Course Schedule

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• CSCI-GA.1144-​001
  (2405) PAC II*  Mohamed Zahran T 6:00-8:30PM CIWW 312
  

  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.1144-​002
  (2792) PAC II Recitation  TBA R 7:10-8:00PM CIWW 312
  

  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
  (2406) Fundamental Algorithms  Chee Yap M 5:10-7:00PM 60 Fifth Ave 110
  

  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
  (2407) Fundamental Algorithms Recitation  TBA W 5:10-6:00PM CIWW 101
  

  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
  (3092) Fundamental Algorithms  Yevgeniy Dodis T 7:10-9:00PM 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-​004
  DS-GA.1170
  (3145) Fundamental Algorithms Recitation  TBA R 8:10-9:00PM 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.1180-​001
  (3351) Mathematical Techniques For CS Applications  Remi Imbach T 5:10-7:00PM CIWW 317
  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
  (2408) Programming Languages  Cory Plock M 5:10-7:00PM CIWW 101
  

  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
  (2409) Programming Languages Recitation  TBA R 7:10-8:00PM 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.2130-​001
  (2410) Compiler Construction  Alexander Alekseyev 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
  (2411) Operating Systems  Hubertus Franke 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.2250-​002
  (2985) Operating Systems  Shameem Akhter W 7:10-9:00PM CIWW 201
  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
  (2412) Data Communications and Networks  Muhammed Fatih Bulut R 5:10-7:00PM CIWW 101
  

  This course teaches the design and implementation techniques essential for engineering robust networks. Topics include networking principles, Transmission Control Protocol/Internet Protocol, naming and addressing (Domain Name System), data encoding/decoding techniques, link layer protocols, routing protocols, transport layer services, congestion control, quality of service, network services, programmable routers and overlay networks.

  
  
  Prerequisites: Students must have a working knowledge of fundamental data structures and associated algorithms. For some of the practical aspects of the course, a working knowledge of an object-oriented programming language (e.g., C++, C#, or preferably Java) is expected. An undergraduate course in data communication and networks is helpful but not required.
• CSCI-GA.2421-​001
  MATH-GA 2020-001
  (2413) Numerical Methods II  Jonathan Goodman T 5:10-7:00PM TBD
  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
  (2414) Database Systems  Zvi Kedem W 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.2440-​001
  (2415) Software Engineering   Jean-Claude Franchitti 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.2520-​001
  BIOL-GA 1127-001
  (2416) Bioinformatics and Genomes  Richard Bonneau
  Brian Parker F 1:00-3:45PM CIWW 102
  The recent explosion in the availability of genome-wide data such as whole genome sequences and microarray data led to a vast increase in bioinformatics research and tool development. Bioinformatics is becoming a cornerstone for modern biology, especially in fields such as genomics. It is thus crucial to understand the basic ideas and to learn fundamental bioinformatics techniques. The emphasis of this course is on developing not only an understanding of existing tools but also the programming and statistics skills that allow students to solve new problems in a creative way.
• CSCI-GA.2560-​001
  (3147) Artificial Intelligence   Ernest Davis 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
  (3437) Deep Learning  Yann LeCun M 4:55-6:35PM GCASL C95
  

  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.2572-​002
  DS-GA.1008-002
  (3448) Deep Learning Lab  TBA T 7:10-8:00PM GCASL C95
  

  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.2590-​001
  (2793) Natural Language Processing  Ralph Grishman T 5:10-7:00PM 60 Fifth Ave 150
  

  An introduction to natural language processing, with an emphasis on methods for creating structured knowledge from text. Basic syntactic structures of English; constituent and dependency representations and parsers. Hidden Markov Models and maximum entropy models for part-of-speech and name tagging. Finite-state grammars and partial parsing. Probabilistic parsing. Lexical semantics. Relation and event extraction. Reference resolution. Machine translation. Supervised, semi-supervised, and active learning of linguistic models. Neural network models. There will be several pencil-and-paper exercises, several computer exercises, a final project, and a final exam.

  
  
  Prerequisites: Some facility with Java and Python and a knowledge of the elements of probability and statistics is expected.
• CSCI-GA.2620-​001
  (2825) Networks and Mobile Systems  Anirudh Sivaraman R 7:10-9:00PM 60 Fifth Ave C12
  

  This is a capstone course. A course in computer networks and large-scale distributed systems. Teaches the design and implementation techniques essential for engineering both robust networks and Internet-scale distributed systems. The goal is to guide students so they can initiate and critique research ideas in networks and distributed systems and implement and evaluate a working system that can handle a real-world workload. Topics include routing protocols, network congestion control, wireless networking, peer-to-peer systems, overlay networks and applications, distributed storage systems, and network security.

  
  
  Prerequisites: CSCI-GA 1170, CSCI-GA 2110, and CSCI-GA 2250.
• CSCI-GA.2820-​001
  (3354) DevOps and Agile Methodologies  John Rofrano T 5:10-7:00PM CIWW 101 Additional information: Not open to graduate Computer Science, Information Systems, CEI (Computing, Entrepreneurship, and Innovation), or Non-Degree students.
  

