Course Schedule

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

View undergraduate course grid View graduate course grid

Number

Name

Professor(s)

Meet Time

Room

CSCI-GA.1170-001
DS-GA.1170-001
(5644) Fundamental Algorithms Chee Yap M 4:55-6:55PM CIWW 109

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.2110-003
(5652) Programming Languages Cory Plock M 4:55-6:55PM Silv 401

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
(5655) Operating Systems Hubertus Franke M 12:30-2:30PM Silv 408

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
(5723) Numerical Methods I Florian Schaefer MW 4:55-6:10PM Silv 208

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
(5662) Artificial Intelligence Paul Bethe M 4:55-6:55PM 194M 206

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.2572-001
DS-GA.1008-001
(5382) Deep Learning Yann LeCun
Alfredo Canziani M 12:30-2:30PM Cant 102

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.2572-002
DS-GA.1008-002
(5384) Deep Learning Lab Alfredo Canziani M 2:45-3:35PM Cant 102 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
(5716) 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
(5717) Entrepreneurship Capstone Lab Evan Korth M 12:30-1:20PM 60 Fifth Ave 110 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
(5687) Special Topics: Cryptocurrencies and Decentralized Ledgers Joseph Bonneau M 7:10-9:10PM 60 Fifth Ave 110

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.3033-110
(5691) Special Topics: Technologies for Finance Anirudh Sivaraman M 7:10-9:10PM CIWW 101

Course Description:

This is a new masters seminar that will explore topics at the intersection of finance and computing technologies. The course will include a mix of lectures from the instructor, lectures from invited speakers, and assigned readings.

Tentative list of topics:
Network technologies: microwave links, FPGAs, layer 1 switches, multicast, programmable switches, Cloud technologies: Challenges of operating exchange infrastructure in the cloud, Synchronized clocks: The role of synchronized time in stock exchanges: PTP, WhiteRabbit, PPS, Software solutions, etc.; High-frequency trading: History, trading algorithms, limit order books, market making, speed races, batch auctions, AI meets finance: BloombergGPT and related technologies, Secure payments, Programming language techniques: OCaml, Confidential computing for fintech, Central bank digital currencies, Distributed systems: Consensus, designing central exchange servers, etc., Dark pools

Prerequisites: Prerequisites vary according to topic.
CSCI-GA.3033-121
(5692) 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.3033-134
(5696) Special Topics: The Science of Deep Learning Pratyusha Sharma M 2:45-4:45PM 60 Fifth Ave C10

Course Description:

Large language models generalize in ways we did not design and fail in ways we did not anticipate. This course is about understanding why. This course will take an empirical approach to unpacking this question: building language models from scratch to develop hands-on fluency, then using that fluency to ask scientific questions about generalization. What does compute-optimal training actually mean? What do data quality, repetition, and domain diversity do to what a model learns? When and why does chain-of-thought help? and more. Students will learn to build transformers from scratch, fit scaling laws, build data pipelines, and run fine-tuning experiments, not as engineering exercises, but as instruments for forming and testing hypotheses. By the end, students will be equipped to read the frontier literature critically, design experiments, and pursue research questions in one of the most consequential and but incompletely understood areas of science.

Prerequisites: deep learning, linear algebra, probability, proficiency in Python and PyTorch.
CSCI-GA.3033-137
(5698) Special Topics: Information Theory and Applications in CS Marshall Ball M 12:30-2:30PM CIWW 317

Course Description:

In the late 1940s, Claude Shannon introduced a mathematical theory of information, quantifying information in terms of uncertainty. Since Shannon's pioneering work on the limits of data compression and reliable/secure communication, intuitions and techniques from information theory have impacted not just our modern communication infrastructure but also a diverse array of other scientific endeavors, including theoretical computer science. In this course, we will begin by covering the foundations of information theory (entropy, mutual information, KL-divergence, etc.) before branching off to explore various applications, primarily in theoretical computer science. Potential application topics include: channel and source coding, error correcting codes, communication complexity, hardness amplification, data structures, Kolmogorov complexity, information-theoretic cryptography, pseudoentropy, the Lovasz Local Lemma, and applications in combinatorics. While there are no specific prerequisites, fluency in basic probability and mathematical maturity are required.

