Course Schedule

Current semester Fall 2025, and future semesters are now available to view.

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• CSCI-GA.1170-​002
  DS-GA.1170-002
  (8919) Fundamental Algorithms Recitation  Daniel Collins M 5:55-6:45PM 5WP 101 Additional information: Recitation for Section 001
  

  Course Description:

  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
  (8925) Programming Languages Recitation  Elaine Li M 4:55-5:45PM 60 Fifth Ave 150 Additional information: Recitation for Section 001
  

  Course Description:

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

  
  
  Prerequisites: Students taking this class should already have substantial programming experience.
• CSCI-GA.2110-​003
  (8926) Programming Languages  Cory Plock M 4:55-6:55PM CIWW 109
  

  Course Description:

  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.2250-​001
  (8929) Operating Systems  Hubertus Franke M 7:10-9:10PM CIWW 109
  

  Course Description:

  The topics covered include the high-level design of key operating systems concepts such OS structures; process scheduling and synchronization; deadlocks and their prevention; memory management, including (demand) paging; and I/O and file systems. The concepts will be shown in the context of Unix/Linux. The learning is facilitated with labs that implement some of these key design principles and algorithms in C/C++.

  
  
  Prerequisites: None
• CSCI-GA.2420-​001
  MATH-GA 2010-001
  (15848) Numerical Methods I   Benjamin Peherstorfer MW 4:55-6:10PM CIWW 1302
  

  Course Description:

  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.2560-​001
  (8936) Artificial Intelligence   Paul Bethe M 4:55-6:55PM CIWW 101
  

  Course Description:

  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-​002
  DS-GA.1008-002
  (8999) Deep Learning Lab  STAFF M 3:45-4:35PM 5WP 101 Additional information: Lab for Section 001
  

  Course Description:

  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.2840-​001
  (8983) Entrepreneurship Capstone  Evan Korth M 10:15-12:15PM 194M 306A
  

  Course Description:

  Only open to MS students in the Computing, Entrepreneurship, and Innovation 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
  (8984) Entrepreneurship Capstone Lab  Charlie O'Donnell M 12:30-1:20PM 194M 305 Additional information: Lab for Section 001
  

  Course Description:

  Only open to MS students in the Computing, Entrepreneurship, and Innovation 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.3033-​078
  (20497) Special Topics: Cryptocurrencies and Decentralized Ledgers  Joseph Bonneau M 7:10-9:10PM 60 Fifth Ave C15
  

  Course Description:

  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-​086
  (8970) Special Topics: Quantum Computation  Oded Regev M 2:45-4:45PM CIWW 317
  

  Course Description:

  This course will provide an introduction to quantum computation and information. We will cover topics such as the quantum circuit model of computation, the Fourier transform, quantum algorithms like Deutsch-Jozsa, Simon, and Grover, Shor's factoring algorithm and discrete log. Topics in quantum information will also be discussed, such as quantum entanglement, teleportation, superdense coding, and quantum nonlocal games. We will also mention quantum cryptography and quantum key distribution. The course will be of interest to students working in computer science, mathematics, or physics.
  
  Prerequisites include a strong undergraduate background in linear algebra (e.g., NYU’s MATH-UA.0140 Linear Algebra), and some familiarity with discrete probability (e.g., NYU’s MATH-UA 235 Probability and Statistics). Familiarity with theory of computation (e.g., NYU’s CSCI-UA.0310 Basic Algorithms) is a plus. No background in physics is required. Evaluation will be based on class participation, homework, and exams.

  
  
  Prerequisites: Prerequisites include a strong undergraduate background in linear algebra (e.g., NYU’s MATH-UA.0140 Linear Algebra), and some familiarity with discrete probability (e.g., NYU’s MATH-UA 235 Probability and Statistics). Familiarity with theory of computation (e.g., NYU’s CSCI-UA.0310 Basic Algorithms) is a plus. No background in physics is required. Evaluation will be based on class participation, homework, and exams.
• CSCI-GA.3033-​121
  (8969) Special Topics: Programming Parallel Algorithms  Sam Westrick M 10:15-12:15PM 60 Fifth Ave C10
  

  Course Description:

  This course considers the challenge of converting high-level algorithmic ideas into efficient parallel code. We will see how this challenge is greatly simplified by modern programming languages and programming techniques, especially functional programming techniques which make it possible to quickly develop efficient, scalable, and correct implementations. Prior experience with functional programming is helpful but not required. Students will learn how to design, analyze, implement, and evaluate the performance of parallel algorithms across a variety of problem domains (e.g., graph analysis, computational geometry, numerical algorithms, image processing, etc.). In the second half of the course, students will complete a parallel programming project of their own design.

