FUNDAMENTALS OF DATA ENGINEERING
FUNDAMENTALS OF DATA ENGINEERING
- Department: Applied Analytics
- S 10:10 a.m.-noon
- M 6:10 p.m.-8 p.m.
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Instructor:
Samar Deen
Info -
Instructor:
Nitinchandra Nayak
Info - 3 points
FUNDAMENTALS OF DATA ENGINEERING
FUND OF DATA ENG ONLINE
FUNDAMENTALS OF DATA ENGINEERING
- Department: Applied Analytics
- M 6:10 p.m.-8 p.m.
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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
- T 3:45 p.m.-5:45 p.m.
- M 8 p.m.-10 p.m.
- W 8 p.m.-10 p.m.
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Instructor:
Barbra Rothschild
Info -
Instructor:
Cindy Geppert
Info - 3 points
PRACTICAL PRODUCTION I
Practical Production 1 teaches students best practices regarding film production and technology in the integrated first year of the MFA Film Program through lectures, discussions, pre-production meetings, multi-hour shoots on set and an end-of-the-semester screening. This class is required for all first-year students. Throughout the Fall, students will work in small production groups to prep and shoot a short script in the Prentis studio. Each week one group will organize a pre-production meeting and then produce a four-hour shoot. The professor will be in attendance and two de-briefing sessions will occur throughout the production to reiterate best film production practices. Additional assignments will include the creation of various pre-production, production and wrap paperwork and tech deliverables. Additional mandatory production and risk management workshops will be given. The last class will be a screening of all group films and prep/discussion for the 3-5 exercise shot over Winter Break. Required for all first-year students.
- Department: Film
- F 10 a.m.-1 p.m.
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Instructor:
Joshua R Troxler
Info - 1.5 points
NON-LINEAR OPTION PRICING
Prerequisites: familiarity with Brownian motion, Itô's formula, stochastic differential equations, and Black-Scholes option pricing. Prerequisites: Familiarity with Brownian motion, Itô's formula, stochastic differential equations, and Black-Scholes option pricing. Nonlinear Option Pricing is a major and popular theme of research today in quantitative finance, covering a wide variety of topics such as American option pricing, uncertain volatility, uncertain mortality, different rates for borrowing and lending, calibration of models to market smiles, credit valuation adjustment (CVA), transaction costs, illiquid markets, super-replication under delta and gamma constraints, etc. The objective of this course is twofold: (1) introduce some nonlinear aspects of quantitative finance, and (2) present and compare various numerical methods for solving high-dimensional nonlinear problems arising in option pricing.
- Department: Mathematics
- F 6 p.m.-8:10 p.m.
- 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.
- T 6:10 p.m.-8 p.m.
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Instructor:
Michael Zwecher
Info -
Instructor:
Deniz Ozenbas
Info - 3 points
ECONOMETRICS I
- Department: Economics
- TR 11:40 a.m.-12:55 p.m.
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Instructor:
Seyhan Erden
CULPA: 7
Info
- 3 points
PRINTMAKING:DRAWING INTO PRINT
- Department: Visual Arts
- T 10 a.m.-4 p.m.
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Instructor:
Tomas Vu Daniel
CULPA: 4
Info
- 3 points
ADVANCED ECONOMETRICS
- Department: Economics
- M 12:10 p.m.-2 p.m.
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Instructor:
Serguei Maliar
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.
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Instructor:
Tamar A Lando
CULPA: 8 Info - 4 points
ANOMALY DETECTION
- Department: Applied Analytics
- M 6:10 p.m.-8 p.m.
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Instructor:
Christopher Kuo
Info - 3 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
- W 8:10 p.m.-10 p.m.
- T 6:10 p.m.-8 p.m.
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Instructor:
Christopher Mann
Info -
Instructor:
Douglas W Dwyer
Info - 3 points
MODEL & TRADE DERIVATIVES
Required Prerequisite: Math GR5010 Intro to the Math of Finance (or equivalent). Recommended Prerequisite: Stat GR5264 Stochastic Processes – Applications I (or equivalent).
The objective of this course is to introduce students, from a practitioner’s perspective with formal derivations, to the advanced modeling, pricing and risk management techniques of vanilla and exotic options that are traded on derivatives desks, which goes beyond the classical option pricing courses focusing solely on the theory. It also presents the opportunity to design, implement and backtest vol trading strategies. The course is divided in four parts: Advanced Volatility Modeling; Vanilla and Exotic Options: Structuring, Pricing and Hedging; FX/Rates Components: Discounting, Forward Projection, Quanto and Compo Options; Designing and Backtesting Vol Trading Strategies in Python.
