Course Schedule

Current semester Fall 2024, and future semesters are now available to view.

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Number

Name

Professor(s)

Meet Time

Room

CSCI-GA.1170-002
(7956) Fundamental Algorithms Recitation Bingwei Zhang M 5:55-6:45PM CIWW 109 Additional information: Recitation for Section 001

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
(7962) Programming Languages Recitation Markus de Medeiros M 4:55-5:45PM CIWW 109

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

Prerequisites: Students taking this class should already have substantial programming experience.
CSCI-GA.2110-003
(7963) Programming Languages Cory Plock M 4:55-6:55PM GCASL 383

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
(7968) Operating Systems Hubertus Franke M 7:10-9:10PM CIWW 109
The topics covered include a review of linkers and loaders and the high-level design of key operating systems concepts such as process scheduling and synchronization; deadlocks and their prevention; memory management, including (demand) paging and segmentation; and I/O and file systems, with examples from Unix/Linux and Windows. Programming assignments may require C, C++, Java, or C#.
CSCI-GA.2420-001
MATH-GA 2010-001
(7972) Numerical Methods I Benjamin Peherstorfer MW 4:55-6:10PM CIWW 1302
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
(7975) Artificial Intelligence Paul Bethe M 4:55-6:55PM CIWW 101

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.2840-001
(20908) Entrepreneurship Capstone Evan Korth M 10:15-12:15PM 194M 304

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
(20927) Entrepreneurship Capstone Lab Charlie O'Donnell M 12:30-1:20PM 194M 306B

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.3033-087
DS-GA.3001-013
(8067) Special Topics in Data Science: Bayesian Machine Learning Andrew Gordon Wilson M 10:00-11:40AM GCASL 383

This course aims to provide students with a strong grasp of the fundamental principles underlying Bayesian model construction and inference. We will go into particular depth on Gaussian process and probabilistic deep learning models. The course will comprise three units, alongside a major research project component. 1. Model Construction and Inference: Parametric models, support, inductive biases, gradient descent, sum and product rules, graphical models, exact inference, approximate inference (Laplace approximation, variational methods, MCMC), model selection and hypothesis testing, Occam's razor, non-parametric models. 2. Gaussian Processes: From finite basis expansions to infinite bases, kernels, function-space modelling, marginal likelihood, non-Gaussian likelihoods, Bayesian optimization. 3. Bayesian Deep Learning: Fully connected, convolutional, and recurrent networks, generative models, normalizing flows, loss surfaces, deep kernel learning, subspace inference.

Prerequisites: A strong foundation in basic linear algebra, probability, statistics, multivariable calculus, and programming. A careful reading of the first three chapters of Christopher Bishop's Pattern Recognition and Machine Learning (2006) before class starts. Prior courses on machine learning are strongly recommended.
CSCI-GA.3033-111
(8010) Special Topics: Protein Design Rob Fergus M 7:10-9:10PM 12WP L120

This new course will explore recent exciting developments in the application of machine learning and computational methods to the design of new-to-nature proteins. These advances promise a revolution in drug design, scientific tooling, materials and more. The course will consist of a mix of lectures (given by the instructor and external speakers) and seminar-style reading groups of recent papers. Assessment will be through class participation (discussions & paper presentations).

Prerequisites: Graduate-level machine learning class. Some knowledge of molecular biology may be useful, although not essential.
CSCI-GA.3033-112
(8017) Special Topics: Fair and Ethical Machine Learning for Social Good Daniel Neill M 10:15-12:15PM GCASL 265

Machine learning (ML) is increasingly used to inform high-stakes decisions that impact individuals' lives and livelihoods. For example, ML algorithms may determine who is given a loan, hired for a job, or sentenced to prison, or how scarce resources are allocated by a hospital or a government agency. It is critical to ensure that these decisions are made in a fair, responsible, and ethical manner, both maximizing the societal benefits and minimizing the harms of ML in practice. The first half of the course will focus primarily on fair ML: defining fairness, building fairer models, and auditing algorithms to identify and correct biases. Fair ML methods, embedded in a broader socio-technical perspective, can mitigate the risks that ML algorithms will create inequity and injustice or that they will exacerbate existing societal disparities. Moreover, fair ML can benefit society by correcting systematic biases in human decisions and by identifying and reducing societal disparities. The second half of the course will consider numerous other aspects of ML ethics (reliability and trustworthiness; privacy and security; interpretability and explainability; transparency and accountability), and will discuss practical challenges and solutions for measuring and optimizing the societal impacts of deployed ML systems. The course will include both lectures on core content and discussion of current research papers. Deliverables will include paper presentations, assignments (including Python coding), and a substantial, semester-long research project.

