Computing and Data Science (Undergraduate)
2 credits – 5 Weeks
Archives
Financial Information Systems (TECH-UB 50)
The financial services industry is being transformed by regulation, competition, consolidation, technology and globalization. These forces will be explored, focusing on how technology is both a driver of change as well as the vehicle for their implementation. The course focuses on payment products and financial markets, their key systems, how they evolved and where might they be going, algorithmic trading, market structure dark, liquidity and electronic markets. Straight through processing, risk management and industry consolidation and convergence will be viewed in light of current events. The course objective is to bring both the business practitioner and technologist closer together. Topics will be covered through a combination of lectures, readings, news, case studies and projects.
Computing and Data Science (Undergraduate)
3 credits – 12 Weeks
Sections (Fall 2020)
TECH-UB 50-000 (21263)09/23/2020 – 12/16/2020 Wed6:00 PM – 9:00 PM (Evening)at Washington SquareInstructed by Donefer, Bernard
Networks, Crowds and Markets (TECH-UB 60)
This is a course on how the social, technological, and natural worlds are connected, and how the study of networks sheds light on these connections. Topics include: social network structure and its effects on business and culture; crowdsourcing; games on graphs; the propagation through networks of information, fads and disease; small worlds, network effects, and “rich-get-richer” phenomena; the power of networks for prediction; the power of the network for web search; networks and social revolutions, and the melding of economics, machine learning, and technology into new markets, such as “prediction markets” or markets for on-line advertisements.The class will be a combination of lectures based on the textbook and guest lectures from well-known experts on these topics, primarily Stern faculty (a well-known center of excellence for research on networks, crowds, and markets).One main goal of this class is to work our way through most of the new, acclaimed textbook: Networks, Crowds, and Markets: Reasoning About a Highly Connected World, by David Easley and Jon Kleinberg. http://www.cs.cornell.edu/home/kleinber/networks-book/networks-book.pdf The textbook readings will be complemented with classic and recent research papers.
Computing and Data Science (Undergraduate)
3 credits – 15 Weeks
Sections (Spring 2023)
TECH-UB 60-000 (19341)at Washington SquareInstructed by
Info Technology in Business & Society (TECH-UB 9001)
Provides the background necessary to make decisions about computer-based information systems and to be an “end-user”. Two major parts of the course are hands-on experience with personal computers and information systems management. Group and individual computer assignments expose students to electronic spreadsheet analysis and database management on a personal computer. Management aspects focus on understanding computer technology, systems analysis and design, and control of information processing by managers.
Computing and Data Science (Undergraduate)
4 credits – 14 Weeks
Sections (Spring 2025)
TECH-UB 9001-000 (4660)01/20/2025 – 04/30/2025 Mon,Wed6:00 PM – 7:00 PM (Evening)at NYU Madrid (Global)Instructed by Sarasua, Asier
TECH-UB 9001-000 (4195)01/20/2025 – 04/28/2025 Tue9:00 AM – 11:00 AM (Morning)at NYU Prague (Global)Instructed by Cermakova, Senta
TECH-UB 9001-000 (20800)02/24/2025 – 05/30/2025 Thu9:00 AM – 12:00 AM (Morning)at NYU Sydney (Global)Instructed by
Projects in Programming and Data Sciences (TECH-UB 24)
This course is the follow-on course to Introduction to Programming and Data Science, which is offered in the Fall. It is recommended for undergraduate students who 1) are interested in jobs in the rapidly growing fields of data science and data analytics or 2) who are interested in acquiring the technical and data analysis skills that are becoming increasingly relevant in all disciplines. Intro to Programming and Data Science forms the basis for this course, but it is not a pre-requisite. Students with basic knowledge of programming in Python and SQL are welcome to join. This course covers select topics that build on the prior course work and is largely project based. Much of the course will be project-based work, with students working on projects that utilize the skills used in this and the prior Programming and Data Science course.
Computing and Data Science (Undergraduate)
3 credits – 15 Weeks
Sections (Spring 2023)
TECH-UB 24-000 (19343)at Washington SquareInstructed by
TECH-UB 24-000 (19344)at Washington SquareInstructed by
Social Media & Digital Marketing (TECH-UB 38)
This course examines the major trends in digital marketing using tools from business analytics and data science. While there will be sufficient attention given to top level strategy used by companies adopting digital marketing, the focus of the course is also on business analytics: how to make firms more intelligent in how they conduct business in the digital age. Measurement plays a big role in this space. The course is complemented by cutting-edge projects and various business consulting assignments that the Professor has been involved in with various companies over the last few years. Prof Ghose has consulted in various capacities for Apple, AMD, Berkeley Corporation, Bank of Khartoum, CBS, Dataxu, Facebook, Intel, NBC Universal, Samsung, Showtime, 3TI China, and collaborated with Alibaba, China Mobile, Google, IBM, Indiegogo, Microsoft, Recobell, Travelocity and many other leading Fortune 500 firms on realizing business value from IT investments, internet marketing, business analytics, mobile marketing, digital analytics and other topics.We will learn about statistical issues in data analyses such as selection problem, omitted variables problem, endogeneity, and simultaneity problems, autocorrelation, multi-collinearity, assessing the predictive power of a regression and interpreting various numbers from the output of a statistical package, various econometrics-based tools such as simple and multivariate regressions, linear and non-linear probability models (Logit and Probit), estimating discrete and continuous dependent variables, count data models (Poisson and Negative Binomial), cross-sectional models vs. panel data models (Fixed Effects and Random Effects), and various experimental techniques that help can tease out correlation from causality such as randomized field experiments.
Computing and Data Science (Undergraduate)
3 credits – 15 Weeks
Sections (Spring 2023)
TECH-UB 38-000 (19338)01/23/2023 – 05/08/2023 Thu6:00 PM – 9:00 PM (Evening)at Washington SquareInstructed by
Introduction to Programming and Data Science (TECH-UB 23)
This course is recommended for undergraduate students without programming experience who are interested in building capabilities in the rapidly growing fields of data science and data analytics. This hands-on coding course does not have any prerequisites and is meant to help students acquire programming and data analysis skills that are becoming increasingly relevant for entrepreneurial, corporate, and research jobs. The course offers an introduction to programming (using Python) and databases (using SQL). We will cover topics related to collection, storage, organization, management, and analysis of data. There is a strong focus on live coding in the classroom, with discussion of examples.
Computing and Data Science (Undergraduate)
3 credits – 15 Weeks
Sections (Spring 2023)
TECH-UB 23-000 (19340)at Washington SquareInstructed by
TECH-UB 23-000 (19342)at Washington SquareInstructed by
TECH-UB 23-000 (19345)at Washington SquareInstructed by
Info Tech in Bus & Society (TECH-UB 1)
Provides the background necessary to make decisions about computer-based information systems and to be an “end-user”. Two major parts of the course are hands-on experience with personal computers and information systems management. Group and individual computer assignments expose students to electronic spreadsheet analysis and database management on a personal computer. Management aspects focus on understanding computer technology, systems analysis and design, and control of information processing by managers.
Computing and Data Science (Undergraduate)
4 credits – 15 Weeks
Sections (Spring 2023)
TECH-UB 1-000 (19329)at Washington SquareInstructed by
TECH-UB 1-000 (19330)at Washington SquareInstructed by
TECH-UB 1-000 (19331)at Washington SquareInstructed by
TECH-UB 1-000 (19336)at Washington SquareInstructed by
TECH-UB 1-000 (19337)at Washington SquareInstructed by
TECH-UB 1-000 (19339)at Washington SquareInstructed by