- Department: Mathematics
- S 10:10 a.m.-noon
- 3 points
QUALITATIVE EVALUATION METHODS FOR NARRA
QUALTV EVALUATION METHODS
TBA
- Department: Narrative Medicine
- 3 points
QUALITATIVE EVALUATION METHODS FOR NARRA
QUALTV EVALUATION METHODS
TBA
- Department: Narrative Medicine
- 3 points
PRINTMAKING I: INTAGLIO
- Department: Visual Arts
- MW 2:30 p.m.-5 p.m.
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Instructor:
Jennifer Nuss
Info - 3 points
PRINTMAKING II: INTAGLIO
- Department: Visual Arts
- MW 2:30 p.m.-5 p.m.
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Instructor:
Jennifer Nuss
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
- T 6:10 p.m.-8 p.m.
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Instructor:
Joseph Dziwura
Info - 3 points
PRINTMAKING I: RELIEF
- Department: Visual Arts
- MW 9:30 a.m.-noon
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Instructor:
Nathan N Catlin
Info - 3 points
ADVANCED MACHINE LEARNING FOR FINANCE
ADV MACHINE LEARNING FOR
The application of Machine Learning (ML) algorithms in the Financial industry is now commonplace, but still nascent in its potential. This course prepares the next generation of researchers and practitioners for the coming revolution, providing an advanced "deep dive" into machine learning methods (both theory and application) that are deemed to be useful for financial applications, including trading and investment management.
- Department: Mathematics
- T 12:10 p.m.-2 p.m.
- 3 points
FINANCIAL DATA SCIENCE AND MACHINE LEARN
FIN DATA SCI & MACHINE LE
This course teaches cutting-edge tools and methods that drive investment decisions at quantitative trading firms, and, more generally, firms applying machine learning to big data. The course will combine presentations of theory, immediately followed by in-class Python programming examples using real financial data. The course will develop a general approach to building models of economic and financial processes, with a focus on statistical learning techniques that scale to large data sets. Among the topics covered are lasso, elastic net, cross validation, Bayesian models, the EM algorithm, Support Vector Machines, kernel methods, Gaussian processes, Hidden Markov Models, and neural networks. The final project will lead the students to build a trading strategy based on the techniques learned throughout the course.
- Department: Applied Analytics
- T 6:10 p.m.-8 p.m.
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Instructor:
William G Ritter
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
- T 8:10 p.m.-10 p.m.
- R 6:10 p.m.-8 p.m.
- W 8:10 p.m.-10 p.m.
- 3 points
PRINTMAKING I: SILKSCREEN
- Department: Visual Arts
- R 10 a.m.-4 p.m.
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Instructor:
Alejo Contreras
Info - 3 points
PRINTMAKING II: SILKSCREEN
- Department: Visual Arts
- R 10 a.m.-4 p.m.
-
Instructor:
Alejo Contreras
Info - 3 points
ORGANIZATIONAL ETHICS AND COMPLIANCE
ORGANIZATIONAL ETHICS & C
This course will explore the influence of institutional policies on the ethical practices of clinicians, researchers, and healthcare administrators. We will examine the ways in which rules and practices related to operational and financial performance shape the ability of practitioners, advocates for patients/research participants, and the public to advance organizational goals. We will evaluate internal and external sources of institutional direction and values. The exercise of authority by different stakeholders produces a cumulative impact on organizational ethics and compliance. At the end of the course students will have a working knowledge of the various institutional influences that impact the sometimes-conflicting obligations of compliance with financial regulations and clinical performance improvement.
- Department: Bioethics
- W 3 p.m.-5 p.m.
-
Instructor:
David N Hoffman
h-index: 2 Info - 3 points
IMPACT FINANCE FOR SUSTAINABILITY PRACTI
IMPACT FINANCE FOR SUST PRACT
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
- M 8:10 p.m.-10 p.m.