Prerequisites: No official prerequisites. However, fluency in basic probability and mathematical maturity is required.
CSCI-GA.3033-139
(5700) Special Topics: Quantum Cryptography Fermi Ma M 2:45-4:45PM Bobst LL150

Course Description:

Quantum computers will profoundly change the landscape of modern cryptography. Most famously, Shor’s algorithm will enable quantum computers to break much of the cryptography that currently secures the internet. But the impact of quantum computers on cryptography goes far beyond breaking existing cryptosystems. Quantum computers will also open the door to new kinds of cryptographic protocols that leverage quantum phenomena. In recent years, there has been an explosion of activity in this area. Not only has there been a flurry of new quantum cryptographic protocols, but surprisingly, studying these protocols has yielded deep insights into computational complexity and even fundamental physics.

The goal of this course will be to survey recent developments at the intersection of quantum computing and cryptography, with an emphasis on basic concepts and techniques. Since this is a rapidly evolving area, this course will also highlight key open questions and encourage students to formulate their own research problems.

Prerequisites: Prerequisites vary according to topic.
CSCI-GA.3033-148
(21778) Special Topics: Learning to Match Distributions: Optimal Transport, Flow Matching & Applications Romain Lopez M 4:55-6:55PM

Course Description:

This special topics course explores how to match and transform probability distributions for machine learning applications. The course begins with a few lectures on optimal transport and flow matching, and transitions into a reading group covering contemporary methods and applications across scientific domains. A background in probability and statistics is expected; familiarity with convex optimization is helpful but not required.

Prerequisites: Prerequisites vary according to topic.
CSCI-GA.3520-001
(5665) Honors Analysis of Algorithms Subhash Khot M 5:10-7:40PM Silv 520

Course Description:
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.3812-001
(5707) Information Technology Projects * Jean-Claude Franchitti M 6:10-9:10PM Silv 509

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.0001-002
(21896) Computers and Society: Introduction to Computer Programming with AI Assistance Craig Kapp MW 2:00-3:15PM Kimmel 808

Course Description:
An introduction to the fundamentals of computer programming and computational thinking. Students design, write, and debug programs while learning to collaborate effectively with artificial intelligence tools. The course emphasizes problem decomposition, system design, and the evaluation of code. No prior knowledge of programming or AI is assumed.

Prerequisites: No prior computing experience is assumed. Not intended for computer science majors.
CSCI-UA.0002-001
(8896) Intro To Computer Programming (No Prior Experience) Craig Kapp MW 8:00-9:15AM Bobst LL138

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
(8900) Intro To Computer Programming (No Prior Experience) Jiri Motejlek MW 11:00-12:15PM 60 Fifth Ave 110

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.0002-006
(8901) Intro To Computer Programming (No Prior Experience) Karl Rosenberg MW 12:30-1:45PM Tisch LC11

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
(8902) Intro To Computer Programming (No Prior Experience) Khye Borg Liew MW 2:00-3:15PM 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.0002-009
(8904) Intro To Computer Programming (No Prior Experience) Joshua Clayton MW 3:30-4:45PM 194M 206

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.0002-013
(22007) Intro To Computer Programming (No Prior Experience) Amanda Steigman MW 8:00-9:15AM 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.0004-001
(8908) Intro to Web Design & Computer Principles Alvaro Olsen MW 8:00-9:15AM 60 Fifth Ave 150

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
(8910) Intro to Web Design & Computer Principles Mark Ramos MW 11:00-12:15PM 60 Fifth Ave 150

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
(8912) Intro to Web Design & Computer Principles Mark Ramos MW 2:00-3:15PM Silv 208

