MANAGING DATA

• Department: Applied Analytics
• M 8:10 p.m.-10 p.m.
• T 8:10 p.m.-10 p.m.
• S 12:10 p.m.-2 p.m.
• F 12:10 p.m.-2 p.m.
• W 8:10 a.m.-10 a.m.
• Instructor: Nitinchandra Nayak
  Info
• Instructor: Constantine Christakos
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• Instructor: Darshan Desai
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• Instructor: Sridhar Ravula
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• Instructor: Samar Deen
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• 3 points

MANAGING DATA

MANAGING DATA ONLINE

• Department: Applied Analytics
• R 6:10 p.m.-8 p.m.
• Instructor: Robert Simione
  Info
• 3 points

CLINICAL ETHICS

While this course is designed to introduce students to the fundamentals of clinical ethics and the basic terminology and framework of ethical analysis in biomedical ethics, it offers a more sociological perspective, putting the contemporary clinical issues into a broader context. We will look briefly at the development of clinical ethics and its impact on hospital care and doctor-patient relationships, on the prevailing autonomy norm and its critique. The course then focuses on issues encountered in clinical practice such as informed consent, patient capacity, decision-making, end of life, advance directives, medical futility, pediatrics ethics, maternal-fetal conflicts, organ transplantation, cultural competence and diversity of beliefs and others. The course will examine the role of the clinical ethics consultant (CEC) and assignments will mimic the work that CECs may perform in the hospital setting.

Over the span of the semester, students become familiar with the ethical questions surrounding major topics in the clinic with a practical case-based approach toward ethics dilemmas and ethics consultation. During the semester, students in New York attend a meeting of the adult or pediatric ethics committees of New York Presbyterian and Morgan Stanley Children's Hospital or another area hospital, as well as ethics lectures given at the medical center.

Students are expected to complete five case write-ups using a template that will be given by the instructor. Students will be using these cases to refine and hone their ethical analysis skills and to show their knowledge of law, policy and ethical principles and how they might apply to each situation.

• Department: Bioethics
• W 2:10 p.m.-4 p.m.
• R 9:30 a.m.-11:30 a.m.
• Instructor: Barbra Rothschild
  Info
• 3 points

RESEARCH SEMINAR IN HIST

This seminar is a step-by-step introduction to scholarly research in the field of History and Literature. In the course of the seminar, students will carry out the initial research and draft the prospectus for their MA thesis.

• Department: French
• Instructor: George Chauncey
  CULPA: 13 Wikipedia Info
• 3 points

OPERATIONS: BACKBONE OF THE COMPANY

OPERATIONS: BACKBONE OF C

• Department: Insurance Management
• Instructor: Amanda Bill
  Info
• 3 points

TAX PLANNING

The Tax Planning course explores the various methods of the U.S. tax system, its development, its applicability to individual (and corporate) taxpayers, and steps taxpayers of various income and wealth levels take to determine,
meet, and minimize their tax obligations, depending on their goals. Students will learn how to identify sources, nature, and taxability of taxpayers’ income and gains, to determine the deductibility of any expenses they incur to reduce income, identify credits they may have to offset taxes due, understand filing and payment obligations, and apply the methods of minimizing tax - avoidance, deferral, and use of lower brackets or realization by other taxpayers.

• Department: Wealth Management
• Instructor: Adam Ludman
  Info
• 3 points

Introduction to French and Francophone H

French and Francophone Hi

Shadow course for 3409. Please email the DGS for permission to enroll.

• Department: French
• Instructor: Zachary Desjardins-Mooney
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• 3 points

MARKET RISK MANAGEMENT

This course provides the tools to measure and manage market risk in the context of large financial institutions. The volume and complexity of the data itself, at large institutions, makes it a challenge to generate actionable information. We will take on this challenge to master the path from data to decisions.

We cover the essential inputs to the engines of financial risk management: VaR, Expected Exposure, Potential Exposure, Expected Shortfall, backtesting, and stress testing as they apply to asset management and trading. We explore the strengths and weaknesses of these different metrics and the tradeoffs between them. We also cover how regulatory frameworks impact both the details and the strategy of building these engines. Lastly, we cover counterparty-credit methodologies, mainly as they apply to Trading Book risk.

• Department: Enterprise Risk Management
• T 6:10 p.m.-8 p.m.
• W 6:10 p.m.-8 p.m.
• Instructor: Igor Axenov
  Info
• Instructor: Deniz Ozenbas
  Info
• 3 points

MARKET RISK MANAGEMENT

This course provides the tools to measure and manage market risk in the context of large financial institutions. The volume and complexity of the data itself, at large institutions, makes it a challenge to generate actionable information. We will take on this challenge to master the path from data to decisions.

We cover the essential inputs to the engines of financial risk management: VaR, Expected Exposure, Potential Exposure, Expected Shortfall, backtesting, and stress testing as they apply to asset management and trading. We explore the strengths and weaknesses of these different metrics and the tradeoffs between them. We also cover how regulatory frameworks impact both the details and the strategy of building these engines. Lastly, we cover counterparty-credit methodologies, mainly as they apply to Trading Book risk.

