Course Schedule

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• CSCI-GA.1170-​002
  DS-GA.1170
  (2279) Fundamental Algorithms Recitation  Alan Siegel
  Office Hours R 5:10-6:00PM CIWW 109
  

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

  
  
  Prerequisites: At least one year of experience with a high-level language such as Pascal, C, C++, or Java; and familiarity with recursive programming methods and with data structures (arrays, pointers, stacks, queues, linked lists, binary trees).
• CSCI-GA.2110-​002
  (2281) Programming Languages Recitation  Zvonimir Pavlinovic
  Office Hours R 6:10-7:00PM CIWW 109
  

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

  
  
  Prerequisites: Students taking this class should already have substantial programming experience.
• CSCI-GA.2112-​001
  MATH-GA 2043-001
  (2282) Scientific Computing   Jonathan Goodman R 5:10-7:00PM CIWW 1302
  Methods for numerical applications in the physical and biological sciences, engineering, and finance. Basic principles and algorithms; specific problems from various application areas; use of standard software packages.
  
  Prerequisites: Multivariate calculus and linear algebra. Some programming experience recommended.
• CSCI-GA.2130-​001
  (19699) Compiler Construction  Eva Rose
  Office Hours R 5:10-7:00PM CIWW 312
  This is a capstone course based on compilers and modern programming languages. The topics covered include structure of one-pass and multiple-pass compilers; symbol table management; lexical analysis; traditional and automated parsing techniques, including recursive descent and LR parsing; syntax-directed translation and semantic analysis; run-time storage management; intermediate code generation; introduction to optimization; and code generation. The course includes a special compiler-related capstone project, which ties together concepts of algorithms, theory (formal languages), programming languages, software engineering, computer architecture, and other subjects covered in the MS curriculum. This project requires a substantial semester-long programming effort, such as construction of a language compilation or translation system that includes lexical and syntactic analyzers, a type checker, and a code generator.
  
  Prerequisites: CSCI-GA 1170, CSCI-GA 2110, and CSCI-GA 2250.
• CSCI-GA.2262-​001
  (2753) Data Communications and Networks  Jean-Claude Franchitti
  Office Hours R 7:10-9:00PM CIWW 312
  

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

  
  
  Prerequisites: Students must have a working knowledge of fundamental data structures and associated algorithms. For some of the practical aspects of the course, a working knowledge of an object-oriented programming language (e.g., C++, C#, or preferably Java) is expected. An undergraduate course in data communication and networks is helpful but not required.
• CSCI-GA.2271-​001
  (2887) Computer Vision   Rob Fergus
  Office Hours R 7:10-9:00PM Silv 405
  

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

  
  
  Prerequisites: CSCI-GA 1170
• CSCI-GA.2830-​001
  (19695) The Lean Launch Pad  Evan Korth
  Office Hours
  Frank Rimalovski R 10:00-12:00PM 16WP 106 Additional information: Open only to students in the MS-CEI program.
  

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

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

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

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

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

  
  
  Prerequisites: CSCI-GA 2250 or equivalent Operating Systems course; programming experience in C/C++, Java, or Python for assignments and final project; CSCI-GA 2262, CSCI-GA 2620, or undergraduate course in networks. A familiarity with databases and Linux will be useful.
• CSCI-GA.3033-​012
  (3029) Special Topics: Vision Meets Machine Learning  Davi Geiger
  Office Hours R 5:10-7:00PM CIWW 201
  

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

  
  
  Prerequisites: Students who take this class should have familiarity with linear algebra, probability, and calculus.
• CSCI-GA.3033-​022
  (22529) Special Topics: High Performance Machine Learning  Alessandro Morari
  Office Hours
  Giacomo Domeniconi R 7:10-9:00PM CIWW 201
  

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

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

  Suggested resources:

  • Logistic Regression - tutorial
  • Neural Networks - short manuscript
  • Convolutional Neural Networks - tutorial
• CSCI-GA.3110-​001
  (3312) Honors Programming Languages  Patrick Cousot
  Office Hours TR 3:30-4:45PM 60 Fifth Ave C15
  The course will introduce a panorama of programming languages concepts underlying the main programming language paradigms (such as imperative, functional, object-oriented, logic, concurrent, and scripting languages) and present in detail the formal methods (code semantics, specification, and verification) used in modern high quality assurance tools for software safety and security. A programming project (design and implementation of an interpreter/compiler for an dynamic object-oriented mini-language) will be programmed in OCaml, a multiparadigm language introduced at the beginning of the course.
  
