M 5:10-7:00PM CIWW 101
  

  This course introduces the concepts and tools necessary for building robust web applications using the Microsoft .NET Framework. Among the topics explored will be the multi-language .NET architecture, build and deployment process, the C# programming language, Entity Framework, Model-View-Controller (MVC) design pattern, web services, Git version control, and the Azure cloud platform. This is a hands-on project-based course where students will build a fully functional web solution.

  
  
  Prerequisites: Programming languages, object-oriented programming, relational databases, and data structures.
• CSCI-GA.3033-​020
  DS-GA.3001-014
  (3357) Special Topics: Mathematics of Deep Learning  Joan Bruna M 7:10-9:00PM CIWW 102
  

  This graduate-level course explores some of the open mathematical challenges arising in the study of Deep Learning. In particular, we will focus on three main topics: (i) signal processing principles underpinning convolutional neural networks and their generalisations to non-euclidean geometries (ii) non-convex optimization challenges arising in high-dimensional (or overparametrised) learning problems, and (iii) geometry of Markov Decision Processes and its role in Reinforcement Learning guarantees.

  
  
  Prerequisites: Background on high-dimensional probability, statistics, and/or harmonic analysis. Familiarity with general Machine Learning topics and basic notions of optimization.
• CSCI-GA.3033-​024
  (20911) Special Topics: Big Data and ML Systems  Lakshminarayanan Subramanian
  Office Hours M 7:10-9:00PM CIWW 512
  

  This class aims to cover introductory and recent concepts in big data and machine learning systems. The class will focus on a broad spectrum of big data computational problems, algorithms and platforms. The class will be centered around several big data case studies in commercial use to understand big data and machine learning tasks across different domains and provide an in-depth understanding of the problems and algorithms used in each domain. From the computational platform perspective, this class covers popular and widely used commercial platforms, Spark, streaming platforms, Tensorflow, ML platforms (MLBase, MxNet) and GPU platforms. The goal of this class is to educate students about the algorithms and systems techniques used to build scalable big data and ML platforms and how these platforms are used in the real world.

  This class covers the following broad topics:

  1. Cloud Infrastructure Blocks: AWS
  2. Big Data Algorithms: searching and indexing large data sets, implementing standard statistical algorithms, similar items, nearest neighbors, graph mining, network analytics, dimensionality reduction
  3. Big Data Computation Platforms: Spark, TensorFlow, MLBase, MLib, MxNet, GPU computing
  4. Scalable ML Algorithms: Implementing deep learning algorithms, graph and network analytics, scalable vision algorithms, scalable NLP algorithms
  5. Domain Specific Applications and Case Studies: vision analytics engines, NLP analytics engines, search and graph analytics
• CSCI-GA.3140-​001
  (20921) Abstract Interpretation  Patrick Cousot
  Office Hours M 5:10-7:00PM 60 Fifth Ave 446
  

  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
  (7480) Intro To Computer Programming  Deena Engel
  Office Hours MW 2:00-3:15PM CIWW 101
  

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

  
  
  Prerequisites: Three years of high school mathematics or equivalent. No prior computing experience is assumed. Students with any programming experience should consult with the department before registering. Students who have taken or are taking Introduction to Computer Science (CSCI-UA 101) will not receive credit for this course. Does not count toward the computer science major; serves as the prerequisite for students with no previous programming experience who want to continue into CSCI-UA 101 and pursue the major.
• CSCI-UA.0002-​003
  (7841) Intro To Computer Programming  Craig Kapp
  Office Hours MW 9:30-10:45AM CIWW 109
  

  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-​007
  (9089) Intro To Computer Programming  David Gochfeld
  Office Hours MW 9:30-10:45AM 60 Fifth Ave C12
  

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

  
  
  Prerequisites: Three years of high school mathematics or equivalent. No prior computing experience is assumed. Students with any programming experience should consult with the department before registering. Students who have taken or are taking Introduction to Computer Science (CSCI-UA 101) will not receive credit for this course. Does not count toward the computer science major; serves as the prerequisite for students with no previous programming experience who want to continue into CSCI-UA 101 and pursue the major.
• CSCI-UA.0002-​009
  (9931) Intro To Computer Programming  Adam Meyers
  Office Hours MW 8:00-9:15AM 60 Fifth Ave C10
  

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

  
  