-
Instructor:
Mohamed Mneimneh
Info - 3 points
RESEARCH ETHICS
In recent years, many crucial issues have arisen concerning research ethics. Scientists in biomedicine, social science and other areas, as well as policy makers face rapidly evolving challenges. In recent years, violations of research ethics have attracted attention from the public, the media, the government, and the scientific community, which have all responded in varying ways. Issues arise in deciding how best to protect human subjects, obtain informed consent, protect privacy and confidentiality, finance research without biasing results, and avoid “misbehavior” among scientists. Questions arise concerning the professional responsibilities and rights of scientists, the rights of study participants, and the appropriate role of the state in these matters.
The course meets online once a week for an hour and a half, with extensive interaction between students and the professor both during class and on post-class discussion forums. It can fulfill the requirements for Responsible Conduct of Research that the NIH and other funders currently mandate for training programs that they support.
- 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
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:
Erin Bansal
Info - 3 points
SPORTS LAW AND ETHICS
- Department: Sports Management
- W 6:10 p.m.-8 p.m.
- M 6:10 p.m.-8 p.m.
-
Instructor:
Carla Varriale
Info -
Instructor:
Jennifer Duberstein
Info - 3 points
WRITING OP-EDS, SMALL PERSONAL ESSAYS AN
WRITING OP-EDS, ESSAYS &
This class is designed to give students exercises and guided experiences in producing and marketing publishable opinion essays. In the last two decades, newspapers, magazines and websites have opened up their pages to reader contributions. This development provides an unprecedented opportunity for students and faculty to connect with the general public about policy issues—and also to their personal passions. Op-eds provide a relatively new pathway to communication and advocacy. This course aims to teach journalistic writing so that our students can gain a larger forum on matters like climate mitigation, conservation biology, green roofs, urban farming, ecologic waste disposal, environmental justice, and pandemic prevention.
- Department: Sustainability Management
- T 6:10 p.m.-8 p.m.
- 3 points
AI and the Future of Strategic Communica
AI & the Future of Strat
The field of Artificial Intelligence (AI) has rapidly evolved to become a transformative global force across various industries, with particular significance for strategic communication. This elective course provides a comprehensive exploration of AI’s foundations, its current landscape, and its profound impact on media, journalism, public relations, and marketing communications. The course also addresses critical issues surrounding AI such as ethics, policy, and risk management associated with adoption, while offering practical insights into implementing common AI tools and developing essential AI skills for communication professionals.
- Department: Strategic Communication
- M 2:10 p.m.-4 p.m.
-
Instructor:
Cecilia Dones
Info - 3 points
CIRCULAR ECONOMY FOR SUSTAINABILITY PROF
CIRC ECON FOR SUST PROFS
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
- R 6:10 p.m.-8 p.m.
-
Instructor:
Danielle Azoulay
Info - 3 points
JOURNALISM & BIOETHICS
- Department: Bioethics
- M 3 p.m.-5 p.m.
-
Instructor:
Harriet A Washington
Wikipedia Info - 3 points
AI INFUSION
Artificial intelligence (AI) is swiftly infusing the communication discipline with immediate implications for students and practitioners alike. To stay current with rapidly unfolding developments and create new ties with industry, this 0-credit course presents a biweekly series of speakers and panels comprised of alumni, Advisory Board members, and professionals. Speakers discuss their own AI use in the workplace. Students have the opportunity to interact with communication leaders on the forefront of AI implementation.
Each session aligns with a different Strategic Communication course topic. Among the areas to be explored are synthetic data and synthetic audience testing, event simulation, retrieval augmented generation (RAG), agentic AI, content production, and personalization at scale. Along with current use cases, a core focus of discussion will be AI governance, leadership strategy and decision-making, workforce training, and the development of principles and policies to guide human-centric and ethical AI implementation.
- Department: Strategic Communication
- T 7 p.m.-8:20 p.m.
-
Instructor:
Brandy N Dawson
Info - 0 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 6:10 p.m.-8 p.m.
-
Instructor:
Roya Heydari
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
- T 6:10 p.m.-8 p.m.
- M 6:10 p.m.-8 p.m.
-
Instructor:
Olusegun Oshin
Info -
Instructor:
Michelle Morales
Info - 3 points
RELIGION & BIOETHICS
- Department: Bioethics
- M 12:10 p.m.-2 p.m.
-
Instructor:
Linda S Golding
Info - 3 points
Algorithmic Trading with Market Simulato
Algo Trading with Market
The course will cover the fundamentals of Algorithmic Trading, the discipline that brings together computer software, and financial markets to open and close trades based on programmed code. The goal of the course is to help the students to get familiar with the different techniques and strategies used in algorithmic trading and to let them experiment with classical and new algorithms they will create.