• Department: Enterprise Risk Management
• W 6:10 p.m.-8 p.m.
• Instructor: Deniz Ozenbas
  Info
• 3 points

PRACTICAL PRODUCTION II

• Department: Film
• F 9 a.m.-11 a.m.
• F 11 a.m.-1 p.m.
• F 1 p.m.-3 p.m.
• Instructor: Maureen A Ryan
  Info
• 1.5 points

LEADERSHIP IN SPORTS MANAGEMENT

LDRSHP & PERS MGMT IN SPR

TBA

• Department: Sports Management
• T 4:10 p.m.-6 p.m.
• 3 points

LEADERSHIP IN SPORTS MANAGEMENT

LDRSHP & PERS MGMT IN SPR

TBA

• Department: Sports Management
• T 4:10 p.m.-6 p.m.
• Instructor: Gregory B Taylor
  Info
• 3 points

LEADERSHIP IN SPORTS MANAGEMENT

TBA

• Department: Sports Management
• T 4:10 p.m.-6 p.m.
• Instructor: Mary Scott
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• Instructor: Leonard Elmore
  Info
• 3 points

ECONOMETRICS II

• Department: Economics
• T 2:10 p.m.-4 p.m.
• Instructor: Anastasios Magdalinos
  Info
• 3 points

Printmaking on, through, and below the m

Print on, through, & belo

This course offers to the student who may find an examination of printmaking an asset to their art practice.
The course will cover several printmaking processes like relief, intaglio, silkscreen, and monotype. In addition, we will discuss printmaking concepts such as repetition, matrix, original/translation, reproducibility, and multiple considering the works produced in class.
We will involve a separate in-depth study of each process by alternating studio time, demonstrations, field trips, individual and group critiques.
Through the printmaking processes, students will explore assignments and projects and be encouraged to incorporate them into their own body of work.

• Department: Visual Arts
• T 10 a.m.-4 p.m.
• Instructor: Craig Zammiello
  Info
• 3 points

SYMBOLIC LOGIC

Advanced introduction to classical sentential and predicate logic. No previous acquaintance with logic is required; nonetheless a willingness to master technicalities and to work at a certain level of abstraction is desirable. Note: Due to significant overlap, students may receive credit for only one of the following three courses: PHIL UN3411, UN3415, GR5415.

• Department: Philosophy
• MW 10:10 a.m.-11:25 a.m.
• Instructor: Achille Varzi
  CULPA: 30 Wikipedia h-index: 40 Info
• 4 points

CREDIT RISK ANALYTICS

The field of credit risk management is undergoing a quiet revolution as subjective and manually-intensive methods give way to digitization, algorithmic management, and decision-making. This course provides a practical overview and hands-on experience with different methods, and it also provides a view of future technologies and discussions of potential future directions. Participants in this course should be well-positioned to take entry-level analytic positions and help drive strategic decisions.

The first half of the course explores analytics used today for credit risk management. You will learn to create rating and scoring models and a macro scenario-based stress testing model. In the second half of the course, we explore more advanced tools used by the more prominent organizations and fintech firms, including neural net and XGBoost decision tree models.

• Department: Enterprise Risk Management
• R 8:10 p.m.-10 p.m.
• T 6:10 p.m.-8 p.m.
• Instructor: Christopher Mann
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• Instructor: Douglas W Dwyer
  Info
• 3 points

PRINTMAKING I: INTAGLIO

• Department: Visual Arts
• MW 2:30 p.m.-5 p.m.
• Instructor: Jennifer Nuss
  Info
• 3 points

PRINTMAKING II: INTAGLIO

• Department: Visual Arts
• MW 2:30 p.m.-5 p.m.
• Instructor: Jennifer Nuss
  Info
• 3 points

Tech Arts: Post Production II

Tech Arts: Post Production II continues teaching the core techniques for picture and sound editing and the post production workflow process for Columbia Film MFA students. We will cover preparing for a long-form edit, digital script integration, color management and continuity, advanced trimming, and advanced finishing. The hands-on lessons and exercises will be conducted using the industry-standard Non-Linear Editing Systems, Avid Media Composer, and Davinci Resolve. Each week’s class will consist of hands-on demonstrations and self-paced practice using content created by the students and provided by the program.

• Department: Film
• R 10 a.m.-1 p.m.
• Instructor: Michael J Cacioppo Belantara
  Info
• 1.5 points

APPLIED TEXT AND NATURAL LANGUAGE ANALYT

APPLIED TXT & NAT LANG AN

• Department: Applied Analytics
• W 8:10 p.m.-10 p.m.
• Instructor: John Ortega
  h-index: None Info
• 3 points

LIQUIDITY RISK MANAGEMENT

Indicators of companies running into hard times typically include revenue volatility, loss of key personnel, reputational damage, and increased litigation. However, company failures are frequently marked by insufficient liquidity, or the lack of cash to meet obligations. Liquidity risk is the unexpected change in a company’s cash resources or demands on such resources that results in the untimely sale of assets, and/or an inability to meet contractual demands and/or default. In extreme cases, the lack of sufficient cash creates severe losses and results in company bankruptcy.

An institution’s cash resources and obligations can and must be managed. Indeed, the field of liquidity risk management is an established part of treasury departments at sizable institutions. The regularity of cash flows and the turbulence of business and markets must be assessed and quantified. This course provides students the tools and techniques to manage all types of liquidity challenges including the need to sell assets unexpectedly in the market, or work through ‘‘run‐on-the‐bank’’ situations for financial services companies.

• Department: Enterprise Risk Management
• W 8:10 p.m.-10 p.m.
• Instructor: Lindsey de Rechter
  Info
• 3 points

Machine Learning for Finance

The application of Machine Learning (ML) algorithms in the Financial industry is now commonplace, but still nascent in its potential.  This course provides an overview of ML applications for finance use cases including trading, investment management, and consumer banking. 

Students will learn how to work with financial data and how to apply ML algorithms using the data.  In addition to providing an overview of the most commonly used ML models, we will detail the regression, KNN, NLP, and time series deep learning ML models using desktop and cloud technologies. 

The course is taught in Python using Numpy, Pandas, scikit-learn and other libraries.  Basic programming knowledge in any language is required.

• Department: Mathematics
• S 2:40 p.m.-4:30 p.m.
• Instructor: Renzo Silva
  Info
• 3 points

GLOBAL ETHICS

Increasingly, issues of medical research and clinical care are posing complex ethical issues not only in the United States, but in other countries in both the industrialized and the developing world. Yet varying economic, political, social, cultural, and historical contexts shape these issues. In diverse contexts in Asia, Africa, Europe and North and South America, practices and policies, along with cultures and moral values, differ enormously. Yet ethical issues are arising not in isolation, but as part of global communities and discourses. In research, multinational pharmaceutical companies are increasingly conducting studies in both industrialized countries and the developing world, posing numerous ethical tensions. In clinical care, uses of reproductive technologies differ across national borders, leading to “reproductive tourism”. End of life care varies widely, reflecting in part differing attitudes toward death and dying. This course examines the political, economic, social, cultural, philosophical, medical, and historical roots and implications of these issues.

