Computational approaches to the analysis, understanding, and generation of natural language text at scale. Emphasis on machine learning techniques for NLP, including deep learning and large language models. Applications may include information extraction, sentiment analysis, question answering, summarization, machine translation, and conversational AI. Discussion of datasets, benchmarking and evaluation, interpretability, and ethical considerations.
Due to significant overlap in content, only one of COMS 4705 or Barnard COMS 3705BC may be taken for credit.
Data, models, visuals; various facets of AI, applications in finance; areas: fund, manager, security selection, asset allocation, risk management within asset management; fraud detection and prevention; climate finance and risk; data-driven real estate finance; cutting-edge techniques: machine learning, deep learning in computational, quantitative finance; concepts: explainability, interpretability, adversarial machine learning, resilience of AI systems; industry utilization
Basic statistical principles and algorithmic paradigms of supervised machine learning.
Prerequisites:
Multivariable calculus (e.g. MATH1201 or MATH1205 or APMA2000), linear algebra (e.g. COMS3251 or MATH2010 or MATH2015), probability (e.g. STAT1201 or STAT4001 or IEOR3658 or MATH2015), discrete math (COMS3203), and general mathematical maturity. Programming and algorithm analysis (e.g. COMS 3134).
COMS 3770 optionally satisfies all math prerequisites for this course.
In this class we will consider the various forms and functions of humor in written prose, discussing techniques and approaches to humor writing. Students will write their own humorous stories and essays which we will read and discuss in class, focusing not only on what is or isn't funny, but on how humor can be advantageously used to increase the power of an overall piece. The class will also break down stories, novels, and essays from a variety of authors-Bill Hicks' political satire; the darkly comedic fiction of Barry Hannah and Paul Beatty; the absurd humor of Tina Fey and Baratunde Thurston; Anthony Lane's charming British snarkiness; Spy Magazine's sharply parodic voice; Woody Allen's one-liners; Lena Dunham's zeitgeist comedy-in an effort to better understand what makes their humor work. Students will be asked to write stories inspired and influenced by these authors. As we critique each other's work, we will investigate strategies related to the craft of humor writing, including self-deprecation, political satire, humor and the other, going blue, dark comedy, schtick, humor as a means vs. humor as an end, crossing the line, and how to write funny without sacrificing substance.
The course focuses on the nexus between energy and security as it reveals in the policies and interaction of leading energy producers and consumers. Topics include: Hydrocarbons and search for stability and security in the Persian Gulf, Caspian basin, Eurasia, Africa and Latin America; Russia as a global energy player; Analysis of the impact of Russia's invasion of Ukraine on energy markets, global security, and the future of the energy transition; Role of natural gas in the world energy balance and European energy security; Transformation of the global energy governance structure; Role and evolution of the OPEC; Introduction into energy economics; Dynamics and fundamentals of the global energy markets; IOCs vs NOCs; Resource nationalism, cartels, sanctions and embargoes; Asia's growing energy needs and its geo-economic and strategic implications; Nuclear energy and challenges to non-proliferation regime; Alternative and renewable sources of energy; Climate change as one of the central challenges of the 21st century; Analysis of the policies, technologies, financial systems and markets needed to achieve climate goals. Climate change and attempts of environmental regulation; Decarbonization trends, international carbon regimes and search for optimal models of sustainable development. Special focus on implications of the shale revolution and technological innovations on U.S. energy security.
Introduction to the mathematical tools and algorithmic implementation for representation and processing of digital pictures, videos, and visual sensory data. Image representation, filtering, transform, quality enhancement, restoration, feature extraction, object segmentation, motion analysis, classification, and coding for data compression. A series of programming assignments reinforces material from the lectures.
The interaction of intelligence and political decision-making in the U.S. other Western democracies, Russia and China. Peculiarities of intelligence in the Middle East (Israel, Iran, Pakistan). Intelligence analyzed both as a governmental institution and as a form of activity, with an emphasis on complex relations within the triangle of intelligence communities, national security organizations, and high-level political leadership. Stages and disciplines of intelligence process. Intelligence products and political decision-making. The function of intelligence considered against the backdrop of rapid evolution of information technologies, changing meaning of homeland security, and globalization. Particular emphasis on the role of intelligence in the prevention of terrorism and WMD proliferation.
Research training course. Recommended in preparation for laboratory related research.
Research training course. Recommended in preparation for laboratory related research.
Research training course. Recommended in preparation for laboratory related research.
Research training course. Recommended in preparation for laboratory related research.
Working with a faculty member and a team of 3-5 graduate or undergraduate students, students will have the opportunity to work on a small research project. Students can enroll ENGI E3900/4900 for zero credit, zero fees; students who wish to earn academic credit can enroll in the faculty member’s independent research course or Fieldwork. Specific requirements for the project are defined by the faculty members. Research groups meet weekly with their faculty member. Students are also encouraged to submit bi-weekly progress reports to the faculty member. Upon completion of the research project (end of July/beginning of August), each research team will participate in a research symposium to present their research and deliverables. Note: Enrollment in this course acknowledges the student’s participation in research with an Engineering faculty member.
Working with a faculty member and a team of 3-5 graduate or undergraduate students, students will have the opportunity to work on a small research project. Students can enroll ENGI E3900/4900 for zero credit, zero fees; students who wish to earn academic credit can enroll in the faculty member’s independent research course or Fieldwork. Specific requirements for the project are defined by the faculty members. Research groups meet weekly with their faculty member. Students are also encouraged to submit bi-weekly progress reports to the faculty member. Upon completion of the research project (end of July/beginning of August), each research team will participate in a research symposium to present their research and deliverables. Note: Enrollment in this course acknowledges the student’s participation in research with an Engineering faculty member.
Working with a faculty member and a team of 3-5 graduate or undergraduate students, students will have the opportunity to work on a small research project. Students can enroll ENGI E3900/4900 for zero credit, zero fees; students who wish to earn academic credit can enroll in the faculty member’s independent research course or Fieldwork. Specific requirements for the project are defined by the faculty members. Research groups meet weekly with their faculty member. Students are also encouraged to submit bi-weekly progress reports to the faculty member. Upon completion of the research project (end of July/beginning of August), each research team will participate in a research symposium to present their research and deliverables. Note: Enrollment in this course acknowledges the student’s participation in research with an Engineering faculty member.
Prerequisite(s): Approval by a faculty member who agrees to supervise the work. Independent work involving experiments, computer programming, analytical investigation, or engineering design.