  Prerequisites: Three years of high school mathematics or equivalent. No prior computing experience is assumed. Students with any programming experience should consult with the department before registering. Students who have taken or are taking Introduction to Computer Science (CSCI-UA 101) will not receive credit for this course. Does not count toward the computer science major; serves as the prerequisite for students with no previous programming experience who want to continue into CSCI-UA 101 and pursue the major.
• CSCI-UA.0004-​001
  (7845) Intro to Web Design & Computer Principles  Alvaro Olsen MW 8:00-9:15AM 60 Fifth Ave 110
  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
  (7847) Intro to Web Design & Computer Principles  Roy Vanegas
  Office Hours MW 12:30-1:45PM CIWW 101
  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-​005
  (9090) Intro to Web Design & Computer Principles  Lee-Sean Huang
  Office Hours MW 3:30-4:45PM CIWW 101
  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
  (9208) Intro to Web Design & Computer Principles  Lee-Sean Huang
  Office Hours MW 11:00-12:15PM CIWW 102
  Introduces students to both the practice of web design and the basic principles of computer science. The practice component covers not only web design but also current graphics and software tools. The principles section includes an overview of hardware and software, the history of computers, and a discussion of the impact of computers and the Internet.
  
  Prerequisites: Three years of high school mathematics or equivalent. No prior computing experience is assumed. Students with computing experience should consult with the department before registering.
• CSCI-UA.0061-​001
  (8994) Web Development And Programming  Craig Kapp
  Office Hours MW 12:30-1:45PM CIWW 201
  Provides a practical approach to web technologies and programming. Students build interactive, secure, and powerful web programs. Covers client and server side technologies for the web.
  
  Prerequisites: Introduction to Computer Programming (CSCI-UA 2) and Introduction to Web Design & Computer Principles (CSCI-UA 4).
• CSCI-UA.0101-​003
  (9932) Intro To Computer Science  Suzanne McIntosh
  Office Hours MW 11:00-12:15PM 60 Fifth Ave 150
  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-​004
  (7851) Intro To Computer Science  Hilbert Gene Locklear
  Office Hours MW 3:30-4:45PM CIWW 102
  How to design algorithms to solve problems and how to translate these algorithms into working computer programs. Experience is acquired through projects in a high-level programming language. Intended primarily for computer science majors but also suitable for students of other scientific disciplines. Programming assignments.
  
  Prerequisites: Introduction to Computer Programming (CSCI-UA 2) or departmental permission assessed by placement exam.
• CSCI-UA.0101-​005
  (9092) Intro To Computer Science  Candido Cabo
  Office Hours MW 12:30-1:45PM CIWW 202
  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
  (9383) Intro To Computer Science  Amos Bloomberg
  Office Hours MW 2:00-3:15PM CIWW 102
  How to design algorithms to solve problems and how to translate these algorithms into working computer programs. Experience is acquired through projects in a high-level programming language. Intended primarily for computer science majors but also suitable for students of other scientific disciplines. Programming assignments.
  
  Prerequisites: Introduction to Computer Programming (CSCI-UA 2) or departmental permission assessed by placement exam.
• CSCI-UA.0101-​007
  (10685) Intro To Computer Science  Douglas Moody
  Office Hours MW 9:30-10:45AM CIWW 202
  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
  (19583) Intro To Computer Science  Nader Nassar
  Office Hours MW 8:00-9:15AM CIWW 102
  How to design algorithms to solve problems and how to translate these algorithms into working computer programs. Experience is acquired through projects in a high-level programming language. Intended primarily for computer science majors but also suitable for students of other scientific disciplines. Programming assignments.
  
  Prerequisites: Introduction to Computer Programming (CSCI-UA 2) or departmental permission assessed by placement exam.
• CSCI-UA.0102-​001
  (7852) Data Structures  Chee Yap
  Office Hours MW 12:30-1:45PM CIWW 102
  Use and design of data structures, which organize information in computer memory. Stacks, queues, linked lists, binary trees: how to implement them in a high-level language, how to analyze their effect on algorithm efficiency, and how to modify them. Programming assignments.
  
  Prerequisites: Introduction to Computer Science (CSCI-UA 101).
• CSCI-UA.0102-​003
  (7854) Data Structures  Young Kun Ko
  Office Hours MW 9:30-10:45AM CIWW 102
  Use and design of data structures, which organize information in computer memory. Stacks, queues, linked lists, binary trees: how to implement them in a high-level language, how to analyze their effect on algorithm efficiency, and how to modify them. Programming assignments.
  