The course meets once a week online for an hour and a half, and offers extensive live-session interaction and post-session discussion forums to explore the various bioethical issues contemplated throughout the semester.

• Department: Bioethics
• R 4:10 p.m.-6 p.m.
• T 6 p.m.-7:45 p.m.
• Instructor: Robert L Klitzman
  Wikipedia Info
• 3 points

BLOCKCHAIN AND ERM

Using Blockchain, decisions can be made without relying on a single centralized authority, allowing for greater transparency and trust between participants. By using smart contracts and distributed ledgers, users can easily create, modify, and manage agreements between stakeholders, ensuring that all parties have access to the same information and can make informed decisions. As a result, Blockchain technology reduces the risks associated with decision-making, and improves efficiency and accuracy. This course first examines the risks and rewards of implementing Blockchain at large organizations engaging in decentralized decision-making processes. The course then explores the Blockchain as a tool for risk management.

• Department: Enterprise Risk Management
• W 8:10 p.m.-10 p.m.
• Instructor: Ivan Bakrac
  Info
• 3 points

PRINTMAKING I: SILKSCREEN

• Department: Visual Arts
• R 10 a.m.-4 p.m.
• Instructor: Ivana K Carman
  Info
• 3 points

IMPACT FINANCE FOR SUSTAINABILITY PRACTI

IMPACT FINANCE FOR STNBLT

This survey course examines a range of sustainable and impact investing fixed income and equity products

before transitioning to the asset owner perspective on sustainable and impact investing. Each class session

includes elements of financial analysis, financial structure, social or environmental impact, and policy and

regulatory context. Brief guest lectures, podcasts, and three experiential exercises bring these topics to life.

At the end of the course, each student will be able to (i) construct a diversified portfolio of impact

investments based on the range of products tackled in class, (ii) integrate ESG into debt and equity valuation,

(iii) develop an impact investing product that an asset manager or investment bank could launch, (iv) develop

an impact investing strategy for an asset owner, and (v) lead either side of the investor-corporate dialogue on

sustainability. The lectures are designed to prepare students for both the impact investing product

development exercise and the impact investing asset owner strategy exercise, and these two exercises are

designed to prepare students for impact investing leadership over the course of their careers.

As an early innovator in social finance, dating back 24 years, the instructor provides students with a practical

toolkit, honed by making mainstream financial institutions and products more beneficial to a broader range

of stakeholders and making specialist impact investment firms more relevant to and integrated with

mainstream markets.

• Department: Sustainability Management
• R 6:10 p.m.-8 p.m.
• Instructor: Bhakti Mirchandani
  Info
• 3 points

Sustainability Value Creation in Private

This course provides an overview of the way sustainability (environmental, social and governance) factors are analyzed in private markets. It focuses on preparing students to implement their understanding of the financial and societal risks and opportunities within the investment making process. In private markets, limited partners (pension funds, endowments, high net-worth individuals) have pushed the sustainability imperative and social consciousness of private equity funds and asset managers by seeking greater clarity around how their money is invested in both a responsible and financially meaningful way. Alongside this trend, an evolving regulatory environment globally has propelled the need to systemize evaluation frameworks for stakeholders within investment functions and advisors who support them.Unlike public markets, sustainability information is harder to glean in private markets and requires a skilled extraction and evaluation process. During this course, we examine a traditional ESG due diligence process embedded within the wider investment lifecycle (sourcing, diligence, hold and exit) through the lens of changing geographic regulatory landscape in financial investing and the market leading frameworks that quantify ESG factors for evaluation. The course culminates with a deal due diligence process that mimics an investment committee (IC) comprised of private equity leaders that understand the commercial and purpose-driven viability of an investment.

• Department: Sustainability Management
• M 4:10 p.m.-6 p.m.
• Instructor: Angela Jhanji
  Info
• 3 points

CLOUD COMPUTING

Data analytics have become an essential component of business intelligence and informed decision making. Sophisticated statistical and algorithmic methodologies, generally known as data science, are now of predominant interest and focus. Yet, the underlying cloud computing platform is fundamental to the enablement of data management and analytics.

This course introduces students to cloud computing concepts and practices ranging from infrastructure and administration to services and applications. The course is primarily focused on the development of practical skills in utilizing cloud services to build distributed and scalable analytics applications. Students will have hands-on exposure to VMs (Virtual Machines), databases, storage, microservices, and AI/ML (Artificial Intelligence and Machine Learning) services through Google Cloud Platform, et al.  Cost and performance characteristics of alternative approaches will also be studied. Topics include: overview of cloud computing, cloud systems, parallel processing in the cloud, distributed storage systems, virtualization, security in the cloud, and multicore operating systems. Throughout, students will study state-of-the-art solutions for cloud computing developed by Google, Amazon, Microsoft, and IBM.

The course modules provide a blend of lecture and reading materials along with class exercises and programming assignments. While extensive programming experience is not required, students taking the course are expected to possess basic Python 3 programming skills.

The desired outcome of the course is the student’s ability to put conceptual knowledge to practical use. Whether you are taking this course for future academic research, for work in industry, or for an innovative startup idea, this course should help you master the fundamentals of cloud computing.

• Department: Applied Analytics
• T 6:10 p.m.-8 p.m.
• Instructor: Mohsen Golalikhani
  Info
• 3 points

Credit Analytics

This course uses a combination of lectures and case studies to introduce students to the modern credit analytics. The objective for the course is to cover major analytic concepts, ideas with a focus on the underlying mathematics used in both credit risk management and credit valuation.  We will start from an empirical analysis of default probabilities (or PD), recovery rates and rating transitions. Then we will introduce the essential concepts of survival analysis as a scientific way to study default.  For credit portfolio we will study and compare different approaches such as CreditPortfolio View, CreditRisk+ as well as copula function approach. For valuation we will cover both single name and portfolio models.