  
  
  Prerequisites: CSCI-GA.2110-001 Programming Languages. Students should be comfortable with recursive programming techniques and familiar with basic data structures and algorithms.
• CSCI-GA.3033-​125
  (20479) Special Topics: Reinforcement Learning with Foundation Models  Sherry Yang M 2:45-4:45PM 60 Fifth Ave 110
  

  Course Description:

  Reinforcement learning has traditionally focused on task-specific, tabula rasa settings with limited prior knowledge. Recent research in applying RL on top of foundation models pretrained on internet-scale data has led to LLMs capable of solving a variety of reasoning, coding, and math problems. RL algorithms combined with video world models have also led to fruitful research outcomes in embodied learning. In this course, we will study these RL algorithms and their practical implications when applied to align foundation models in task-specific downstream settings.

  This course is designed to be a PhD-level research course.  Students taking this course should have successfully completed CSCI-GA.3033-090 Deep Decision Making & Reinforcement Learning usually taught in the spring by Professor Lerrel Pinto.  Students enrolled in this class should also be interested in pursuing conference-style publications in Reinforcement Learning.

  
  
  Prerequisites: Linear algebra, differential equations, CSCI-GA.3033-090 Deep Decision Making & Reinforcement Learning.
• CSCI-GA.3033-​7863
  ROB-GY.7863-A
  (23168) Special Topics: Space Robotics  Benjamin Riviere M 2:00-4:30PM Jacobs 211
  

  Course Description:

  This class will study the math and implementation of planning, learning, and control algorithms through applications in spacecraft, rocket landings, and rover autonomy. We will cover classical topics and emerging research areas in linear and nonlinear dynamics, optimal control, numerical optimization, Bayesian estimation, search-based planning, and reinforcement learning. We will study existing applications like precision rocket landings and martian rover path planning, and proposed future missions like distributed apertures of spacecraft swarms and complex locomotion for planetary exploration.

   

  The goals of the course are: (i) to build fundamental understanding of robot planning, learning, and control, (ii) to introduce applications in aerospace robotics and (iii) to prepare students to become researchers and devise novel methods and algorithms. The grading will be coding-assignments and project-based. This class is targeted towards graduate-level students with familiarity in robotics, linear algebra, differential equations, probability, and Python programming. If you are unsure, feel free to contact Dr. Riviere at riviere.b@nyu.edu.
• CSCI-GA.3812-​001
  (8974) Information Technology Projects *  Jean-Claude Franchitti M 6:10-9:10PM 60 Fifth Ave 110
  

  Course Description:

  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-UA.0002-​001
  (10316) Intro To Computer Programming (No Prior Experience)  Amanda Steigman MW 8:00-9:15AM Kimmel 803
  

  Course Description:

  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 with any reported score on the Computer Science AP examination cannot enroll in this course; Albert will block them from registering for it. 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. Students may not receive credit for both CSCI-UA 2 and CSCI-UA 3.
• CSCI-UA.0002-​003
  (10318) Intro To Computer Programming (No Prior Experience)  Craig Kapp MW 9:30-10:45AM 19W4 101
  

  Course Description:

  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 with any reported score on the Computer Science AP examination cannot enroll in this course; Albert will block them from registering for it. 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. Students may not receive credit for both CSCI-UA 2 and CSCI-UA 3.
• CSCI-UA.0002-​005
  (10320) Intro To Computer Programming (No Prior Experience)  STAFF MW 11:00-12:15PM 194M 204
  

  Course Description:

  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 with any reported score on the Computer Science AP examination cannot enroll in this course; Albert will block them from registering for it. 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. Students may not receive credit for both CSCI-UA 2 and CSCI-UA 3.
• CSCI-UA.0002-​007
  (10322) Intro To Computer Programming (No Prior Experience)  Karl Rosenberg MW 12:30-1:45PM 194M 208
  

  Course Description:

  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 with any reported score on the Computer Science AP examination cannot enroll in this course; Albert will block them from registering for it. 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. Students may not receive credit for both CSCI-UA 2 and CSCI-UA 3.
• CSCI-UA.0002-​009
  (10324) Intro To Computer Programming (No Prior Experience)  Khye Borg Liew MW 2:00-3:15PM Online Online
  

  Course Description:

  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 with any reported score on the Computer Science AP examination cannot enroll in this course; Albert will block them from registering for it. 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. Students may not receive credit for both CSCI-UA 2 and CSCI-UA 3.
• CSCI-UA.0002-​011
  (10326) Intro To Computer Programming (No Prior Experience)  Joshua Clayton MW 3:30-4:45PM CIWW 109
  

  Course Description:

  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 with any reported score on the Computer Science AP examination cannot enroll in this course; Albert will block them from registering for it. 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. Students may not receive credit for both CSCI-UA 2 and CSCI-UA 3.
• CSCI-UA.0004-​001
  (10328) Intro to Web Design & Computer Principles  Alvaro Olsen MW 8:00-9:15AM CIWW 109
  

  Course Description:

  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
  (10330) Intro to Web Design & Computer Principles  Mark Ramos MW 11:00-12:15PM CIWW 202
  

  Course Description:

  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
  (10332) Intro to Web Design & Computer Principles  Alvaro Olsen MW 3:30-4:45PM CIWW 312
  

  Course Description:

  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
  (10333) Intro to Web Design & Computer Principles  Mark Ramos MW 2:00-3:15PM 194M 206
  

  Course Description:

  Introduces students to both the practice of web design and the basic principles of computer science. The practice component covers not only web design but also current graphics and software tools. The principles section includes an overview of hardware and software, the history of computers, and a discussion of the impact of computers and the Internet.
  
  Prerequisites: Three years of high school mathematics or equivalent. No prior computing experience is assumed. Students with computing experience should consult with the department before registering.
• CSCI-UA.0061-​001
  (10335) Web Development And Programming  Sana Odeh MW 3:30-4:45PM CIWW 101
  

  Course Description:

  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 (No Prior Experience) (CSCI-UA 2) or Introduction to Computer Programming (Limited Prior Experience) (CSCI-UA 3), and Introduction to Web Design and Computer Principles (CSCI-UA 4). Students that have successfully completed Applied Internet Technology (CSCI-UA 467) are NOT eligible to take this course.
• CSCI-UA.0101-​001 Intro To Computer Science  CANCELLED MW 8:00-9:15AM Bobst LL138
  

  Course Description:

  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 (No Prior Experience) (CSCI-UA 2) or Introduction to Computer Programming (Limited Prior Experience) (CSCI-UA 3), or a score of 3 on the AP Computer Science exam (scores of 4 and 5 are acceptable prerequisites for students who wish to take CSCI-UA 101 before entering CSCI-UA 102; they will forfeit the AP credit), or departmental permission assessed by placement exam.
• CSCI-UA.0101-​003
  (10338) Intro To Computer Science  Tobias Blickhan MW 9:30-10:45AM 60 Fifth Ave 110
  

  Course Description:

  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 (No Prior Experience) (CSCI-UA 2) or Introduction to Computer Programming (Limited Prior Experience) (CSCI-UA 3), or a score of 3 on the AP Computer Science exam (scores of 4 and 5 are acceptable prerequisites for students who wish to take CSCI-UA 101 before entering CSCI-UA 102; they will forfeit the AP credit), or departmental permission assessed by placement exam.
• CSCI-UA.0101-​004
  (10339) Intro To Computer Science  Sana Odeh MW 11:00-12:15PM CIWW 317
  

  Course Description:

  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 (No Prior Experience) (CSCI-UA 2) or Introduction to Computer Programming (Limited Prior Experience) (CSCI-UA 3), or a score of 3 on the AP Computer Science exam (scores of 4 and 5 are acceptable prerequisites for students who wish to take CSCI-UA 101 before entering CSCI-UA 102; they will forfeit the AP credit), or departmental permission assessed by placement exam.
• CSCI-UA.0101-​006
  (10341) Intro To Computer Science  Sana Odeh MW 12:30-1:45PM CIWW 101
  

  Course Description:

  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 (No Prior Experience) (CSCI-UA 2) or Introduction to Computer Programming (Limited Prior Experience) (CSCI-UA 3), or a score of 3 on the AP Computer Science exam (scores of 4 and 5 are acceptable prerequisites for students who wish to take CSCI-UA 101 before entering CSCI-UA 102; they will forfeit the AP credit), or departmental permission assessed by placement exam.
• CSCI-UA.0101-​008
  (10343) Intro To Computer Science  Hilbert Gene Locklear MW 2:00-3:15PM CIWW 101
  

  Course Description:

  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 (No Prior Experience) (CSCI-UA 2) or Introduction to Computer Programming (Limited Prior Experience) (CSCI-UA 3), or a score of 3 on the AP Computer Science exam (scores of 4 and 5 are acceptable prerequisites for students who wish to take CSCI-UA 101 before entering CSCI-UA 102; they will forfeit the AP credit), or departmental permission assessed by placement exam.
• CSCI-UA.0101-​010
  (10345) Intro To Computer Science  Michael Tao MW 3:30-4:45PM GCASL 361
  

  Course Description:

  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 (No Prior Experience) (CSCI-UA 2) or Introduction to Computer Programming (Limited Prior Experience) (CSCI-UA 3), or a score of 3 on the AP Computer Science exam (scores of 4 and 5 are acceptable prerequisites for students who wish to take CSCI-UA 101 before entering CSCI-UA 102; they will forfeit the AP credit), or departmental permission assessed by placement exam.
• CSCI-UA.0102-​010
  (10347) Data Structures  Joanna Klukowska MW 9:30-10:45AM Cant 200
  

  Course Description:

  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), or a score of 4 or 5 on the AP Computer Science examination.
• CSCI-UA.0102-​040
  (10364) Data Structures  Alan Amin MW 2:00-3:15PM CIWW 312
  

  Course Description:

  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), or a score of 4 or 5 on the AP Computer Science examination.
• CSCI-UA.0102-​050 Data Structures  CANCELLED MW 11:00-12:15PM
  

  Course Description:

  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), or a score of 4 or 5 on the AP Computer Science examination.
• CSCI-UA.0201-​001
  (10370) Computer Systems Organization  Douglas Moody MW 9:30-10:45AM CIWW 101
  

  Course Description:

  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
  (10374) Computer Systems Organization  Benjamin Goldberg MW 3:30-4:45PM Silv 408
  

  Course Description:

  This section is a fast paced version of the regular CSO class. Students who are considering research in their senior year or graduate school should take this class.
  
  This course aims to give students an understanding of what's "under the hood" in a modern computer system. Take this class to boost your confidence on a computer and to understand how everything works like never before! We'll cover basic topics including how machines represent and execute programs, how user program interact with the OS, as well as advanced topics including how to write networked and concurrent programs. These topics are supported by a series of challenging lab assignments in C.

  
  
  Prerequisites: CSCI-UA.0102
• CSCI-UA.0202-​001
  (10378) Operating Systems  Michael Walfish MW 11:00-12:15PM CIWW 109
  

  Course Description:

  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
  (10380) Basic Algorithms  Oded Regev MW 9:30-10:45AM CIWW 109
  

  Course Description:

  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); Discrete Mathematics (MATH-UA 120); and either Calculus I (MATH-UA 121) OR Mathematics for Economics I (MATH-UA 211).
• CSCI-UA.0310-​003
  (10382) Basic Algorithms  STAFF MW 2:00-3:15PM CIWW 202
  

  Course Description:

  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); Discrete Mathematics (MATH-UA 120); and either Calculus I (MATH-UA 121) OR Mathematics for Economics I (MATH-UA 211).
• CSCI-UA.0380-​001
  (10391) Topics of General Interest: Interactive Computing  Craig Kapp MW 2:00-3:15PM 194M 304
  

  Course Description:

  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.0002, CSCI-UA.0004
• CSCI-UA.0381-​001
  (10409) Programming Tools for the Data Scientist  Hasan Aljabbouli MW 2:00-3:15PM Silv 411
  

  Course Description:

  Lecture and laboratory.  Building applications in Python using a project-based learning approach. Students use Python packages in a variety of applied areas, such as textual analysis and data visualization. Does not count toward the computer science major. 

  
  
  Prerequisites: Data Science for Everyone (DS-UA 111) or equivalent proficiency in Python, and either Introduction to Computer Programming (No Prior Experience) (CSCI-UA 2) or Introduction to Computer Programming (Limited Prior Experience) (CSCI-UA 3).
• CSCI-UA.0430-​001
  (10416) Agile Software Development and DevOps  Amos Bloomberg MW 9:30-10:45AM Online Online
  

  Course Description:

  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 in the software industry today.

  
  
  Prerequisites: Computer Systems Organization (CSCI-UA 201)
• CSCI-UA.0467-​002
  (10410) Applied Internet Technology  Joseph Versoza MW 12:30-1:45PM CIWW 109
  

  Course Description:

  Applied Internet Technology is a practical introduction to creating modern web applications. It covers full-stack (that is, every aspect of building a database driven web application: server programming, database implementation, frontend markup, styling and interactivity) web development. It includes topics such as database and data model design, web application architecture, separation of logic and presentation, handling user input and processing form data, managing asynchronous processes, strategies for creating real-time web applications, and handling client-side interactivity. Students will use current server and client-side web frameworks and libraries to build dynamic, data-driven sites. Various applications to support development will also be introduced, such as version control, static analysis tools, and build systems.