Prerequisites: A graduate or advanced undergraduate course in machine learning; Python programming including numpy, pandas, and scikit-learn.
CSCI-GA.3812-001
(8018) Information Technology Projects * Jean-Claude Franchitti M 6:10-9:10PM 60 Fifth Ave 110

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
(6854) Intro To Computer Programming (No Prior Experience) Amanda Steigman MW 8:00-9:15AM Tisch LC11

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
(6856) Intro To Computer Programming (No Prior Experience) Waqar Aqeel MW 9:30-10:45AM CIWW 317

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

Prerequisites: Three years of high school mathematics or equivalent. No prior computing experience is assumed. Students with any programming experience should consult with the department before registering. Students 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
(6858) Intro To Computer Programming (No Prior Experience) Emily Zhao MW 11:00-12:15PM GCASL 261

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
(6860) Intro To Computer Programming (No Prior Experience) Emily Zhao MW 12:30-1:45PM GCASL 275

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
(6862) Intro To Computer Programming (No Prior Experience) Adam Meyers MW 2:00-3:15PM Kimmel 808

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
(6864) Intro To Computer Programming (No Prior Experience) Joshua Clayton MW 3:30-4:45PM CIWW 109

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

Prerequisites: Three years of high school mathematics or equivalent. No prior computing experience is assumed. Students with any programming experience should consult with the department before registering. Students 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
(6866) Intro To Computer Programming (No Prior Experience) Na'im Tyson MW 8:00-9:15AM GCASL 388

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.0002-014
(6867) Intro To Computer Programming (No Prior Experience) Karl Rosenberg MW 9:30-10:45AM GCASL 388

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.0002-015
(6868) Intro To Computer Programming (No Prior Experience) Craig Kapp MW 3:30-4:45PM CIWW 317

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

Prerequisites: Three years of high school mathematics or equivalent. No prior computing experience is assumed. Students with any programming experience should consult with the department before registering. Students 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
(6869) Intro to Web Design & Computer Principles Alvaro Olsen MW 8:00-9:15AM CIWW 101
Introduces students to both the practice of web design and the basic principles of computer science. The practice component covers not only web design but also current graphics and software tools. The principles section includes an overview of hardware and software, the history of computers, and a discussion of the impact of computers and the Internet.

Prerequisites: Three years of high school mathematics or equivalent. No prior computing experience is assumed. Students with computing experience should consult with the department before registering.
CSCI-UA.0004-003
(6871) Intro to Web Design & Computer Principles Mark Ramos MW 11:00-12:15PM CIWW 202
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
(6873) Intro to Web Design & Computer Principles Alvaro Olsen MW 3:30-4:45PM CIWW 312
Introduces students to both the practice of web design and the basic principles of computer science. The practice component covers not only web design but also current graphics and software tools. The principles section includes an overview of hardware and software, the history of computers, and a discussion of the impact of computers and the Internet.

Prerequisites: Three years of high school mathematics or equivalent. No prior computing experience is assumed. Students with computing experience should consult with the department before registering.
CSCI-UA.0060-001
(6875) Database Design And Implementation David Prager MW 2:00-3:15PM CIWW 202

Introduces principles and applications of database design and working with data. Students use Python as they prepare, analyze, and work with data and use SQL to study the principles and implementations of relational databases. Also covers other database paradigms, such as NoSQL. Students apply these principles to computer systems and their respective fields of interest.

Prerequisites: Introduction to Computer Programming (No Prior Experience) (CSCI-UA 2) or Introduction to Computer Programming (Limited Prior Experience) (CSCI-UA 3). Students that have successfully completed Data Management and Analysis (CSCI-UA 479) are NOT eligible to take this course.
CSCI-UA.0101-003
(6879) Intro To Computer Science Tobias Blickhan MW 9:30-10:45AM 60 Fifth Ave C15

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
(6880) Intro To Computer Science Sana Odeh MW 11:00-12:15PM CIWW 317

How to design algorithms to solve problems and how to translate these algorithms into working computer programs. Experience is acquired through projects in a high-level programming language. Intended primarily for computer science majors but also suitable for students of other scientific disciplines. Programming assignments.