  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
  (3355) DevOps and Agile Methodologies Lab  John Rofrano T 7:10-8:00PM CIWW 101 Additional information: Not open to graduate Computer Science, Information Systems, CEI (Computing, Entrepreneurship, and Innovation), or Non-Degree students.
  

  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.2840-​001
  (3356) Entrepreneurship Capstone  Evan Korth T 10:15-12:15PM 16WP 106 Additional information: Open only to students in the MS-CEI program.
  

  The Entrepreneurship Capstone class is a 15­week bootcamp class on entrepreneurship. This class aims to translate experiences of students on idea incubation, prototype development and Lean Launchpad towards entrepreneurship. Students will learn how to pitch their ideas to VCs, focus on business development and translate their prototypes to an evolving MVP.

• CSCI-GA.2840-​002
  (3361) Entrepreneurship Capstone Lab  TBA T 12:25-1:15PM 16WP 106 Additional information: Open only to students in the MS-CEI program.
  

  The Entrepreneurship Capstone class is a 15­week bootcamp class on entrepreneurship. This class aims to translate experiences of students on idea incubation, prototype development and Lean Launchpad towards entrepreneurship. Students will learn how to pitch their ideas to VCs, focus on business development and translate their prototypes to an evolving MVP.

• CSCI-GA.2945-​001
  MATH-GA 2012-001
  (2417) Advanced Topics in Numerical Analysis: Convex and Nonsmooth Optimization  Michael Overton M 5:10-7:00PM CIWW 1302
  

  Convex optimization problems have many important properties, including a powerful duality theory and the property that any local minimum is also a global minimum. Nonsmooth optimization refers to minimization of functions that are not necessarily convex, usually locally Lipschitz, and typically not differentiable at their minimizers. Topics in convex optimization that will be covered include duality, linear and semidefinite programming, CVX ("disciplined convex programming"), gradient and Newton methods, Nesterov's complexity bound, the alternating direction method of multipliers, the nuclear norm and matrix completion, the primal barrier method, primal-dual interior-point methods for linear and semidefinite programs. Topics in nonsmooth optimization that will be covered include subgradients and subdifferentials, Clarke regularity, and algorithms, including gradient sampling and BFGS, for nonsmooth, nonconvex optimization. Homework will be assigned, both mathematical and computational. Students may submit a final project on a pre-approved topic or take a written final exam.

  
  
  Prerequisites: Undergraduate Linear Algebra and Multivariable Calculus.
• CSCI-GA.2945-​002
  MATH-GA 2012-002
  (2418) Advanced Topics in Numerical Analysis: High Performance Computing  Benjamin Peherstorfer M 1:25-3:15PM CIWW 512
  

  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: (Serial) programming experience with C/C++ (I will use C in class) or FORTRAN, and some familiarity with numerical method.
• CSCI-GA.3033-​001
  (2419) Special Topics: Big Data Science  Anasse Bari W 5:10-7:00PM 60 Fifth Ave C15
  

  Data Science has recently gained a substantial interest in a variety of industries including healthcare, finance, manufacturing and marketing. It is positioned at the intersection point of computer science, data mining, machine learning, predictive analytics, business, statistics and domain expertise. It aims at finding hidden knowledge (patterns, models, associations) for the purpose of making better decisions. This course will introduce the basic fundamental concepts of the algorithms and the tools of extracting valuable insights from data with the ability to formulating and solving problems with it. Topics of this course include, but are not limited to: Basics of Data Analytics Project Lifecycle, Developing an Analytics Roadmap, Data Preprocessing, Data Analytics Use cases, Data Cleaning Algorithms, Feature Selection Algorithms, Introduction to Hadoop in Theory and in Practice, Algorithms for Finding Similar Data Items, Dimensionality Reduction techniques, Clustering Algorithms, Classification Algorithms, Introduction to Sentiment Analysis in short text (e.g Tweets), Mining Association Rules, Performance Measures, Ensemble Methods, Information retrieval systems and Recommendation Systems with applications in Bio-informatics, Text Mining and Social Network Analytics.

  
  
  Prerequisites: Strong programming skills in the Java language and fundamentals of linear algebra.
• CSCI-GA.3033-​002
  (2872) Special Topics: Social Networks  Bhubaneswar Mishra R 5:10-7:00PM CIWW 512
  