  
  
  Prerequisites: Computer Systems Organization (CSCI-UA 201). Students who complete Applied Internet Technology (CSCI-UA 467) with a C or better are not eligible to take Web Development and Programming (CSCI-UA 61).
• CSCI-UA.0470-​001
  (10392) Object Oriented Programming  Hasan Aljabbouli MW 3:30-4:45PM Silv 411
  

  Course Description:

  Introduces the important concepts of object-oriented design and languages, including code reuse, data abstraction, inheritance, and dynamic overloading. Covers in depth those features of Java and C++ that support object-oriented programming and gives an overview of other object-oriented languages of interest. Significant programming assignments stressing object-oriented design. Not offered every academic year.

  
  
  Prerequisites: Computer Systems Organization (CSCI-UA 201).
• CSCI-UA.0472-​001
  (10393) Artificial Intelligence   Ernest Davis MW 11:00-12:15PM Online Online
  

  Course Description:

  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.0474-​001
  (10394) Software Engineering  Amos Bloomberg MW 2:00-3:15PM Online Online
  

  Course Description:

  An intense hands-on study of practical techniques and methods of software engineering. Topics include advanced object-oriented design, design patterns, refactoring, code optimization, universal modeling language, threading, user interface design, enterprise application development, and development tools. All topics are integrated and applied during the semester long group project. The aim of the project is to prepare students for dynamics in a real workplace. Members of the group meet on a regular basis to discuss the project and to assign individual tasks. Students are judged primarily on the final project presentations. Not offered every academic year. 

  
  
  Prerequisites: Computer Systems Organization (CSCI-UA 201).
• CSCI-UA.0475-​001
  (10408) Predictive Analytics  Ahmad Emad MW 8:00-9:15AM CIWW 101
  

  Course Description:

  Predictive analytics is the art and science of extracting useful information from historical data and present data for the purpose of predicting future trends. In this course, students will be introduced to the phases of the analytics life-cycle and will gain an understanding of a variety of tools and machine learning algorithms for analyzing data and discovering forward insights. Several techniques will be introduced including: data preprocessing techniques, data reduction algorithms, data clustering algorithms, data classification algorithms, uplifting algorithms, association rules, data mining algorithms, recommender systems, and more. This course aims to provide students with skills of the new generation of data scientists that will allow them to structure, analyze and derive useful insights from data that could help make better decisions.

  
  
  Prerequisites: Computer Systems Organization (CSCI-UA 201), Basic Algorithms (CSCI-UA 310), and Linear Algebra (MATH-UA 140) or Honors Linear Algebra (MATH-UA 148).
• CSCI-UA.0479-​001
  (10411) Data Management and Analysis  Joseph Versoza MW 11:00-12:15PM CIWW 101
  

  Course Description:

  Extracting, transforming and analyzing data in myriad formats. Using traditional 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 API programming.

  
  
  Prerequisites: Data Structures (CSCI-UA 102). Students that complete Data Management and Analysis (CSCI-UA 479) with a C or better are not eligible to take Database Design and Implementation (CSCI-UA 60).
• CSCI-UA.0479-​003
  (14796) Data Management and Analysis  Matthew Zeidenberg MW 3:30-4:45PM 60 Fifth Ave 150
  

  Course Description:

  Extracting, transforming and analyzing data in myriad formats. Using traditional 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 API programming.

  
  
  Prerequisites: Data Structures (CSCI-UA 102). Students that complete Data Management and Analysis (CSCI-UA 479) with a C or better are not eligible to take Database Design and Implementation (CSCI-UA 60).
• CSCI-UA.0480-​052
  (10399) Special Topics: Algorithmic Problem Solving  Joanna Klukowska MW 12:30-1:45PM 60 Fifth Ave 150
  

  Course Description:

  Student must also register for a Recitation section.

  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.

  
  
  Prerequisites: CSCI-UA.0310
• CSCI-UA.0480-​063
  (10401) Special Topics: Introduction to Computer Security  Joseph Bonneau MW 2:00-3:15PM CIWW 109
  

  Course Description:

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

  
  
  Prerequisites: CSCI-UA.0201

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