• Department: Mathematics
• F 1:10 p.m.-3:40 p.m.
• Instructor: David X Li
  Info
• 3 points

PRIVACY RISK MANAGEMENT

In today’s digital age, with the collection and usage of personal  information growing at an exponential rate, the study of privacy risk management is crucial. As organizations grapple with the dual challenge of monetizing technological innovation without running afoul of regulatory and legal restrictions, the ERM professional who understands how to identify, assess, and manage privacy risk is in high demand. In this course, students will develop an understanding of the legal frameworks governing data usage, the ethical issues associated with the use of personal information, and how to develop robust privacy frameworks and controls in order to manage privacy risk.

• Department: Enterprise Risk Management
• T 6:10 p.m.-8 p.m.
• Instructor: Alison L Bird
  Info
• 3 points

INTEREST RATES MODELS

The objective of this course is to introduce students to interest rates models and to build step by step a coherent understanding of the interest rates world, from the stripping of a yield curve to the modern frameworks of option pricing. Adopting a practitioner’s perspective, it will put an emphasis on building a strong intuition on the products and models, and will adopt a balanced approach between formal derivation and concrete applications.

• Department: Mathematics
• F 6:10 p.m.-8 p.m.
• Instructor: Paul-Guillaume Fournie
  Info
• 3 points

SPORTS LAW AND ETHICS

• Department: Sports Management
• W 6:10 p.m.-8 p.m.
• Instructor: Carla Varriale
  Info
• 3 points

INTRO TO BLOCKCHAIN, CRYPTO$ & ANALYTICS

BLOCKCHAINCRYPTOCURRENCY &ANL

TBD

• Department: Applied Analytics
• T 6:10 p.m.-8 p.m.
• Instructor: Siddhartha Dalal
  Info
• 3 points

CLINICAL ETHICS: END OF LIFE CARE

This course will explore how medical decisions at the end of life regarding both curative and palliative care are influenced by medical, legal and philosophical principles and social norms. We will explore how the development of clinical practice standards for patients with advanced disease have evolved in response to advances in treatment and societal assertion of consumerist rights of self determination. This work will assist students in the Bioethics Masters Program to develop the consultation skills needed to interact effectively with patients, even under difficult circumstances. We will build on the knowledge base established in the Introduction to Clinical Ethics course (BIETPS5400) to develop the specific insights and skills needed by clinicians and other professionals to support patients and caregivers who confront dilemmas in end of life care management. Students will develop the analytic and communication techniques needed to advise treating clinicians who seek guidance on management of end of life care for patients, and communicating prognosis and treatment options to their patients’ families. The skills developed in this course will be useful to students who will confront ethical dilemmas in their roles as treating clinicians, health care administrators, ethics committee members, compliance officers, and patient advocates. This course will also provide a valuable foundation for students who intend to pursue more advanced training in clinical ethics consultation, in order to prepare for a career as an institutionally based Ethics Consultant.

• Department: Bioethics
• F 9:10 a.m.-11 a.m.
• Instructor: David N Hoffman
  h-index: 2 Info
• 3 points

A MATHEMATICAL APPROACH TO GENERATIVE AI

MATHMATCL APPRCH GENERATI

Generative AI (“GenAI") is reshaping the global economy and the future of work by revolutionizing problem-solving, optimizing complex systems, and enabling data-driven decision-making. Its profound impact spans across natural language understanding, image generation, and predictive analytics, marking a paradigm shift that necessitates a deep and rigorous understanding of its mathematical foundations. This course is designed to equip students with a comprehensive framework for exploring the mathematical principles underpinning GenAI. Emphasizing statistical modeling, optimization, and computational techniques, the curriculum provides the essential tools to develop and analyze cutting-edge generative models.

• Department: Mathematics
• S 4:30 p.m.-6:20 p.m.
• Instructor: Konstantin Kuchenmeister
  Info
• 3 points

CIRCULAR ECONOMY FOR SUSTAINABILITY PROF

Throughout history, societies have discovered resources, designed and developed them into textiles,

tools and structures, and bartered and exchanged these goods based on their respective values.

Economies emerged, driven by each society’s needs and limited by the resources and technology

available to them. Over the last two centuries, global development accelerated due in large part to the

overextraction and use of finite resources, whether for energy or materials, and supported by vast

technological advancements. However, this economic model did not account for the long-term impacts of

the disposal or depletion of these finite resources and instead, carried on unreservedly in a “take-make’-

waste” manner, otherwise known as a linear economy. Despite a more profound understanding of our

planet’s available resources, the environmental impact of disposal and depletion, and the technological

advancements of the last several decades, the economic heritage of the last two centuries persists today;

which begs the question: what alternatives are there to a linear economy?

The premise of this course is that through systems-thinking, interdisciplinary solutions for an alternative

economic future are available to us. By looking at resources’ potential, we can shape alternative methods

of procurement, design, application, and create new market demands that aim to keep materials,

products and components in rotation at their highest utility and value. This elective course will delve into

both the theory of a circular economy - which would be a state of complete systemic regeneration and

restoration as well as an optimized use of resources and zero waste - and the practical applications

required in order to achieve this economic model. Achieving perfect circularity represents potentially

transformative systemic change and requires a fundamental re-think of many of our current economic

structures, systems and processes.