  Social Networks is a specific example of many forms of networks that have become ubiquitous in our modern society. The World Wide Web enables information flows among vast number of humans; Facebook, and LinkedIn, etc. connect small groups of friends; amazon, eBay, etc. provide opportunities for trading, etc, BitCoins, Ethereum, etc. allow parties to make financial and contractual transactions . These networks determine our information, influence our opinions, and shape our political attitudes. They also link us, often through important but weak ties, to other humans. Their origin is biological: going back to quorumsensing, swarming, flocking, social grooming, gossip, etc., and have evolved with the dynamics of evolutionary games (particularly Signaling Games). Yet, as we have connected our social networks to traditional human institutions (markets, justice systems, education, etc.) through new technologies, the underlying biology has become obscured, but not dormant. Economic markets also look much more like networks than anonymous marketplaces. Firms interact with the suppliers and customers in a Web-like supply chains. Systemic risk in financial markets often results from the counterparty risks created within this financial network. This course will introduce the tools for the study of networks, and mechanism designed to interact strategically: SmartContractss, Costly Signaling, Credible and Noncredible Threats, Model Checking and Verification, Safety and Liveness, Recommenders and Verifiers, Deception, Market mechanisms (pricing and auction), Privacy and Trust… Exampled Systems: Bit-coins, Zcash, Ripple, Stellar, Ethereum, Solidity, Rholang, DAO (Distributed Companies), Cyber Security (M-coins), Information Finance Markets (WealthFront, etc.), Market Microstructure, ICO/STO/ITO, GDPR, OpenLaw, OpenZeplin, ...

• CSCI-GA.3033-​003
  (19033) Special Topics: Production Quality Software  Michael Schidlowsky W 5:10-7:00PM CIWW 317
  

  In this course we study the craft of software engineering. The semester begins with a thorough review of Java and the Java Virtual Machine. We concentrate on library components and language features most relevant to typical engineering projects. Later lectures cover more sophisticated topics, including concurrency and thread-safety, writing tests, object-oriented programming, and design patterns. The course also covers non-technical topics that are critical to software development including how to write with clarity, managing bugs, successfully developing and reinforcing salutary engineering habits, the nature of human productivity as it relates specifically to engineering, and communicating effectively with teammates. Lessons are reinforced with weekly assignments that are meticulously graded, with some submissions critiqued in classroom code reviews.

• CSCI-GA.3033-​005
  (2420) Special Topics: Big Data Application Development  Suzanne McIntosh R 7:10-9:00PM CIWW 101
  

  This course covers Apache Spark programming, Spark architecture, Spark SQL, Spark Streaming, and integration of Spark with other tools for developing Big Data applications. In addition, it covers technologies that integrate well with Spark in the creation of Big Data applications. Students are required to complete weekly reading and/or programming assignments and demonstrate mastery of course topics by developing a final project using Spark and complementary Big Data tools.

  
  
  Prerequisites: Students should have hands-on experience using Hadoop (Apache HDFS and Apache Hadoop MapReduce). In addition, students should have: strong programming skills in Java, Python, or C/C++; coursework in operating systems, networking, and algorithms; familiarity with Linux commands.
• CSCI-GA.3033-​010
  (3046) Special Topics: Cloud Computing  Jean-Claude Franchitti R 7:10-9:00PM CIWW 102
  

  This course is a capstone course that introduces the latest Cloud computing, Artificial Intelligence (AI), and Web3 Decentralized Applications technologies that can be combined to create next-generation multi-cloud innovative Intelligent Autonomous Networked (IAN) business solutions. Students will learn about services provided on the top “Big Clouds”, namely Amazon AWS Cloud, Google Cloud, Microsoft Azure Cloud, IBM Cloud, Salesforce, and others. Related services provided on the Cloud and covered in the course include computing and hosting services, storage services, networking services, big data services, and machine/deep learning services. Once familiar with Cloud services, Students will learn how to combine them to support cognitive computing and enable the creation of IAN solutions that cater to the practical needs of next-generation mobile devices and social media users in novel and creative ways. As they create these IAN solutions, students will learn about immersive Augmented/Virtual Reality (AR/VR) User Experience and Interfaces (UX/UI), hybrid decentralized computing and DApps, Edge and Fog computing and Internet of Things (IoT), Mobility/5G networking and Software Defined infrastructures, and various key aspects of digital security that are critical to ensure the safety of modern software.  Throughout the course, students will develop their own Intelligent Autonomous Networked (IAN) business solutions using Cloud-based machine and deep learning and other services and capabilities as noted above. Sample platform and related application components will be provided as applicable to speed up the development process.

• CSCI-GA.3033-​016
  (3047) Special Topics: Multicore Processors: Architecture and Programming  Mohamed Zahran W 5:10-7:00PM CIWW 312
  

  This is a capstone course.

  The tremendous advances in process technology have created a revolution both in hardware and in software. On the hardware side, we moved from single core processors to multicore/manycore processors. Multicore chips are now everywhere. You can find them in smartphones, playstations, notebooks, all the way up to supercomputers. To benefit from these chips, software must be parallelized, which starts another revolution in software. The purpose of this course is to introduce you to both the hardware advances and parallel programming techniques targeting multicore and manycore processors. You will learn how to make the best use of the underlying hardware to build applications that are faster, more power efficient, and more reliable.

• CSCI-GA.3033-​019
  (3052) Special Topics: Cryptocurrencies and Decentralized Ledgers  Joseph Bonneau R 5:10-7:00PM 60 Fifth Ave C12
  

  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
  DS-GA.3033-014
  (3048) Special Topics: Mathematics of Deep Learning  Joan Bruna R 5:10-7:00PM CIWW 201
  

  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-​023
  (3200) Special Topics: High Performance Machine Learning  Ulrich Finkler
  Wei Zhang W 7:10-9:00PM CIWW 312
  

  This is a capstone course for the MSCS program.