During the course, the students will use a Trading Market Simulator: The Rotman Market Simulator – a platform which allows students to transact financial securities with each other on a real time basis. Using the simulator, the students will familiarize themselves with specific decision tasks associated with financial securities, market dynamics, and investment or risk management strategies and get ready for the Rotman Competition.
- Department: Mathematics
- T 10:10 a.m.-11:25 a.m.
- 1.5 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
- R 6:10 p.m.-8 p.m.
-
Instructor:
James Murphy
Info - 3 points
Introduction to Medieval Manuscript Stud
Intro to Medieval Manuscr
This team-taught course introduces methods for studying medieval manuscripts through weekly hands-on instruction and assignments. Students will become acquainted with the collections of medieval manuscripts at Columbia, and will learn from the scholars at Columbia who specialize in the material study of manuscripts as artifacts as well as in types of manuscripts as defined by their textual contents. The course provides a foundation for advanced work and satisfies the material text requirement of the MA in Medieval and Renaissance Studies.
- Department: Medieval and Renaissance Studies
- F 10 a.m.-1 p.m.
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Instructor:
Emily Runde
Info - 4 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
- W 10 a.m.-4 p.m.
-
Instructor:
Sable Smith
Wikipedia Info - 3 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
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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
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Instructor:
Lili Yamasaki
CULPA: 5 Info - 3-6 points
Animation
Unlike any other medium, animation provides unmatched suspicion of disbelief. Moreover, one can exercise one's imagination in digital space beyond material and physical limitations. Combining the two provides the permissive space to manifest our wildest reveries: utopias, dystopias, thought experiments, psi-fic scenarios, or dollhouses for amphibians.
In this course, students will receive a general survey on a range of methods in animation production. From the most traditional hand-drawn animation and cel animation to digital animation employing Photoshop, After Effects, and Blender (3D animation). Although this class can be technically involved; software mastery the end goal of the course is using these techniques to produce animations as a means of expression. These are only tools to help students form and realize their creative visions. Designed for both the digitally inclined and those who hate computers, students can try and then choose the method most agreeable to their temperament and ideas. They can also combine and mix different methods, maximizing creative freedom.
The course will introduce projects from animation history (early experimental animation, Disney, Soviet experimental animation, etc.) and contemporary art examples (Pierre Huyghe, Ian Chang, Wong Ping. etc.). However, the aim is to go beyond the Western art canon and expose students to other facets of culture. We will also study examples from popular culture (music videos) and Japanese anime (Hideaki Anno, Satoshi Kon, Masaaki Yuasa, etc.). One of the most essential responsibilities the students will take on is expanding our collective references by bringing in and presenting works that genuinely inspire and interest them.
Animation is an exceptionally permissive medium; it facilitates all of your prior skills and interests. Whether it is drawing, painting, music, poetry, fiction, or using a yoyo, there is a way for it to exist in animation. Students will be asked to keep a sketchbook for the duration of the semester. It will serve a landing pad for ideas and an anchor point to manage the project. The course will cover the entire production process, from idea development, concept design, character design, writing, storyboarding, foley, voice, music, editing, and final publication. Much of the class time will be dedicated to working, punctured by presentations, technical workshops, and critiques. At the end of the semester, students will have completed three shorts (30 seconds-2 minutes) and one fully developed pr
- Department: Visual Arts
- F 10 a.m.-4 p.m.
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Instructor:
Yi Fan Jiang
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.
- W 8:10 p.m.-10 p.m.
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Instructor:
Adam H Litke
Info -
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
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Instructor:
Jaehyuk Choi
Info - 1-3 points
MATHEMATICS FOR AI
This course equips students with essential mathematical foundations for understanding and working with artificial intelligence (AI) algorithms. After a brief introduction to the historical and social context that numbers arise in, students will learn about:
- Linear Algebra: Matrices, matrix-vector multiplication, linear models, change of basis, dimensionality, spectral decomposition, and principal component analysis (PCA).
- Calculus: Rates of change, derivatives, optimization techniques like gradient descent, with a brief touch upon linear approximation.
- Probability and Statistics: Mathematically deriving complex probability distributions out of simpler ones, mathematically deriving statistical testing methods
- Graph Theory: How graphs are used to find relationships between data as well as being a setting for AI-driven problem solving.