This is a full-semester elective course which is designed to create awareness among sustainability

leaders that those structures, systems and processes which exist today are not those which will carry us

(as rapidly as we need) into a more sustaining future. The class will be comprised of a series of lectures,

supported by readings and case-studies on business models, design thinking and materi

• Department: Sustainability Management
• M 4:10 p.m.-6 p.m.
• Instructor: Diana A Trushell
  Info
• 3 points

Blockchain, Crypto, and Web 3.0

Blockchain, Crypto, & Web

In this course, students will comprehend the fundamental principles of these new technologies and how to strategically apply them to drive innovation, create efficiencies, and generate new opportunities in a rapidly evolving digital landscape. It offers students the opportunity to understand the factors fueling the adoption of these technologies including the exponential growth of data, the decline in trust post-financial crisis, the desire for data ownership, growing regulatory transparency requirements, the need for greater efficiencies, and the required protection of sensitive data. The evolution goes beyond the implementation of new processes, decentralized business models and technologies. The convergence of new technologies and interdisciplinary innovation drive the requirement for changes in regulatory processes, governance, and ethics. 

This course is designed for graduate students who aspire to lead in the era of digital transformation. It is ideal for those who seek to understand the strategic applications of blockchain, AI, and Web 3.0 technologies to drive innovation within their organizations. Whether planning to advance in a career in technology management or a professional in data and knowledge-driven industries, this course will enable the acquisition of knowledge and skills necessary to navigate and leverage the opportunities presented by the Fourth Industrial Revolution.

• Department: Technology Management
• R 6:10 p.m.-8 p.m.
• Instructor: Cristina Dolan
  Info
• 3 points

MARKET RESEARCH

Market research is the way that companies identify, understand and develop the target market for their products.  It is an important component of business strategy, and it draws on the research and analytics skills you have learned thus far in the program. Often market research consists of generating your own data, through quantitative and qualitative methodologies, in pursuit of the market research question.

This course is an elective that will expand on quantitative and qualitative methodologies that have been introduced previously, provide an introduction to other methodologies that are more specific to market research, and provide hands-on practice in defining a market research plan from start to finish. Students will also learn about particular types of market research studies and when and how they should be deployed. Students will generate and test their own research instruments. Through the use of case studies and simulations, students will learn how market research fits into an overarching marketing plan for a company.

This course is designed for students who have completed the Research Design and Strategy and Analytics core courses, and who are exploring how research fits into product marketing. You will leave this class understanding the essential aspects of market research, when and how they should be deployed, and the role you could play in small and large companies directing and executing on market research opportunities.

• Department: Applied Analytics
• M 8:10 p.m.-10 p.m.
• Instructor: Diahanna L Post
  Info
• 3 points

INTRODUCTION TO QUANTITATIVE BALANCE SHE

QUANT BALANCE SHEET STRAT

This course introduces students to a quantitative approach to defining and executing on commercial bank balance sheet strategy. Students will receive working knowledge of analyzing, managing and optimizing interest rate risk, liquidity risk and capital risk exposures of commercial bank balance sheets. The course also provides an overview of quantitative approaches to evaluation of business trends within the US commercial banking industry which informs balance sheet strategy of a typical commercial bank.

• Department: Mathematics
• S noon-2 p.m.
• Instructor: Greg A Borovykh
  Info
• 3 points

ORGAN TRANSPLANT ETHICS

• Department: Bioethics
• T 8 p.m.-10 p.m.
• Instructor: David N Hoffman
  h-index: 2 Info
• 3 points

AI USER INTERFACES FOR ANALYTICS

AI UI FOR ANALYTICS

In recent years, data analytics and artificial intelligence (AI) have become essential to business intelligence and informed decision making. But to realize the impact of analytics and AI, effective visual communication of data insights via user interfaces (UI), such as web pages and app dashboards, is equally critical. Building effective UIs requires mastering the user experience (UX) design principles and certain front-end development technologies. Furthermore, the recent rise of multimodal Generative AI offers unprecedented opportunities for simplifying, automating, and scaling UX/UI development.

This course provides a comprehensive understanding of UX design principles and best practices for developing UIs while emphasizing ethical considerations and inclusivity. Students will learn to create intuitive and visually engaging websites and dashboards that leverage AI-generated insights, also considering data privacy, diversity, and accessibility. Key topics include the design, implementation, and evaluation of UIs, with hands-on experience in web development technologies like HTML, CSS, and JavaScript, as well as related cloud services. Students will apply state-of-the-art AI technologies to create intelligent and interactive UIs, all while critically assessing data sources and AI models for potential biases.

The course content comprises a blend of conceptual learning and practice assignments. Weekly lectures and reading materials will cover the fundamentals of data visualization and user experience designs. Students will put the gained knowledge into practice through individual design and coding assignments and a group term project.

• Department: Applied Analytics
• M 8:10 p.m.-10 p.m.
• Instructor: Javid B Huseynov
  Info
• 3 points

AI AND ETHICS

tba

• Department: Bioethics
• T 4 p.m.-5:45 p.m.
• Instructor: Anne Zimmerman
  Info
• 3 points

PEDIATRICS & ETHICS

• Department: Bioethics
• W 4:30 p.m.-6 p.m.
• Instructor: George Hardart
  Info
• 3 points

Supervised Research

Students conduct research related to biotechnology under the sponsorship of a mentor within the University. The student and the mentor determine the nature and extent of this independent study. In some laboratories, the student may be assigned to work with a postdoctoral fellow, graduate student or a senior member of the laboratory, who is in turn supervised by the mentor. The mentor is responsible for mentoring and evaluating the students progress and performance. Credits received from this course may be used to fulfill the laboratory requirement for the degree. Instructor permission required. Web site: http://www.columbia.edu/cu/biology/courses/g4500-g4503/index.html

• Department: Biological Sciences
• Instructor: Lili Yamasaki
  CULPA: 5 Info
• 3-6 points

Supervised Research

Students conduct research related to biotechnology under the sponsorship of a mentor within the University. The student and the mentor determine the nature and extent of this independent study. In some laboratories, the student may be assigned to work with a postdoctoral fellow, graduate student or a senior member of the laboratory, who is in turn supervised by the mentor. The mentor is responsible for mentoring and evaluating the students progress and performance. Credits received from this course may be used to fulfill the laboratory requirement for the degree. Instructor permission required. Web site: http://www.columbia.edu/cu/biology/courses/g4500-g4503/index.html

• Department: Biological Sciences
• Instructor: Lili Yamasaki
  CULPA: 5 Info
• 3-6 points

CAPSTONE PROJECT

• Department: Construction Administration
• M 4:10 p.m.-6 p.m.
• 3 points

Ethics: Inclusive Storytelling

This course focuses on the necessary and often undiscussed role of ethics and inclusivity in storytelling and story creation. This course will provide space, as requested by the students, faculty and staff, for facilitated discussion around narrative ownership, comedy, history of on-screen portrayals, intersectionality, the business of inclusion and other related topics so that students walk away with a personal inclusive storytelling plan and a greater level of cultural competency as they continue their creative journeys.  The instructors are professionals in the entertainment space with deep knowledge and practical Equity, Diversity and Inclusion (EDI) experience.