  One of the key ingredients of the success of Machine Learning is the ability to perform computations on very large amounts of training data. High Performance Computing (HPC) is where cutting edge technology (GPUs, low latency interconnects, etc.) is applied to the solution of computing intensive problems. Today, the application of High Performance Computing 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.

  Topics: ML Hardware and Software stack, Performance analysis methodology, ML algorithms performance, CUDA, cuDNN, Pytorch, MPI, Parallel and Distributed 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.
• CSCI-GA.3033-​024
  (3349) Special Topics: Big Data and ML Systems  Lakshminarayanan Subramanian W 7:10-9:00PM CIWW 102
  

  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.3033-​025
  (3350) Special Topics: Cloud and Machine Learning  Seetharami Seelam
  I-Hsin Chung R 5:10-7:00PM CIWW 312
  

  This is a capstone course for the MSCS program.

  This course exposes students to various cloud computing models and introduces them to performing machine learning on the cloud. The course material introduces students to various cloud providers including Amazon AWS, Google GCE, and IBM Cloud and their machine learning service capabilities. Students will learn how to build cloud systems for machine learning, the application characteristics, and develop hands-on experience with programming machine learning applications on these cloud platforms.

  
  
  Prerequisites: CSCI-GA 1170, CSCI-GA 2110, and CSCI-GA 2250. Basic understudying of operating systems and computer architecture, ability to program in at least one of c/c++, go, or Python languages. Basic understanding of cloud computing systems.
• CSCI-GA.3033-​026
  (19032) Special Topics: Practical Computer Security  Kevin Chen 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: memory safety (buffer overflow, return-oriented programming, etc), web security (XSS, CSRF, SQL Injection, etc), malware, threat modeling, security principles, secure coding practices (fuzzing, sandboxing, etc) and network security. Course projects and assignments may require Assembly, C, Python, JavaScript, HTML, SQL and/or other scripting languages.

  
  
  Prerequisites: Programming experience in C/C++, JavaScript, Python, and SQL; basic understanding of assembly language; working knowledge of web application development.
• CSCI-GA.3033-​027
  (23369) Special Topics: Blockchain and Its Applications  Richard Hull T 5:10-7:00PM CIWW 201
  

  Blockchain has the potential to fundamentally shift how businesses and other organizations collaborate, enabling increased trust between participants and substantial efficiency gains in terms of time and labor. This course provides a hands-on introduction to the rapidly evolving field of Blockchain for applications centered around inter-organization collaboration. The emphasis is on creating and programming Blockchain applications and off-chain interactions with them, The course will also cover setting up Blockchain networks, the underlying distributed systems architecture, the role of encryption and consensus algorithms, model-driven application development, governance and security. The course will cover several existing blockchain platforms, although the programming assignments and case studies will be based on the open-source Hyperledger Fabric, one of the leading platforms for inter-organization collaboration applications.

  
  
  Prerequisites: An undergraduate algorithms course.
• CSCI-GA.3033-​028
  (23764) Special Topics: Hardness of Approximation: PCP Theorem to 2-to-2 Games Theorem  Subhash Khot M 7:10-9:00PM CIWW 102
  

  Researchers firmly believe that no algorithm can efficiently compute optimal solutions to computationally complex problems called NP-hard problems. For many NP-hard problems, even computing an approximately-optimal solution remains NP-hard. This phenomenon, known as the hardness of approximation, has numerous connections to proof checking, optimization, combinatorics, discrete Fourier analysis, and geometry.

  The course will provide an overview of these connections. In particular, it will address why graph coloring is a computationally hard problem, how it is possible to check a proof without even looking at it, why computer scientists love the majority vote, and whether a shape exists that looks spherical as well as cubical. It will explain how all this fits into a 30-year research program starting with the foundational Probabilistically Checkable Proofs (PCP) Theorem and leading to the recent 2-to-2 GamesTheorem.

  
  
  Prerequisites: Basic knowledge of algorithms, NP-hardness, discrete math, analysis.
• CSCI-GA.3812-​001
  (2421) Information Technology Projects *  Evan Korth W 6:00-9:00PM CIWW 512
  

  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
  (3053) 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
  (2422) 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
  (2423) 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
  (2424) 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
  (2425) 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
  (2426) 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
  (2427) 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
  (2428) 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
  (2429) 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
  (2430) 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-​007
  (19895) PhD Seminar: Applications of Contextual Integrity**  Yan Shvartzshnaider W 3:30-4:45PM 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.3860-​001
  (2431) PhD Thesis Research **  STAFF -
  
  
  Prerequisites: Permission of the thesis adviser or director of graduate studies for the Ph.D. program.
• CSCI-GA.3870-​001
  (3049) 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
  (3050) 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.
• MAINT-GA.4747-​001 Maintenance of Matriculation (MS Students)  STAFF -
  Section 1 is for MS students. Section 4 is for non-supported PhD students.
• MAINT-GA.4747-​004 Maintenance of Matriculation (non-supported PhD students)  STAFF -
  Section 1 is for MS students. Section 4 is for non-supported PhD students.
• CSCI-UA.0002-​001
  (7667) Intro To Computer Programming (No Prior Experience)  Dakota Hernandez MW 3:30-4:45PM CIWW 201
  