- Problem Solving and Algorithms: Applying mathematical concepts to find problem solutions.
Students will learn about search methods like uninformed search, informed search with the A* algorithm, and greedy algorithms.
- Computational Theory and Automata: Answering questions about what is computable, what is needed in order to compute something, and using this framework to state how much “information” is contained in a mathematical object.
By the end of this course, students will possess a strong mathematical toolkit to confidently tackle the complexities of modern AI algorithms.
- Department: Applied Analytics
- M 6:10 p.m.-8 p.m.
- T 6:10 p.m.-8 p.m.
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Instructor:
Thilan Arachchi Appuhamillage
Info -
Instructor:
Robert Simione
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.
- W 6:10 p.m.-8 p.m.
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Instructor:
Jean Michel Ngalikpima
Info -
Instructor:
Eric Goetz
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 10:10 a.m.-11:25 a.m.
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Instructor:
Jaehyuk Choi
Info - 0 points
Topics in Mathematical Finance
The purpose of this course is for MA in Mathematics of Finance students to gain knowledge and practical skills that are essential in the finance industry. The course will run as a series of lectures and discussions on various relevant topics, such as business communications and career talks that may feature guest speakers from the industry as well as the full-time faculty members. This will prepare the students for their job search, networking, and in their industry jobs in the future.
- Department: Mathematics
- TR 6:10 p.m.-7:25 p.m.
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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.
- R 8:10 p.m.-10 p.m.
- T 6:10 p.m.-8 p.m.
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Instructor:
Helda Rock
Info -
Instructor:
Jean Michel Ngalikpima
Info -
Instructor:
Tahmina Day
Info - 3 points
ANALYTICS FOR BUSINESS OPERATIONS MANAGE
Operations Management (OM) is responsible for the efficient production and delivery of goods and services, serving as a cornerstone of successful organizations. This course emphasizes how analytical techniques, such as forecasting, queuing theory, and linear programming, provide critical tools for optimizing operational decision-making, improving efficiency, and addressing real-world challenges in operations management. In this course, you will gain essential skills to optimize processes, manage resources, and enhance productivity across various industries. The course will be delivered through a combination of interactive lectures, case studies, and hands-on coding exercises to ensure a balance between conceptual learning and practical application.
Through lectures, you will gain a solid foundation in OM principles and analytical techniques. Case studies will help illustrate real-world applications of OM in industries such as manufacturing, healthcare, retail, and logistics, allowing you to see how the concepts are applied in diverse contexts. This course will integrate the principles of OM with hands-on analytical techniques using Python, allowing you to model and solve real-world OM problems. You will learn to run simulations, perform optimizations, and analyze data to make data-driven decisions that enhance efficiency and overall performance.
OM practices are tailored to meet the specific needs of various sectors. In manufacturing, OM helps streamline production lines and minimize waste; in healthcare, it enhances patient flow and optimizes resource allocation; in retail, it improves inventory management and supply chain operations; and in logistics, it ensures timely deliveries while reducing transportation costs. This course will equip you with the skills to apply OM practices effectively in different industries.
Analytics for Business Operations Management is an elective that is intended for students who are interested in pursuing a career using analytics and operational insights to drive organizational success in a competitive global marketplace across various industries.
- Department: Applied Analytics
- M 6:10 p.m.-8 p.m.
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Instructor:
Andy W Chen
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.
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Instructor:
Alberto Scalari
Info - 3 points
MANAGING STAKEHOLDER RISK IN THE ORGANIZ
In this course, students study major concepts of management and organization theory to understand human behavior in an organizational context, and then learn how to apply this to better manage interactions with key ERM stakeholders. Students will learn how to accomplish key ERM activities effectively while preserving and enhancing key internal relationships.
The course provides a deep dive into how enterprise risk functions operate within organizations, blending theoretical frameworks with practical, real-world applications. Topics include individual and organizational psychology, risk culture, organizational structure and governance, and the dynamics of managing risk in complex institutions. Through case studies and class discussions, students explore the behavioral and structural dimensions that shape ERM practices.
This elective is open only to students within the ERM program. This course (MSRO) is analogous to Managing Human Behavior in the Organization (MHBO), but customized for an ERM role. As a result, ERM students may not register for MHBO and those that have already taken MHBO may not register for MSRO.