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
(8913) Intro to Web Design & Computer Principles Alvaro Olsen MW 3:30-4:45PM Silv 411

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
(8916) Web Development And Programming Sana Odeh MW 2:00-3:15PM GCASL 279

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
(8917) Intro To Computer Science Nader Nassar MW 8:00-9:15AM 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.0101-003
(8919) Intro To Computer Science Sana Odeh MW 11:00-12:15PM 194M 206

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.0101-005
(8920) Intro To Computer Science Hilbert Gene Locklear MW 12:30-1:45PM 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.0101-008
(8923) Intro To Computer Science Sana Odeh MW 3:30-4:45PM 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.0102-010
(8927) Data Structures Joanna Klukowska MW 9:30-10:45AM Silv 408 Additional information: In-person recitation for Section 9

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.0102-020
(8932) Data Structures Evan Korth MW 12:30-1:45PM CIWW 109

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.0102-031
(8941) Data Structures - Recitation TBA M 9:30-10:45AM 194M 206 Additional information: In-person recitation for Section 30

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
(8945) Data Structures Federico Sichetti 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.0201-010
(8947) Computer Systems Organization Douglas Moody MW 9:30-10:45AM CIWW 101 Additional information: Required Recitation is Section 11

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: CSCI-UA.0102
CSCI-UA.0201-030
(8951) Computer Systems Organization Jinyang Li MW 3:30-4:45PM 60 Fifth Ave 150

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: CSCI-UA.0102
CSCI-UA.0202-001
(8955) 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.0310-010
(8957) Basic Algorithms Ernest Davis MW 9:30-10:45AM CIWW 109 Additional information: In-person recitation for Section 09

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.0310-020
(8959) Basic Algorithms Janani Sundaresan 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.0380-003
(22018) Topics of General Computing Interest: Interactive Computing Craig Kapp MW 11:00-12:15PM GCASL 369

Course Description:
Detailed descriptions available when topics are announced. Typical offerings include Computing in the Humanities and Arts and Introduction to Flash Programming. Does not count toward the computer science major.

Prerequisites: CSCI-UA.0002
CSCI-UA.0381-001
(8985) Programming Tools for the Data Scientist Hasan Aljabbouli MW 2:00-3:15PM Silv 206

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
(8994) Agile Software Development and DevOps TBA MW 9:30-10:45AM 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
(8987) Applied Internet Technology Joseph Versoza MW 12:30-1:45PM 194M 203

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
(8969) Object Oriented Programming Hasan Aljabbouli MW 3:30-4:45PM Silv 206

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.0474-001
(8970) Software Engineering TBA MW 12:30-1:45PM 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.0479-001
(8988) 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
(8990) Data Management and Analysis Matthew Zeidenberg MW 3:30-4:45PM Kimmel 808

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
(8976) 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.0480-062
(21315) Special Topics: Computer Networks Jinkun Geng MW 11:00-12:15PM GCASL 361

Course Description:

This course will introduce students to computer networks, using today's Internet as an example. Topics covered include socket programming, routing, forwarding, reliable transmission, congestion control, and medium access control. The course will involve a good deal of programming in Python. Familiarity with programming, algorithms, and basic probability is expected. Prerequisites: Computer Systems Organization (CSCI-UA 201), Basic Algorithms (CSCI-UA.0310), and Discrete Mathematics (Math UA 120); or permission of the department.

Prerequisites: CSCI-UA.0201
CSCI-UA.0480-063
(8977) 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
CSCI-UA.0480-076
(22206) Special Topics: Technology, Law, and Policy Sunoo Park MW 3:30-4:45PM CIWW 312

Course Description:
Detailed course descriptions are available when advanced topics are announced each semester. Typical offerings include, but are not limited to, Bioinformatics, Building Robots, Computer Graphics, Machine Learning, Network Programming, Computer Vision, and Multimedia for Majors.

Prerequisites: CSCI-UA.0201

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Classroom Locations

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