• Department: Film
• W 9:30 a.m.-12:30 p.m.
• Instructor: Leon III Hendrix
  Info
• 1.5 points

GLOBAL LEGAL & REGULATORY ECOSYSTEM

• Department: Insurance Management
• Instructor: Sandra Bograd
  Info
• 3 points

Intro to Moving Image: Video, Film & Art

Intro Moving Image:Video,

Intro to Moving Image: Video, Film & Art is an introductory class on the production and editing of digital video. Designed as an intensive hands-on production/post-production workshop, the apprehension of technical and aesthetic skills in shooting, sound and editing will be emphasized. Assignments are developed to allow students to deepen their familiarity with the language of the moving image medium. Over the course of the term, the class will explore the language and syntax of the moving image, including fiction, documentary and experimental approaches. Importance will be placed on the decision making behind the production of a work; why it was conceived of, shot, and edited in a certain way. Class time will be divided between technical workshops, viewing and discussing films and videos by independent producers/artists and discussing and critiquing students projects. Readings will be assigned on technical, aesthetic and theoretical issues. Only one section offered per semester. If the class is full, please visit http://arts.columbia.edu/undergraduate-visual-arts-program.

• Department: Visual Arts
• M 10 a.m.-4 p.m.
• Instructor: Hinda R Weiss
  Info
• 3 points

SPECIAL PROJECTS WORKSHOP

• Department: Writing
• W 4:15 p.m.-7:15 p.m.
• Instructor: Edwin Torres
  Info
• 6 points

Supervised Independent Research

Students conduct research related to biotechnology under the sponsorship of a mentor outside the University within the New York City Metropolitan Area unless otherwise approved by the Program. The student and the mentor determine the nature and extent of this independent study. In some laboratories, the student may be assigned to work with a postdoctoral fellow, graduate student or a senior member of the laboratory, who is in turn supervised by the mentor. The mentor is responsible for mentoring and evaluating the students progress and performance. Credits received from this course may be used to fulfill the laboratory requirement for the degree. Instructor permission required. Web site: http://www.columbia.edu/cu/biology/courses/g4500-g4503/index.html

• Department: Biological Sciences
• Instructor: Lili Yamasaki
  CULPA: 5 Info
• 3-6 points

Supervised Independent Research

Students conduct research related to biotechnology under the sponsorship of a mentor outside the University within the New York City Metropolitan Area unless otherwise approved by the Program. The student and the mentor determine the nature and extent of this independent study. In some laboratories, the student may be assigned to work with a postdoctoral fellow, graduate student or a senior member of the laboratory, who is in turn supervised by the mentor. The mentor is responsible for mentoring and evaluating the students progress and performance. Credits received from this course may be used to fulfill the laboratory requirement for the degree. Instructor permission required. Web site: http://www.columbia.edu/cu/biology/courses/g4500-g4503/index.html

• Department: Biological Sciences
• Instructor: Lili Yamasaki
  CULPA: 5 Info
• 3-6 points

M.A. ESSAY II

• Department: French
• Instructor: Keithley Woolward
  Info
• 3 points

COMPANY FAILURES

Examination of areas critical to an organization’s success from strategic, operational, financial, and insurance perspectives, and examines why many companies fail in spite of the vast knowledge of factors driving success. Several case studies examined in depth.

• Department: Enterprise Risk Management
• T 6:10 p.m.-8 p.m.
• Instructor: Adam H Litke
  Info
• 3 points

COMPANY FAILURES

Examination of areas critical to an organization’s success from strategic, operational, financial, and insurance perspectives, and examines why many companies fail in spite of the vast knowledge of factors driving success. Several case studies examined in depth.

• Department: Auditing
• T 6:10 p.m.-8 p.m.
• W 8:10 p.m.-10 p.m.
• Instructor: Adam H Litke
  Info
• Instructor: Steve Lindo
  Info
• 0 points

COMPANY FAILURES

Examination of areas critical to an organization’s success from strategic, operational, financial, and insurance perspectives, and examines why many companies fail in spite of the vast knowledge of factors driving success. Several case studies examined in depth.

• Department: Enterprise Risk Management
• W 8:10 p.m.-10 p.m.
• Instructor: Steve Lindo
  Info
• 3 points

MAFN FIELDWORK

Prerequisites: all 6 MAFN core courses, at least 6 credits of approved electives, and the instructors permission. See the MAFN website for details. This course provides an opportunity for MAFN students to engage in off-campus internships for academic credit that counts towards the degree. Graded by letter grade. Students need to secure an internship and get it approved by the instructor.

• Department: Mathematics
• Instructor: Jaehyuk Choi
  Info
• 1-3 points

Archive Photography

When millions of images are made every day, how can a photographer create an original body of work? This class proposes that parsing humanity’s existing shared archive of images is more relevant than generating new images. Following models such as Nepal Picture Library, Magnum Foundation, Drik/Majority World, and Arab Image Foundation, contemporary photography has remapped its practice around the reimagining and explanation, of the archival object. This class explores many archives–family albums, historical photographs, government records, fragile maps, musical albums, and flea market collectibles. We will use a series of lens-based technologies, starting from the flatbed scanner and Photoshop retouching and radiating outward. We will explore archive concerns, including consent, ownership, privacy, circulation, respect, and political impact. Students will explore display forms, including slide shows, zines, books, and exhibitions. There will be a strong complement of reading and writing in this class around the theory and practice of archives from the Western North and Global South.