  Prerequisites: Introduction to Computer Science (CSCI-UA 101).
• CSCI-UA.0201-​001
  (7857) Computer Systems Organization  Jinyang Li
  Office Hours MW 11:00-12:15PM 60 Fifth Ave C12
  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-​004
  (9754) Computer Systems Organization - Recitation  Christopher Moirano M 11:00-12:15PM CIWW 202
  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
  (10279) Computer Systems Organization - Recitation  Sai Anirudh Kondaveeti
  Office Hours M 3:30-4:45PM CIWW 109
  Covers the internal structure of computers, machine (assembly) language programming, and the use of pointers in high-level languages. Topics include the logical design of computers, computer architecture, the internal representation of data, instruction sets, and addressing logic, as well as pointers, structures, and other features of high-level languages that relate to assembly language. Programming assignments are in both assembly language and other languages.
  
  Prerequisites: Data Structures (CSCI-UA 102).
• CSCI-UA.0201-​007
  (20932) Computer Systems Organization - Recitation  Christopher Moirano M 3:30-4:45PM CIWW 202
  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
  (10271) Operating Systems  Yan Shvartzshnaider
  Office Hours MW 11:00-12:15PM Meyr 102
  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-​003
  (7862) Basic Algorithms  Gleb Pogudin
  Office Hours MW 11:00-12:15PM CIWW 101
  Introduction to the study of algorithms. Presents two main themes: designing appropriate data structures and analyzing the efficiency of the algorithms that use them. Algorithms studied include sorting, searching, graph algorithms, and maintaining dynamic data structures. Homework assignments, not necessarily involving programming.
  
  Prerequisites: Data Structures (CSCI-UA 102) and Discrete Mathematics (MATH-UA 120).
• CSCI-UA.0480-​002
  (7865) Special Topics: iOS Programming  Nathan Hull MW 3:30-4:45PM CIWW 317
  

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

  
  
  Prerequisites: CSCI-UA.0201 with a grade of C or better
• CSCI-UA.0480-​003
  (7866) Special Topics: Parallel Computing  Mohamed Zahran
  Office Hours MW 2:00-3:15PM CIWW 109
  

  Most of us have learned to program a single microprocessor (single core) using a high-level programming language like C/C++, Java, ... This is called sequential programming. We feel very comfortable with this because we think in a sequential way and give the machine statements to be executed in sequence. However, this has to change. A microprocessor with single core no longer exists in almost all computers we are using today (including your tablets and smart phones). Most of our devices are now multicore processors. A multicore processor contains several cores (called CPUs or cores) on-chip. To make the best use of these multicore chips we need to program them in-parallel. Sequential programming, for all platforms from smartphones to supercomputers, is falling out of fashion and taking back-seat to parallel programming. How to think in parallel? How to write code in parallel to make the best use of the underlying hardware? How is that new hardware different from the traditional one? What will the future be for the software and hardware? This is the topic of this course.

  
  
  Prerequisites: CSCI-UA.0201 with a grade of C or better
• CSCI-UA.0480-​008
  (10136) Special Topics: Applied Internet Technology  Joseph Versoza
  Office Hours MW 11:00-12:15PM CIWW 109
  

  A practical introduction to creating modern web applications. Covers full stack web development - including topics such as database / data model design, MVC architecture, templating, handling user input, asynchronous processing, and client side interactivity. Students will use current server and client side web frameworks to build dynamic, data-driven sites. Various tools to support development will also be introduced, such as version control and build systems. Basic knowledge of HTML and CSS and familiarity with command line tools are recommended.

  
  
  Prerequisites: CSCI-UA.0201 with a grade of C or better
• CSCI-UA.0480-​009
  (10275) Special Topics: Natural Language Processing  Adam Meyers
  Office Hours MW 12:30-1:45PM Silv 414
  

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

  
  
  Prerequisites: CSCI-UA.0201 with a grade of C or better
• CSCI-UA.0480-​010
  (10662) Special Topics: Open Source Software Development  Joanna Klukowska
  Office Hours MW 3:30-4:45PM CIWW 517
  

  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 with a grade of C or better
• CSCI-UA.0480-​011
  (19584) Special Topics: Introduction to Computer Security  Joseph Bonneau
  Office Hours MW 12:30-1:45PM 60 Fifth Ave 150
  

  This course will cover basic principles of computer security and security engineering. To facilitate understanding, this course will consider security both from an attacker's perspective (threat modeling) and the defender's perspective (building and deploying secure systems). Specific topics will include operating system security, network security, web security, and mobile device security. Course projects will focus both on writing secure code and exploiting insecure code.

  
  
  Prerequisites: Computer Systems Organization (CSCI-UA 201) with a grade of C or better. Recommended: Operating Systems (CSCI-UA.202)
• CSCI-UA.0480-​012
  (25368) Special Topics: iOS Programming  Nathan Hull MW 12:30-1:45PM CIWW 312
  

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

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

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