Prerequisites: Introduction to Computer Programming (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
(6882) Intro To Computer Science Hilbert Gene Locklear MW 12:30-1:45PM Silv 101A

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
(6884) Intro To Computer Science Sana Odeh MW 2:00-3:15PM CIWW 101

How to design algorithms to solve problems and how to translate these algorithms into working computer programs. Experience is acquired through projects in a high-level programming language. Intended primarily for computer science majors but also suitable for students of other scientific disciplines. Programming assignments.

Prerequisites: Introduction to Computer Programming (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
(6886) Intro To Computer Science Michael Tao MW 3:30-4:45PM GCASL 279

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.0102-005
(6892) Data Structures Joanna Klukowska MW 8:00-9:15AM CIWW 109

Use and design of data structures, which organize information in computer memory. Stacks, queues, linked lists, binary trees: how to implement them in a high-level language, how to analyze their effect on algorithm efficiency, and how to modify them. Programming assignments.

Prerequisites: Introduction to Computer Science (CSCI-UA 101), or a score of 4 or 5 on the AP Computer Science examination.
CSCI-UA.0102-007
(6894) Data Structures Max Sklar MW 11:00-12:15PM CIWW 312

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.0102-009
(6896) Data Structures Sungmin Cha MW 12:30-1:45PM 60 Fifth Ave 110

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.0102-011
(6898) Data Structures Alan Amin MW 2:00-3:15PM 60 Fifth Ave 110

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
(6911) Computer Systems Organization Douglas Moody MW 9:30-10:45AM CIWW 101

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
(6915) Computer Systems Organization Benjamin Goldberg MW 3:30-4:45PM Silv 405

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: You need to be comfortable with programming (e.g. in Java) and the UNIX environment.
CSCI-UA.0202-002
(6920) Operating Systems Michael Walfish MW 11:00-12:15PM CIWW 109

Covers the principles and design of operating systems. Topics include process scheduling and synchronization, deadlocks, memory management (including virtual memory), input/output, and file systems. Programming assignments.

Prerequisites: Computer Systems Organization (CSCI-UA 201).
CSCI-UA.0310-001
(6921) Basic Algorithms Rotem Oshman MW 9:30-10:45AM CIWW 109

Introduction to the study of algorithms. Presents two main themes: designing appropriate data structures and analyzing the efficiency of the algorithms that use them. Algorithms studied include sorting, searching, graph algorithms, and maintaining dynamic data structures. Homework assignments, not necessarily involving programming.

Prerequisites: Data Structures (CSCI-UA 102); Discrete Mathematics (MATH-UA 120); and either Calculus I (MATH-UA 121) OR Mathematics for Economics I (MATH-UA 211).
CSCI-UA.0310-003
(6923) Basic Algorithms Alan Siegel MW 2:00-3:15PM Online

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
(6929) Topics of General Interest: Interactive Computing Craig Kapp MW 2:00-3:15PM CIWW 312

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 and CSCI-UA.0004, or permission of Instructor
CSCI-UA.0381-001
(6949) Programming Tools for the Data Scientist Hasan Aljabbouli MW 2:00-3:15PM CIWW 317

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.0467-002
(6951) Applied Internet Technology Joseph Versoza MW 12:30-1:45PM CIWW 109

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
(6930) Object Oriented Programming Hasan Aljabbouli MW 3:30-4:45PM CIWW 101

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
(6931) Artificial Intelligence Ernest Davis MW 11:00-12:15PM Online
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
(6932) Software Engineering Amos Bloomberg MW 2:00-3:15PM Online

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
(23703) Predictive Analytics Ahmad Emad MW 8:00-9:15AM WWH 312

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
(6952) Data Management and Analysis Joseph Versoza MW 11:00-12:15PM CIWW 101

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

Prerequisites: Data Structures (CSCI-UA 102). 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
(6954) Data Management and Analysis Matthew Zeidenberg MW 3:30-4:45PM 60 Fifth Ave 150

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

Prerequisites: Data Structures (CSCI-UA 102). 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
(6936) Special Topics: Algorithmic Problem Solving Joanna Klukowska MW 12:30-1:45PM Silv 520

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.0201 Computer Systems Organization, CSCI-UA.0310 Basic Algorithms. Student must also register for a Recitation section.
CSCI-UA.0480-063
(6938) Special Topics: Introduction to Computer Security Benedikt Bünz MW 2:00-3:15PM CIWW 109

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 201 Computer Systems Organization with a grade of C or better. Recommended: Operating Systems (CSCI-UA.202)

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Classroom Locations

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