• Department: Visual Arts
• MW 1 p.m.-3:30 p.m.
• Instructor: Naeem Mohaiemen
  Wikipedia h-index: 8 Info
• 3 points

GLOBAL FINANCIAL SERVICES IN THE 21ST CE

GLOBAL FIN SERV IN THE 21

With an orientation more towards practical application, the intent of this course is to provide a strategic framework with which students can evaluate and understand the global financial services industry of both today and tomorrow. In this course we are defining global financial services as encompassing central banks, commercial and investment banks, asset/wealth management institutions and financial regulators. Via case studies, proprietary materials, class based problem solving exercises, and guest lectures, we will examine and discuss the i) current and future role of the major financial service participants, (ii) key drivers influencing an industry that has always been characterized by significant change (e.g., regulatory, technology, risk, globalization, and client needs), and (iii) challenges and opportunities facing today's financial services' CEOs post the 2008/09 financial crisis. Furthermore, this course is designed for students who want to be financial “architects and leaders”, not financial “technicians”.

• Department: Enterprise Risk Management
• R 4:10 p.m.-6 p.m.
• Instructor: Richard Goldberg
  Info
• 3 points

RISK REGULATIONS IN FINANCE

This course examines post-financial crisis regulations including Basel III, Fundamental Review of the Trading Book (FRTB), Dodd-Frank Act, Supervision and Regulation Letter 11-7 (SR 11-7), and others.  Case studies will explore the technical details of these new rules; and guest lectures from industry experts will bring the material to life.  Areas of focus include: model risk management, stress testing, derivatives, and insurance.  By the end of this course students will be able to:


Evaluate the purpose and limitations of risk regulations in finance.

Identify and communicate weaknesses in a financial firm.

Communicate with regulators.

Understand Recovery and Resolution Plans or “Living Wills” for a financial firm.

• Department: Enterprise Risk Management
• R 6:10 p.m.-8 p.m.
• Instructor: Lisa Broomer
  Info
• 3 points

RISK REGULATIONS IN FINANCE

This course examines post-financial crisis regulations including Basel III, Fundamental Review of the Trading Book (FRTB), Dodd-Frank Act, Supervision and Regulation Letter 11-7 (SR 11-7), and others.  Case studies will explore the technical details of these new rules; and guest lectures from industry experts will bring the material to life.  Areas of focus include: model risk management, stress testing, derivatives, and insurance.  By the end of this course students will be able to:


Evaluate the purpose and limitations of risk regulations in finance.

Identify and communicate weaknesses in a financial firm.

Communicate with regulators.

Understand Recovery and Resolution Plans or “Living Wills” for a financial firm.

• Department: Auditing
• R 6:10 p.m.-8 p.m.
• T 6:10 p.m.-8 p.m.
• Instructor: Lisa Broomer
  Info
• Instructor: Juan Echeverri
  Info
• 0 points

RISK REGULATIONS IN FINANCE

This course examines post-financial crisis regulations including Basel III, Fundamental Review of the Trading Book (FRTB), Dodd-Frank Act, Supervision and Regulation Letter 11-7 (SR 11-7), and others.  Case studies will explore the technical details of these new rules; and guest lectures from industry experts will bring the material to life.  Areas of focus include: model risk management, stress testing, derivatives, and insurance.  By the end of this course students will be able to:


Evaluate the purpose and limitations of risk regulations in finance.

Identify and communicate weaknesses in a financial firm.

Communicate with regulators.

Understand Recovery and Resolution Plans or “Living Wills” for a financial firm.

• Department: Enterprise Risk Management
• T 6:10 p.m.-8 p.m.
• Instructor: Juan Echeverri
  Info
• 3 points

Career Development for Quantitative Fina

Career Develop for Quant

This course helps the students understand the job search process and develop the professional skills necessary for career advancement. The students will not only learn the best practices in all aspects of job-seeking but will also have a chance to practice their skills. Each class will be divided into two parts: a lecture and a workshop.

In addition, the students will get support from Teaching Assistants who will be available to guide and prepare the students for technical interviews.

• Department: Mathematics
• MW 11:40 a.m.-12:55 p.m.
• Instructor: Jaehyuk Choi
  Info
• 0 points

ESG AND ERM

ESG will be a driving force in risk management in upcoming years. ERM / Risk professionals need a solid understanding of emerging ESG trends and regulations and how they apply to day-to-day job responsibilities. The ESG and ERM course begins with an overview of the ESG landscape and framework. After a foundational understanding is established, the course focuses on incorporating ESG into enterprise risk management, including identification, quantification, decision making, and reporting of ESG-related risks.

• Department: Enterprise Risk Management
• M 6:10 p.m.-8 p.m.
• W 6:10 p.m.-8 p.m.
• Instructor: Helda Rock
  Info
• Instructor: Tahmina Day
  Info
• 3 points

ESG AND ERM

ESG will be a driving force in risk management in upcoming years. ERM / Risk professionals need a solid understanding of emerging ESG trends and regulations and how they apply to day-to-day job responsibilities. The ESG and ERM course begins with an overview of the ESG landscape and framework. After a foundational understanding is established, the course focuses on incorporating ESG into enterprise risk management, including identification, quantification, decision making, and reporting of ESG-related risks.

• Department: Enterprise Risk Management
• W 6:10 p.m.-8 p.m.
• Instructor: Tahmina Day
  Info
• 3 points

CONSUMERISM AND SUSTAINABILITY

TBA

• Department: Sustainability Management
• R 6:10 p.m.-8 p.m.
• Instructor: Michelle Gabriel
  Info
• 3 points

DERIVATIVES RISK MANAGEMENT

This course explores financial derivatives across different asset classes with in-depth analysis of several popular trades including block trades, program trades, vanilla options, digital options, and variance swaps. Their dynamics and risks are explored through Monte Carlo simulation using Excel and Python. The daily decisions and tasks of a frontline risk manager are recreated and students have the opportunity to see which trades they would approve or reject. Students will gain a working knowledge of financial derivatives and acquire technical skills to answer complex questions on the trading floor.