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

  
  
  Prerequisites: Three years of high school mathematics or equivalent. No prior computing experience is assumed. Students with any programming experience should consult with the department before registering. Students who have taken or are taking Introduction to Computer Science (CSCI-UA 101) will not receive credit for this course. Does not count toward the computer science major; serves as the prerequisite for students with no previous programming experience who want to continue into CSCI-UA 101 and pursue the major.
• CSCI-UA.0002-​002
  (9501) Intro To Computer Programming (No Prior Experience)  Craig Kapp 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-​003
  (7668) Intro To Computer Programming (No Prior Experience)  Adam Meyers TR 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.0002-​004
  (7669) Intro To Computer Programming (No Prior Experience)  Craig Kapp T 5:00-7:30PM 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.0002-​005
  (7670) Intro To Computer Programming (No Prior Experience)  Shaheer Mohammed Haroon TR 9:30-10:45AM CIWW 317
  

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

  
  
  Prerequisites: Three years of high school mathematics or equivalent. No prior computing experience is assumed. Students with any programming experience should consult with the department before registering. Students who have taken or are taking Introduction to Computer Science (CSCI-UA 101) will not receive credit for this course. Does not count toward the computer science major; serves as the prerequisite for students with no previous programming experience who want to continue into CSCI-UA 101 and pursue the major.
• CSCI-UA.0002-​006
  (8811) Intro To Computer Programming (No Prior Experience)  David Gochfeld MW 9:30-10:45AM 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.0002-​007 Intro To Computer Programming (No Prior Experience)  TENTATIVE TR 8:00-9:15AM CIWW 201
  

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

  
  
  Prerequisites: Three years of high school mathematics or equivalent. No prior computing experience is assumed. Students with any programming experience should consult with the department before registering. Students who have taken or are taking Introduction to Computer Science (CSCI-UA 101) will not receive credit for this course. Does not count toward the computer science major; serves as the prerequisite for students with no previous programming experience who want to continue into CSCI-UA 101 and pursue the major.
• CSCI-UA.0002-​008
  (9502) Intro To Computer Programming (No Prior Experience)  Adam Meyers 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.0002-​009
  (9100) Intro To Computer Programming (No Prior Experience)  Michell Cardona TR 8:00-9:15AM 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-​010
  (10063) Intro To Computer Programming (No Prior Experience)  Saadia Lgarch TR 3:30-4:45PM CIWW 512
  

  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-​011
  (20030) Intro To Computer Programming (No Prior Experience)  Na'im Tyson W 6:20-8:50PM 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-​012
  (24536) Intro To Computer Programming (No Prior Experience)  Deena Engel 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-​013
  (24580) Intro To Computer Programming (No Prior Experience)  Deena Engel TR 9:30-10:45AM 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.0003-​001 Intro to Computer Programming (Limited Prior Experience)  CANCELLED -
  

  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.0003-​002
  (19674) Intro to Computer Programming (Limited Prior Experience)  Joseph Versoza TR 11:00-12:15PM CIWW 312
  

  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.0003-​003
  (20469) Intro to Computer Programming (Limited Prior Experience)  CANCELLED -
  

  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-​001
  (7671) 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-​002
  (7672) Intro to Web Design & Computer Principles  Amos Bloomberg TR 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.0004-​003 Intro to Web Design & Computer Principles  CANCELLED -
  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
  (8916) Intro to Web Design & Computer Principles  Lee-Sean Huang 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
  (9384) Intro to Web Design & Computer Principles  Lee-Sean Huang 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.0004-​007
  (19669) Intro to Web Design & Computer Principles  Adam Scher TR 8:00-9:15AM 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.0004-​008
  (23260) Intro to Web Design & Computer Principles  CANCELLED -
  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
  (7674) Database Design And Implementation  Deena Engel TR 2:00-3:15PM CIWW 102
  

  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
  (8723) Web Development And Programming  Craig Kapp 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.0002) and Introduction to Web Design & Computer Principles (CSCI-UA.0004).
• CSCI-UA.0061-​002
  (9101) Web Development And Programming  Nathan Hull TR 2:00-3:15PM CIWW 202
  

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

  
  
  Prerequisites: Introduction to Computer Programming (CSCI-UA.0002) and Introduction to Web Design & Computer Principles (CSCI-UA.0004).
• CSCI-UA.0101-​001
  (7675) Intro To Computer Science  Suzanne McIntosh TR 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-​002
  (7676) Intro To Computer Science  Teseo Schneider TR 2:00-3:15PM CIWW 317
  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
  (9503) Intro To Computer Science  Badreddine Oudjehane TR 9:30-10:45AM 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-​004
  (7677) Intro To Computer Science  Hilbert Gene Locklear 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
  (8814) Intro To Computer Science  Candido Cabo 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
  (9071) Intro To Computer Science  Amos Bloomberg MW 2:00-3:15PM CIWW 317
  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 Intro To Computer Science  Marsha Berger MW 11:00-12:15PM TBD
  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
  (10064) Intro To Computer Science  Nader Nassar 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
  (7678) Data Structures  Evan Korth 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-​002
  (7679) Data Structures - Recitation  TBA T 12:30-1:45PM CIWW 101
  Use and design of data structures, which organize information in computer memory. Stacks, queues, linked lists, binary trees: how to implement them in a high-level language, how to analyze their effect on algorithm efficiency, and how to modify them. Programming assignments.
  
