Course Schedule

Current semester Fall 2026, and future semesters are now available to view.

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Number

Name

Professor(s)

Meet Time

Room

CSCI-GA.1170-002
DS-GA.1170-002
(5645) Fundamental Algorithms Recitation Bingwei Zhang F 11:15-12:05PM 19UP 102 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.

Required Foundational course for MSCS, MSIS

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.1170-006
DS-GA.1170-002
(5647) Fundamental Algorithms Recitation Bingwei Zhang F 2:45-3:35PM Silv 414 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.

Required Foundational course for MSCS, MSIS

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
(5651) Programming Languages Recitation Seong-Heon Jung F 12:30-1:20PM Meyr 122 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.2110-005
(5653) Programming Languages Recitation Satyapragnya Kar F 11:15-12:05PM Silv 401 Additional information: Recitation for Section 003

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.2110-006
(5654) Programming Languages Recitation Sundara Satish F 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.2810-001
(5710) Design and Innovation* Gary Zamchick F 10:15-12:15PM Silv 407 Additional information: Open only to students in the MS-CEI program

Course Description:

Only open to MS students in the Computing, Entrepreneurship, and Innovation program.

This is an intensive idea-incubation, computing-centric design class where students will be exposed to a spectrum of tech challenges, latest and future technology trends (using case studies) and will need to iteratively propose and refine bold computing centric ideas for real problems. Students will also initiate the process of translating their ideas to initial prototypes. Right from the beginning, students in the class will form small teams where each team will work on a single project idea that solves an important real world problem. Students will be provided exposure to basic tools and platforms that can be leveraged by individual teams in their project design and implementation. In addition to idea incubation, the class will provide a beginner's background to tech startups including: product development cycle, how to pitch your idea, product market fit, fundraising and venture capital, customer discovery. Teams are expected to constantly interact with other teams to discuss and exchange ideas.

Prerequisites: None
CSCI-GA.2810-002
(5711) Design and Innovation Lab* Gary Zamchick F 12:30-1:20PM Silv 407 Additional information: Lab for Section 001

Course Description:

Only open to MS students in the Computing, Entrepreneurship, and Innovation program.

This is an intensive idea-incubation, computing-centric design class where students will be exposed to a spectrum of tech challenges, latest and future technology trends (using case studies) and will need to iteratively propose and refine bold computing centric ideas for real problems. Students will also initiate the process of translating their ideas to initial prototypes. Right from the beginning, students in the class will form small teams where each team will work on a single project idea that solves an important real world problem. Students will be provided exposure to basic tools and platforms that can be leveraged by individual teams in their project design and implementation. In addition to idea incubation, the class will provide a beginner's background to tech startups including: product development cycle, how to pitch your idea, product market fit, fundraising and venture capital, customer discovery. Teams are expected to constantly interact with other teams to discuss and exchange ideas.

Prerequisites: None
CSCI-GA.3033-091
(5690) Special Topics: Introduction to Deep Learning and LLM based Generative AI Systems Parijat Dube
Chen Wang F 7:10-9:10PM Tisch LC11

Course Description:

This course serves as a graduate-level introduction to Deep Learning systems, with an emphasis on LLM-based Generative AI systems. The course will cover several topics related toDeep Learning (DL) systems and their performance. Both algorithmic and system related building blocks of DL systems will be covered including DL training algorithms, network architectures, and best practices for performance optimization. The course will have an in-depth exploration of Large Language Models (LLMs), covering key areas towards advanced topics including attention mechanisms, transformer models, prompt engineering, LLM applications including RAG, tool assisted agents, model context protocol (MCP), toolless multi-agents, pre-training strategies, Reinforcement Learning with Human Feedback (RLHF), efficient LLM serving techniques, fine-tuning methods, and benchmarking specifically for LLMs. The students will gain practical experience working on different stages of LLM life cycle, including model pretraining, fine tuning, GenAI application development and deployment. The assignments will be mostly hands-on involving standard LLM frameworks (Pytorch, vLLM) and open-source technologies.

Prerequisites: An introductory graduate level machine learning course. Working knowledge of Python, Pytorch and experience using Jupyter Notebook
CSCI-GA.3033-925
(5706) Special Topics: Graphics Processing Units (GPUs): Architecture & Programming Recitation Lalita Gupta F 11:15-12:05PM Meyr 122 Additional information: Recitation for Section 025

Course Description:

This is the recitation for section 025. Refer to the lecture for description.