• Department: Enterprise Risk Management
• M 6:10 p.m.-8 p.m.
• Instructor: Alberto Scalari
  Info
• 3 points

TOOLS FOR RISK MANAGEMENT

Tools for Risk Management examines how risk technology platforms assess risks. These platforms gather, store, and analyze data; and transform that data to actionable information. This course explores how the platforms are implemented, customized, and evaluated. Topics include business requirements specification, data modeling, risk analytics and reporting, systems integration, regulatory issues, visualization, and change processes. Hands-on exercises using selected vendor tools will give students the opportunity to see what these tools can offer.

• Department: Enterprise Risk Management
• R 6:10 p.m.-8 p.m.
• M 8:10 p.m.-10 p.m.
• Instructor: Barney Baldwin
  Info
• Instructor: Viktor Ziskin
  Info
• 3 points

TOOLS FOR RISK MANAGEMENT

Tools for Risk Management examines how risk technology platforms assess risks. These platforms gather, store, and analyze data; and transform that data to actionable information. This course explores how the platforms are implemented, customized, and evaluated. Topics include business requirements specification, data modeling, risk analytics and reporting, systems integration, regulatory issues, visualization, and change processes. Hands-on exercises using selected vendor tools will give students the opportunity to see what these tools can offer.

• Department: Enterprise Risk Management
• M 8:10 p.m.-10 p.m.
• Instructor: Viktor Ziskin
  Info
• 3 points

ERM MODELING

Equips students with the basics of risk measurement and simulation using a hands-on approach to ERM modeling. Using industry-standard simulation software, students build systems of risk drivers for finance and insurance companies. Topics include risk correlations, VaR and TVaR, capital modeling, capital allocation, and parameter, process, and model Risk. Students acquire both quantitative experience building models and qualitative appreciation for model weaknesses.

• Department: Enterprise Risk Management
• R 8:10 p.m.-10 p.m.
• Instructor: Julian Horky
  Info
• 3 points

SPORTS SPONSORSHIP & SALES

• Department: Sports Management
• M 6:10 p.m.-8 p.m.
• Instructor: Michael Neuman
  Info
• 3 points

Fieldwork Course in Modern Asia-Pacific

Fieldwork Mod Asia-Pacifi

This course provides an opportunity for students in the MA in Regional Studies: East Asia (MARSEA) Program to engage in off-campus internships for academic credit that will count towards their requirements for the degree. Open only to MARSEA students and only with prior written approval of the program director or academic director. Prerequisites: Both semesters of the required MARSEA Core Seminar. This course is not open to students in their first two semesters.

To apply for EARS GR5555, tsubmit a complete application and an official offer letter from the internship sponsor to the MARSEA program office as early as possible (must be submitted at least 21 days before the start of the internship). The application should include:
• Student’s full name and UNI
• Name of organization sponsoring or employing the student; department within the organization (if applicable); and address
• Expected start and end dates of internship
• Number of credits requested. Students should be aware that the application may be approved for a lower number of credits than requested.
• Number of hours of work per week
•Name, title, phone number, and email address for the student’s supervisor in the organization or the organization’s Human Resources office (HR)
• An official letter from the employer/internship sponsor offering employment. It must include the following information: Beginning and ending dates of employment, number of hours of work per week, a description of appropriate duties, location of employment
• All international students in F-1 status applying for EARS GR5555 are required to submit an application for CPT.

• Department: East Asian Regional Studies
• Instructor: Lisbeth K Brandt
  CULPA: 4 Info
• 1 points

MACHINE LEARNING FOR RISK MANAGEMENT

The exponentially increasing availability of data and the rapid development of information technology and computing power have inevitably made Machine Learning part of the risk manager’s toolkit. But, what are these tools? This class provides the driving intuitions for machine learning. Students will see how many of the algorithms are extensions of what we already do with our human minds. These algorithms include regularized regression, cluster analysis, naive bayes, apriori algorithm, decision trees, random forests, and boosted ensembles.

Through practical and real-life applications of ML to Risk Management, students will learn to identify the best technique to apply to a particular risk management problem, from credit risk measurement, fraud detection, portfolio selection to climate change, and ESG applications.

• Department: Enterprise Risk Management
• W 6:10 p.m.-8 p.m.
• 3 points

History & Literature Seminar

Post-esclavage, 1791-XXle

• Department: French
• Instructor: Keithley Woolward
  Info
• 1-6 points

History & Literature Seminar

Sensus Communis

• Department: French
• Instructor: Keithley Woolward
  Info
• 1-6 points

History & Literature Seminar

Poesie de la Negritude

• Department: French
• Instructor: Keithley Woolward
  Info
• 1-6 points

History & Literature Seminar

American Poetry 19th cent

• Department: French
• Instructor: Keithley Woolward
  Info
• 1-6 points

History & Literature Seminar

Histoire transnationale

• Department: French
• Instructor: Keithley Woolward
  Info
• 1-6 points

History & Literature Seminar

Histoire maintien ordre

• Department: French
• Instructor: Keithley Woolward
  Info
• 1-6 points

History & Literature Seminar

Heros/Heroines

• Department: French
• Instructor: Keithley Woolward
  Info
• 1-6 points

History & Literature Seminar

Fictions of aggression

• Department: French
• Instructor: Keithley Woolward
  Info
• 1-6 points

History & Literature Seminar

Hist. sociale Moyen Age

• Department: French
• Instructor: Keithley Woolward
  Info
• 1-6 points

History & Literature Seminar

Peaux de betes

• Department: French
• Instructor: Keithley Woolward
  Info
• 1-6 points

History & Literature Seminar

Critique, utopie, praxis

• Department: French
• Instructor: Keithley Woolward
  Info
• 1-6 points