  Prerequisites: Permission of the instructor for master’s students
• CSCI-GA.3520-​001
  (2294) Honors Analysis of Algorithms  Subhash Khot TR 9:30-10:45AM CIWW 317
  Design of algorithms and data structures. Review of searching, sorting, and fundamental graph algorithms. In-depth analysis of algorithmic complexity, including advanced topics on recurrence equations and NP-complete problems. Advanced topics on lower bounds, randomized algorithms, amortized algorithms, and data structure design as applied to union-find, pattern matching, polynomial arithmetic, network flow, and matching.
  
  Prerequisites: Permission of the instructor for master’s students.
• CSCI-GA.3850-​004
  (2305) PhD Seminar: Formal Methods**  Thomas Wies
  Office Hours 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.
• CORE-UA.0109-​002
  (9858) Quantitative Reasoning: Recitation  Chandra Prakash Konkimalla
  Office Hours R 9:30-10:45AM Wav 668
  

  This course teaches key mathematical concepts using the new Python programming language. The first part of the course teaches students how to use the basic features of Python: operations with numbers and strings, variables, Boolean logic, control structures, loops and functions. The second part of the course focuses on the phenomena of growth and decay: geometric progressions, compound interest, exponentials and logarithms. The third part of the course introduces three key mathematical concepts: trigonometry, counting problems and probability. Students use Python to explore the mathematical concepts in labs and homework assignments. No prior knowledge of programming is required.

  
  
  Prerequisites: Department Permission
• CSCI-UA.0002-​001
  (7496) Intro To Computer Programming  Nathan Hull
  Office Hours TR 12:30-1:45PM CIWW 202
  

  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
  (7497) Intro To Computer Programming  Craig Kapp
  Office Hours TR 11:00-12:15PM Silv 520
  

  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
  (7500) Intro To Computer Programming  Joshua Clayton
  Office Hours TR 9:30-10:45AM 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-​009
  (9018) Intro To Computer Programming  Jerry Waxman
  Office Hours TR 3:30-4:45PM CIWW 517
  

  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
  (9627) Intro To Computer Programming  Michell Cardona
  Office Hours TR 8:00-9:15AM CIWW 312
  

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

  
  
  Prerequisites: Three years of high school mathematics or equivalent. No prior computing experience is assumed. Students with any programming experience should consult with the department before registering. Students who have taken or are taking Introduction to Computer Science (CSCI-UA 101) will not receive credit for this course. Does not count toward the computer science major; serves as the prerequisite for students with no previous programming experience who want to continue into CSCI-UA 101 and pursue the major.
• CSCI-UA.0004-​004
  (7505) Intro to Web Design & Computer Principles  Amos Bloomberg
  Office Hours TR 12:30-1:45PM Silv 411
  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
  (9017) Intro to Web Design & Computer Principles  Joshua Clayton
  Office Hours TR 2:00-3:15PM CIWW 201
  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
  (9197) Intro to Web Design & Computer Principles  Adam Scher
  Office Hours TR 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.0061-​002
  (9430) Web Development And Programming  Sana Odeh
  Office Hours TR 3:30-4:45PM CIWW 101
  Provides a practical approach to web technologies and programming. Students build interactive, secure, and powerful web programs. Covers client and server side technologies for the web.
  
  Prerequisites: Introduction to Computer Programming (CSCI-UA 2) and Introduction to Web Design & Computer Principles (CSCI-UA 4).
• CSCI-UA.0101-​001
  (7507) Intro To Computer Science  Anasse Bari
  Office Hours TR 2:00-3:15PM CIWW 101
  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
  (7508) Intro To Computer Science  Amos Bloomberg
  Office Hours TR 9:30-10:45AM 60 Fifth Ave 110
  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
  (7509) Intro To Computer Science  Teseo Schneider
  Office Hours TR 3:30-4:45PM Silv 411
  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
  (9872) Intro To Computer Science  Nader Nassar
  Office Hours TR 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-​003
  (7513) Data Structures  Anasse Bari
  Office Hours TR 11:00-12:15PM 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-​007
  (9617) Data Structures  Young Kun Ko TR 9:30-10:45AM CIWW 202
  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-​010
  (20947) Data Structures - Recitation  Sachin Shastri
  Office Hours R 9:30-10:45AM CIWW 102
  Use and design of data structures, which organize information in computer memory. Stacks, queues, linked lists, binary trees: how to implement them in a high-level language, how to analyze their effect on algorithm efficiency, and how to modify them. Programming assignments.
  