Prerequisites: Prerequisites vary according to topic.
CSCI-UA.0101-007
(8922) Intro To Computer Science Anasse Bari F 2:00-4:45PM GCASL 279

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.0102-011
(8928) Data Structures - Recitation TBA F 9:30-10:45AM CIWW 317 Additional information: In-person recitation for Section 10

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.0102-012
(8929) Data Structures - Recitation Elina Adibi F 11:00-12:15PM CIWW 317 Additional information: In-person recitation for Section 10

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.0102-013
(8930) Data Structures - Recitation TBA F 12:30-1:45PM CIWW 317 Additional information: In-person recitation for Section 10

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.0102-021
(8933) Data Structures - Recitation TBA F 11:00-12:15PM CIWW 101 Additional information: In-person recitation for Section 20

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.0102-022
(8934) Data Structures - Recitation TBA F 12:30-1:45PM CIWW 101 Additional information: In-person recitation for Section 20

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.0102-023
(8935) Data Structures - Recitation TBA F 2:00-3:15PM CIWW 101 Additional information: In-person recitation for Section 20

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.0102-030
(8939) Data Structures Anasse Bari F 11:00-1:30PM Silv 408

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.0102-041
(8944) Data Structures - Recitation Joseph Tung F 9:30-10:45AM CIWW 202 Additional information: In-person recitation for Section 40

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.0102-051
(8946) Data Structures - Recitation Satyapragnya Kar F 2:00-3:15PM CIWW 317 Additional information: In-person recitation for Section 50

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.0102-061
(21347) Data Structures - Recitation TBA F 3:30-4:45PM Additional information: In-person recitation for Section 60

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.0201-011
(8948) Computer Systems Organization - Recitation Satyapragnya Kar F 9:30-10:45AM GCASL 279 Additional information: Required Lecture is Section 10

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.0201-021
(8950) Computer Systems Organization - Recitation TBA F 9:30-10:45AM Online Additional information: Required Lecture is Section 20

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.0201-031
(8952) Computer Systems Organization - Recitation TBA F 12:30-1:45PM Silv 206

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.0201-041
(8954) Computer Systems Organization - Recitation Navya Kumar F 11:00-12:15PM Silv 206 Additional information: Required Lecture is Section 40

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.0310-011
(8958) Basic Algorithms - Recitation Ramakrishnan Krishnamurthy F 11:00-12:15PM Silv 208

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.0310-012
(22021) Basic Algorithms - Recitation Ramakrishnan Krishnamurthy F 9:30-10:45AM Silv 401

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.0310-021
(8960) Basic Algorithms - Recitation Manas Ghai F 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.0310-031
(8962) Basic Algorithms - Recitation Vaibhav Chaudhari F 9:30-10:45AM Online

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.0310-041
(8964) Basic Algorithms - Recitation Manas Ghai F 9:30-10:45AM 194M 307

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.0473-002
(8981) Fundamentals of Machine Learning - Recitation TBA F 9:30-10:45AM 60 Fifth Ave 150 Additional information: In-person recitation for Section 01

Course Description:

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), Linear Algebra (MATH-UA 140) and Probability and Statistics (MATH-UA 185). Students may take any of the following courses in place of MATH-UA 185: Theory of Probability (MATH-UA 333), Mathematical Statistics (MATH-UA 334), Honors Theory of Probability (MATH-UA 338) OR Data Analysis (MA-UY 2224).
CSCI-UA.0473-003
(8982) Fundamentals of Machine Learning - Recitation TBA F 2:00-3:15PM 60 Fifth Ave 150

Course Description:

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), Linear Algebra (MATH-UA 140) and Probability and Statistics (MATH-UA 185). Students may take any of the following courses in place of MATH-UA 185: Theory of Probability (MATH-UA 333), Mathematical Statistics (MATH-UA 334), Honors Theory of Probability (MATH-UA 338) OR Data Analysis (MA-UY 2224).

*

Indicates controlled enrollment (permission number required for registration). Contact your program advisor.
**

Indicates controlled enrollment (permission number required for registration). Contact Santiago Pizzini (pizzini@cs.nyu.edu).
***

Indicates controlled enrollment (permission number required for registration). Contact the instructor.

Classroom Locations

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