  Prerequisites: Introduction to Computer Science (CSCI-UA 101).
• CSCI-UA.0102-​003
  (7680) Data Structures  Young Kun Ko 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.0102-​004
  (7681) Data Structures - Recitation  TBA R 8:00-9:15AM CIWW 109
  Use and design of data structures, which organize information in computer memory. Stacks, queues, linked lists, binary trees: how to implement them in a high-level language, how to analyze their effect on algorithm efficiency, and how to modify them. Programming assignments.
  
  Prerequisites: Introduction to Computer Science (CSCI-UA 101).
• CSCI-UA.0102-​005
  (7682) Data Structures  Anasse Bari TR 9:30-10:45AM 60 Fifth Ave 150
  Use and design of data structures, which organize information in computer memory. Stacks, queues, linked lists, binary trees: how to implement them in a high-level language, how to analyze their effect on algorithm efficiency, and how to modify them. Programming assignments.
  
  Prerequisites: Introduction to Computer Science (CSCI-UA 101).
• CSCI-UA.0102-​006
  (9102) Data Structures - Recitation  TBA W 3:30-4:45PM Meyr 122
  Use and design of data structures, which organize information in computer memory. Stacks, queues, linked lists, binary trees: how to implement them in a high-level language, how to analyze their effect on algorithm efficiency, and how to modify them. Programming assignments.
  
  Prerequisites: Introduction to Computer Science (CSCI-UA 101).
• CSCI-UA.0102-​007
  (9103) Data Structures  Anasse Bari TR 2:00-3:15PM Silv 207
  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-​008
  (9285) Data Structures - Recitation  TBA W 8:00-9:15AM CIWW 109
  Use and design of data structures, which organize information in computer memory. Stacks, queues, linked lists, binary trees: how to implement them in a high-level language, how to analyze their effect on algorithm efficiency, and how to modify them. Programming assignments.
  
  Prerequisites: Introduction to Computer Science (CSCI-UA 101).
• CSCI-UA.0201-​001
  (7683) Computer Systems Organization  Douglas Moody MW 9:30-10:45AM 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-​002
  (7684) Computer Systems Organization - Recitation  Goktug Saatcioglu T 9:30-10:45AM 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-​003
  (9352) Computer Systems Organization  Joanna Klukowska TR 9:30-10:45AM 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-​004
  (9353) Computer Systems Organization - Recitation  Justin Mae 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-​005
  (9679) Computer Systems Organization  Jean-Claude Franchitti MW 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-​006
  (9680) Computer Systems Organization - Recitation  TBA T 11:00-12:15PM 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
  (10257) Computer Systems Organization - Recitation  Goktug Saatcioglu 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.0201-​008
  (10258) Computer Systems Organization - Recitation  Justin Mae W 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-​001
  (7685) Operating Systems  Aurojit Panda TR 3:30-4:45PM CIWW 109
  Covers the principles and design of operating systems. Topics include process scheduling and synchronization, deadlocks, memory management (including virtual memory), input/output, and file systems. Programming assignments.
  
  Prerequisites: Computer Systems Organization (CSCI-UA 201).
• CSCI-UA.0202-​002
  (9674) Operating Systems  Yan Shvartzshnaider MW 11:00-12:15PM CIWW 109
  Covers the principles and design of operating systems. Topics include process scheduling and synchronization, deadlocks, memory management (including virtual memory), input/output, and file systems. Programming assignments.
  
  Prerequisites: Computer Systems Organization (CSCI-UA 201).
• CSCI-UA.0310-​001
  (7686) Basic Algorithms  Joel Spencer TR 2:00-3:15PM CIWW 109
  Introduction to the study of algorithms. Presents two main themes: designing appropriate data structures and analyzing the efficiency of the algorithms that use them. Algorithms studied include sorting, searching, graph algorithms, and maintaining dynamic data structures. Homework assignments, not necessarily involving programming.
  
  Prerequisites: Data Structures (CSCI-UA 102) and Discrete Mathematics (MATH-UA 120).
• CSCI-UA.0310-​002
  (7687) Basic Algorithms - Recitation  Samarth Tambad M 8:00-9:15AM CIWW 109
  Introduction to the study of algorithms. Presents two main themes: designing appropriate data structures and analyzing the efficiency of the algorithms that use them. Algorithms studied include sorting, searching, graph algorithms, and maintaining dynamic data structures. Homework assignments, not necessarily involving programming.
  