- Department: Enterprise Risk Management
- R 6:10 p.m.-8 p.m.
- W 8:10 p.m.-10 p.m.
- T 8:10 p.m.-10 p.m.
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Instructor:
Kristen Walters
Info - 3 points
FINANCIAL SEC ANALYSIS AND PORTFOLIO MGT
FIN SEC ANALYSIS AND PORT
Financial securities analysis and portfolio management is the study of analyzing information to evaluate financial securities and design investment strategies. Studying the subject can provide a foundation for students entering the fields of investment analysis or portfolio management. This course provides an intensive introduction to major topics in investments. Part I of the course lays the theoretical foundation by introducing the Portfolio Theory and Equilibrium Asset Pricing models. Part II covers the valuation models and analysis of major asset classes: equity, fixed-income, and derivatives. Topics include bond valuation and interest rate models, equity valuation and financial statement analysis, options valuation, other derivatives, and risk management. Part III of the course focuses on the practice of active portfolio management.
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 8:10 p.m.-10 p.m.
- W 8:10 p.m.-10 p.m.
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Instructor:
Viktor Ziskin
Info -
Instructor:
Barney Baldwin
Info - 3 points
MODEL RISK MANAGEMENT
Given the ever growing reliance on models, Model risk affects financial institutions at almost every level of their organization including pricing, risk, finance, and marketing. Model risk management (MRM) is now one of the primary focuses of operational risk management at modern financial institutions. In this class, the ERM skill sets of risk identification, risk quantification, and risk decision making are applied to the kinds of models seen in large, complex financial institutions. Through readings, lecture, assignments, and in-class discussions, students learn the principles and concepts that a robust MRM function uses to manage model risk.
- Department: Enterprise Risk Management
- T 8:10 p.m.-10 p.m.
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Instructor:
Peter L Russo
Info - 3 points
SPORTS SPONSORSHIP & SALES
- Department: Sports Management
- M 6:10 p.m.-8 p.m.
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Instructor:
Ishwara Glassman Chrein
Info - 3 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
- M 6:10 p.m.-8 p.m.
- 3 points
Oral History & Justice: Memory, Power, a
HUM RGTS & ORAL HIST
This course will explore the ethics and politics of using oral history methods for documenting injustice, oppression, and human rights issues. The course is open to graduate students of oral history, human rights, journalism, and related fields; no prior experience with oral history interviewing is required. Oral history can be a powerful means of documenting oppression, human rights abuses, and crisis “from the bottom up” and facilitating the understanding and possible transformation of conditions of injustice. It can open the space for people and narratives that have been marginalized to challenge official narratives and complicate narrow accounts of injustice and crisis. The course will first explore what is distinct about oral history as a response to harm or injustice, comparing it to more familiar forms of testimony and narrative used within the realm of human rights, social justice organizations and courts of law. With its commitment to life narrative interviews and archival preservation, oral history situates injustice within the broader context of a life, a historical trajectory, and a political and cultural setting. Weaving together conceptual and practical approaches, we will examine different potential goals of oral history, such as documenting the experiences of people who have been marginalized; seeking justice; fostering dialogue and healing; and/or supporting activism and advocacy. The course covers interviewing skills and project planning specifically for oral history projects about injustice and human rights, and explores various dimensions of how power, politics, and ethics come into play — how politics and power shape the way a narrative is heard; the challenges of realizing ideals of collaboration and shared authority amid uneven power dynamics; contending with the effects of trauma on both narrators and interviewers; and critical considerations for projects produced with activist and advocacy aims. We will explore how oral history can work alongside other forms of memory and witnessing that go beyond words, such as activism, film, and memorials.
- Department: Oral History
- M 2:10 p.m.-4 p.m.
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Instructor:
Suchitra Vijayan
Info - 4 points
Internship in ACTU
This asynchronous, 1.5-credit elective combines a supervised professional internship with guided analysis of workplace culture, ethics, and feedback practices. Students evaluate organizational values, inclusivity, and ethical decision-making while developing the skills needed to navigate professional environments and identify the workplace cultures in which they will thrive.
- Department: Actuarial Science
- 1.5 points
Internship in APAN
This asynchronous, 1.5-credit elective combines a supervised professional internship with guided analysis of workplace culture, ethics, and feedback practices. Students evaluate organizational values, inclusivity, and ethical decision-making while developing the skills needed to navigate professional environments and identify the workplace cultures in which they will thrive.