  Prerequisites: Introduction to Computer Science (CSCI-UA 101).
• CSCI-UA.0201-​001
  (7516) Computer Systems Organization  Mohamed Zahran
  Office Hours TR 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-​003
  (9044) Computer Systems Organization  Mohamed Zahran
  Office Hours TR 3:30-4:45PM 60 Fifth Ave 150
  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
  (9758) Computer Systems Organization - Recitation  Lingfan Yu
  Office Hours R 12:30-1:45PM CIWW 312
  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
  (24410) Computer Systems Organization  Allan Gottlieb
  Office Hours TR 3:30-4:45PM CIWW 512
  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
  (7518) Operating Systems  Allan Gottlieb
  Office Hours TR 2:00-3:15PM 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-​002
  (7520) Basic Algorithms - Recitation  Harish Karthikeyan R 3:30-4:45PM 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-​003
  (10325) Basic Algorithms  Amir Shpilka
  Office Hours TR 3:30-4:45PM CIWW 102
  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.0380-​001
  (7521) Topics of General Interest: Interactive Computing  Craig Kapp
  Office Hours TR 2:00-3:15PM CIWW 202
  

  In this course you will learn how to develop multimedia applications for both the desktop and the web. The course focuses on general programming techniques with an emphasis on the production of interactive graphical environments. In addition, a number of advanced topics will be covered including image processing, video games, simulations, basic computer vision, augmented reality (AR), virtual reality (VR) and data visualization techniques.

  
  
  Prerequisites: CSCI-UA 2 and CSCI-UA 4, or permission of Instructor
• CSCI-UA.0472-​001
  (22793) Artificial Intelligence   Ernest Davis
  Office Hours TR 9:30-10:45AM 60 Fifth Ave 150
  Many cognitive tasks that people can do easily and almost unconsciously have proven extremely difficult to program on a computer. Artificial intelligence tackles the problem of developing computer systems that can carry out these tasks. Focus is on three central areas in AI: representation and reasoning, machine learning, and natural language processing.
  
  Prerequisites: Computer Systems Organization (CSCI-UA 201) and Basic Algorithms (CSCI-UA 310).
• CSCI-UA.0480-​001
  (19651) Special Topics: Applied Internet Technology  Joseph Versoza
  Office Hours TR 8:00-9:15AM CIWW 201
  

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

  
  
  Prerequisites: CSCI-UA.0201 with a grade of C or better
• CSCI-UA.0480-​003
  (9267) Special Topics: Applied Internet Technology  Joseph Versoza
  Office Hours TR 11:00-12:15PM Silv 411
  

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

  
  
  Prerequisites: CSCI-UA.0201 with a grade of C or better
• CSCI-UA.0480-​004
  (9268) Special Topics: Intro to Social Networking  Bhubaneswar Mishra
  Office Hours TR 2:00-3:15PM CIWW 1302
  

  Social Networks is a specific example of many forms of networks that have become ubiquitous in our modern society. Their utilities have been enhanced by their ability to generate massive amount of personal data that need to be analyzed and disseminated quickly. The World Wide Web enables information flows among vast number of humans; Facebook, LinkedIn, etc. connect small groups of friends; amazon, eBay, etc. provide opportunities for trading, etc. 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 quorum-sensing, swarming, flocking, social grooming, gossip, etc. 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. This course will introduce the tools, analytics and algorithms for the study of networks and their data. It will show how certain common principles permeate the functioning of these diverse networks: e.g., issues related to robustness, fragility, and interlinkages etc.

  
  
  Prerequisites: CSCI-UA.0201
• CSCI-UA.0480-​006
  (9620) Special Topics: Natural Language Processing  Adam Meyers
  Office Hours TR 8:00-9:15AM Bobst LL150
  

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

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

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