  Prerequisites: Data Structures (CSCI-UA 102) and Discrete Mathematics (MATH-UA 120).
• CSCI-UA.0310-​003
  (7688) Basic Algorithms  Seyed Nassajianmojarrad 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.0310-​004
  (9104) Basic Algorithms - Recitation  TBA R 9:30-10:45AM Silv 208
  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
  (9625) Basic Algorithms  Victor Shoup TR 12:30-1:45PM CIWW 109
  Introduction to the study of algorithms. Presents two main themes: designing appropriate data structures and analyzing the efficiency of the algorithms that use them. Algorithms studied include sorting, searching, graph algorithms, and maintaining dynamic data structures. Homework assignments, not necessarily involving programming.
  
  Prerequisites: Data Structures (CSCI-UA 102) and Discrete Mathematics (MATH-UA 120).
• CSCI-UA.0310-​006
  (9675) Basic Algorithms - Recitation  TBA W 12:30-1:45PM CIWW 109
  Introduction to the study of algorithms. Presents two main themes: designing appropriate data structures and analyzing the efficiency of the algorithms that use them. Algorithms studied include sorting, searching, graph algorithms, and maintaining dynamic data structures. Homework assignments, not necessarily involving programming.
  
  Prerequisites: Data Structures (CSCI-UA 102) and Discrete Mathematics (MATH-UA 120).
• CSCI-UA.0330-​001
  MATH-UA.0144
  (9168) 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.0330-​002
  (9169) Introduction to Computer Simulation  TBA F 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
  (8813) Topics of General Interest: Drawing on the Web  Joshua Clayton TR 2:00-3:15PM CIWW 312
  

  PREREQUISITES: CSCI-UA 2 and CSCI-UA 4, or permission of Instructor.
  
  The Web is an intrinsically visual medium whose graphical capabilities are diverse and evolving. With the development of HTML5 and CSS3, there are now multiple ways to code images and animation natively in the browser. This course will provide a survey of current drawing techniques. We will create a series of Web-based projects that involve raster graphics, vector graphics, and interactivity using HTML, CSS, SVG, and JavaScript. Drawing on the Web builds upon foundations in Web design and computer programming with a focus on the range of graphics that can be coded into Web pages.

• CSCI-UA.0421-​001
  (7689) Numerical Computing   Margaret Wright TR 9:30-10:45AM CIWW 312
  

  The need for floating-point arithmetic, the IEEE floating-point standard, and the importance of numerical computing in a wide variety of scientific applications. Fundamental types of numerical algorithms: direct methods (e.g., for systems of linear equations), iterative methods (e.g., for a nonlinear equation), and discretization methods (e.g., for a differential equation). Numerical errors: can you trust your answers? Uses graphics and software packages such as Matlab. Programming assignments.

  
  
  Prerequisites: Computer Systems Organization (CSCI-UA 201), either Calculus I (MATH-UA 121) or both of Mathematics for Economics I and II (MATH-UA 211 and 212), and Linear Algebra (MATH-UA 140), or permission of instructor.
• CSCI-UA.0453-​001
  (9287) Theory Of Computation   Richard Cole TR 11:00-12:15PM 194M 306A
  A mathematical approach to studying topics in computer science, such as regular languages and some of their representations (deterministic finite automata, nondeterministic finite automata, regular expressions) and proof of nonregularity. Context-free languages and pushdown automata; proofs that languages are not context-free. Elements of computability theory. Brief introduction to NP-completeness.
  
  Prerequisites: Basic Algorithms (CSCI-UA 310).
• CSCI-UA.0473-​001
  (9504) Intro To Machine Learning  Kyunghyun Cho MW 11:00-12:15PM 60 Fifth Ave 150
  

  This exciting and fast-evolving field of computer science has many recent consumer applications (e.g., Microsoft Kinect, Google Translate, IPhone's Siri, digital camera face detection, Netflix recommendations, Google news) and applications within the sciences and medicine (e.g., predicting protein-protein interactions, species modeling, detecting tumors, personalized medicine). Students learn the theoretical foundations and how to apply machine learning to solve new problems.

  
  
  Prerequisites: Data Structures (CSCI-UA.102), Probability and Statistics (MATH-UA.235), and Linear Algebra (MATH-UA.140).
• CSCI-UA.0476-​001
  (19847) Processing Big Data for Analytics Applications  Suzanne McIntosh MW 4:55-6:10PM 7E12 LL23
  

  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.0479-​001
  (23650) Data Management and Analysis  Joseph Versoza TR 9:30-10:45AM CIWW 202
  

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

  
  
  Prerequisites: Data Structures (CSCI-UA 102)
• CSCI-UA.0480-​001
  (7690) Special Topics: Computer Vision  Davi Geiger TR 3:30-4:45PM CIWW 101
  

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

  
  An introduction to the field of computer vision. Basic concepts will be covered such as edge detection, stereo vision, motion, color, texture and recognition.
  
  

• CSCI-UA.0480-​002
  (7691) Special Topics: iOS Programming  Nathan Hull MW 3:30-4:45PM CIWW 317
  

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

  
  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.

• CSCI-UA.0480-​003
  (8815) Special Topics: Parallel Computing  Mohamed Zahran MW 2:00-3:15PM CIWW 109
  

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

  
  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.