- Department: Applied Analytics
- 1.5 points
Internship in CNAD
This asynchronous, 1.5-credit elective combines a supervised professional internship with guided analysis of workplace culture, ethics, and feedback practices. Students evaluate organizational values, inclusivity, and ethical decision-making while developing the skills needed to navigate professional environments and identify the workplace cultures in which they will thrive.
- Department: Construction Administration
- 1.5 points
Internship in COMM
This asynchronous, 1.5-credit elective combines a supervised professional internship with guided analysis of workplace culture, ethics, and feedback practices. Students evaluate organizational values, inclusivity, and ethical decision-making while developing the skills needed to navigate professional environments and identify the workplace cultures in which they will thrive.
- Department: Strategic Communication
- 1.5 points
Internship in ERM
This asynchronous, 1.5-credit elective combines a supervised professional internship with guided analysis of workplace culture, ethics, and feedback practices. Students evaluate organizational values, inclusivity, and ethical decision-making while developing the skills needed to navigate professional environments and identify the workplace cultures in which they will thrive.
- Department: Enterprise Risk Management
- 1.5 points
Internship in HCM
This asynchronous, 1.5-credit elective combines a supervised professional internship with guided analysis of workplace culture, ethics, and feedback practices. Students evaluate organizational values, inclusivity, and ethical decision-making while developing the skills needed to navigate professional environments and identify the workplace cultures in which they will thrive.
- Department: Human Capital Management
- 1.5 points
Internship in IKNS
This asynchronous, 1.5-credit elective combines a supervised professional internship with guided analysis of workplace culture, ethics, and feedback practices. Students evaluate organizational values, inclusivity, and ethical decision-making while developing the skills needed to navigate professional environments and identify the workplace cultures in which they will thrive.
- Department: Information & Knowledge Strat
- 1.5 points
Internship in NECR
This asynchronous, 1.5-credit elective combines a supervised professional internship with guided analysis of workplace culture, ethics, and feedback practices. Students evaluate organizational values, inclusivity, and ethical decision-making while developing the skills needed to navigate professional environments and identify the workplace cultures in which they will thrive.
- Department: Negotiation & Conflict Resolution
- 1.5 points
Internship in NMED
This asynchronous, 1.5-credit elective combines a supervised professional internship with guided analysis of workplace culture, ethics, and feedback practices. Students evaluate organizational values, inclusivity, and ethical decision-making while developing the skills needed to navigate professional environments and identify the workplace cultures in which they will thrive.
- Department: Narrative Medicine
- 1.5 points
Internship in NOPM
This asynchronous, 1.5-credit elective combines a supervised professional internship with guided analysis of workplace culture, ethics, and feedback practices. Students evaluate organizational values, inclusivity, and ethical decision-making while developing the skills needed to navigate professional environments and identify the workplace cultures in which they will thrive.
- Department: Non Profit Management
- 1.5 points
Internship in POAN
This asynchronous, 1.5-credit elective combines a supervised professional internship with guided analysis of workplace culture, ethics, and feedback practices. Students evaluate organizational values, inclusivity, and ethical decision-making while developing the skills needed to navigate professional environments and identify the workplace cultures in which they will thrive.
- Department: Political Analytics
- 1.5 points
Internship in SPRT
This asynchronous, 1.5-credit elective combines a supervised professional internship with guided analysis of workplace culture, ethics, and feedback practices. Students evaluate organizational values, inclusivity, and ethical decision-making while developing the skills needed to navigate professional environments and identify the workplace cultures in which they will thrive.
- Department: Sports Management
- 1.5 points
Internship in SUMA
This asynchronous, 1.5-credit elective combines a supervised professional internship with guided analysis of workplace culture, ethics, and feedback practices. Students evaluate organizational values, inclusivity, and ethical decision-making while developing the skills needed to navigate professional environments and identify the workplace cultures in which they will thrive.
- Department: Sustainability Management
- 1.5 points
Internship in SUSC
This asynchronous, 1.5-credit elective combines a supervised professional internship with guided analysis of workplace culture, ethics, and feedback practices. Students evaluate organizational values, inclusivity, and ethical decision-making while developing the skills needed to navigate professional environments and identify the workplace cultures in which they will thrive.
- Department: Sustainability Science
- 1.5 points