• CSCI-UA.0480-​004
  (9105) Special Topics: Algorithmic Problem Solving  Joanna Klukowska TR 12:30-1:45PM 12WP L120
  

  Prerequisites: CSCI-UA.0201 and CSCI-UA.310 with a grade of C or better

  Many of the top firms in the technological and financial sectors are using algorithmic problems as interview questions for assessing candidate skill. In this course we take this idea one step further and use algorithmic problem solving as way to hone programming skills. Students will use the material covered in the data structures and algorithms courses and learn new algorithmic techniques to solve challenging problems quickly. Each week will be devoted to a particular type of algorithm. Weekly problem sets will reinforce the lecture, and require students to implement their solutions in Java or C++. Students completing this course will be well prepared to participate in programming competitions such as the ACM Inter-Collegiate Programming Contest, TopCoder, and Google's Code Jam.

• CSCI-UA.0480-​005
  (9106) Special Topics: Algorithmic Problem Solving - Recitation  TBA W 8:00-9:15AM CIWW 101
  

  Prerequisites: CSCI-UA.0201 and CSCI-UA.310 with a grade of C or better.

  Many of the top firms in the technological and financial sectors are using algorithmic problems as interview questions for assessing candidate skill. In this course we take this idea one step further and use algorithmic problem solving as way to hone programming skills. Students will use the material covered in the data structures and algorithms courses and learn new algorithmic techniques to solve challenging problems quickly. Each week will be devoted to a particular type of algorithm. Weekly problem sets will reinforce the lecture, and require students to implement their solutions in Java or C++. Students completing this course will be well prepared to participate in programming competitions such as the ACM Inter-Collegiate Programming Contest, TopCoder, and Google's Code Jam.

• CSCI-UA.0480-​006
  (9286) Special Topics: Computer Graphics  Kenneth Perlin TR 11:00-12:15PM 60 Fifth Ave C12
  

  Prerequisites: CSCI-UA.0201 and MATH-UA.140 with a grade of C or better.

  There are many courses that can teach you how to use commercial computer graphics packages and APIs. This course, in contrast, will teach you how to build 3D computer graphics from the ground up. This will include 3D modeling, animation, and rendering. At the end of the semester you will have built your own complete working real-time 3D computer graphics systems that run in web browsers.

• CSCI-UA.0480-​007
  (9619) Special Topics: Agile Software Development and DevOps  Amos Bloomberg TR 12:30-1:45PM CIWW 317
  

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

  Agile software development has come to describe a specific approach and toolset that allow for the requirements of a software project to change as a project progresses without disrupting schedules, budgets, and responsibilities.  The field of DevOps, a portmanteau of development and operations has introduced further processes and infrastructure to automate many of the tasks required in such development.  Together, Agile's methodology and DevOps' automation have increased the speed, robustness, and scalability with which software is developed today. Upon completion of this course, students will understand the core methodologies, technologies, and tools used for software engineering.

• CSCI-UA.0480-​008
  (9677) Special Topics: Applied Internet Technology  Joseph Versoza MW 11:00-12:15PM 12WV L120
  

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

  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.

• CSCI-UA.0480-​009
  (9846) Special Topics: Natural Language Processing  Adam Meyers MW 12:30-1:45PM Silv 414
  

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

  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.

• CSCI-UA.0480-​010
  (10065) Special Topics: Open Source Software Development  Joanna Klukowska MW 3:30-4:45PM CIWW 517
  

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

  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.

• CSCI-UA.0480-​011
  (10493) Special Topics: Introduction to Computer Security  Joseph Bonneau MW 12:30-1:45PM 60 Fifth Ave 150
  

  Prerequisites: CSCI-UA.0201 with a grade of C or better. Recommended: CSCI-UA.202 Operating Systems.

  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.

• CSCI-UA.0480-​012
  (19670) Special Topics: Advanced Computer Systems  Michael Walfish TR 3:30-4:45PM CIWW 201
  

  Prerequisites: CSCI-UA.0202 Operating Systems.

  This course will deepen students' understanding of complex computer systems: how these systems work, how to approach a given system or proposal critically, and how to design and build systems. Topics will include the interface between computer hardware and software, concurrency and parallelism, performance analysis, virtual machines, sandboxing, distributed systems, networking and the Internet, and security. The work will include substantial implementation exercises, critical reading and in-class discussion of research papers, and a final project. Because of the close relationship among critical reading, critical thinking, and clear communication, there may also be exercises to build writing skill.

• CSCI-UA.0480-​013 Special Topics: TBA  TENTATIVE TR 8:00-9:15AM CIWW 317
  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-​014
  (21937) Special Topics: iOS Programming  Nathan Hull MW 12:30-1:45PM CIWW 101
  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.0490-​001
  (19672) Special Topics: Programming Languages  Edward Yang TR 11:00-12:15PM Silv 414
  

  Covers topics in programming languages at an advanced level. Detailed course descriptions are available when topics are announced.

  
  
  Prerequisites: Topics determine prerequisites.

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