This course provides an overview of the traditional ERM frameworks used to identify, assess, manage, and disclose key organizational risks. The traditional ERM frameworks are those that are more commonly in use and include COSO ERM, ISO 31000, and the Basel Accords. This course also provides an understanding of the methods, tools, techniques, and terminology most organizations use to manage their key risks, presented in the context of the foundational elements of an ERM process. This will enable students to navigate the ERM landscape within most organizations, and, along with the second-semester course Value-Based ERM, evaluate opportunities to enhance the existing ERM practices and evolve their ERM programs over time.
This course provides an overview of the traditional ERM frameworks used to identify, assess, manage, and disclose key organizational risks. The traditional ERM frameworks are those that are more commonly in use and include COSO ERM, ISO 31000, and the Basel Accords. This course also provides an understanding of the methods, tools, techniques, and terminology most organizations use to manage their key risks, presented in the context of the foundational elements of an ERM process. This will enable students to navigate the ERM landscape within most organizations, and, along with the second-semester course Value-Based ERM, evaluate opportunities to enhance the existing ERM practices and evolve their ERM programs over time.
Weekly lectures will introduce film grammar, textual analysis, staging, the camera as narrator, pre-visualization, shot progression, directorial style, working with actors and editing. Lectures by all members of the full time directing faculty anchor the class, highlighting a range of directorial approaches with additional lectures on the techniques and aesthetics of editing. Each lecture will be supported by visual material from master film directors as well as the examples of the short films students will be required to produce in their first two semesters. For the final 7 weeks of the term, a student fellow will be available to mentor students through the planning of their 3-5 films.
Generative AI represents a pivotal technological evolution with profound implications for the global economy and modern society. This course delves into the decades-long development of AI and machine learning, emphasizing its emergence as a critical economic and strategic force. As we explore this technology, we will assess its potential to revolutionize industries, enhance capabilities, and introduce complex challenges related to security, identity, and ethical considerations.
In this dynamic landscape, both incumbent businesses and governmental bodies face the urgent need to adapt to this disruption and the transformative changes it heralds. This course seeks to unpack the catalysts of this technological surge, its foundational principles, and the critical knowledge required for modern leadership in the AI era.
Financial Psychology focuses on the intersection of human psychology and wealth
management and the basic elements of consumer behavior. Students will explore
all of the biases, behaviors and perceptions that impact client decision-making and
financial well-being. Most importantly, this course is specifically designed to help
prepare the advisor to better understand all of the factors that impact client
decisions in an effort to help them achieve their own personal goals.
Prerequisites: graduate standing. Introductory survey of major concepts and areas of research in social and cultural anthropology. Emphasis is on both the field as it is currently constituted and its relationship to other scholarly and professional disciplines. Required for students in Anthropology Department's master degree program and for students in the graduate programs of other departments and professional schools desiring an introduction in this field.
Each week, outstanding shorts from Sundance, Cannes, Tribeca, Aspen, and other international festivals will be screened and discussed. (You might see a few duds as well, for comparison purposes.) The emphasis in the first two weeks will be on shorts under six minutes, in preparation for the “3-to-5” project. The second two weeks will be devoted to films between 8 and 12 minutes long, in preparation for the “8-to-12”. The final weeks will include a variety of narratives the size of Columbia thesis films. Altogether, over forty films will be shown and discussed.
The Graduate Seminar in Printmaking and Related Media is designed to create a space that is inclusive yet focused on printmaking. Class time is structured to support, adapt and reflect students' needs and goals as individual artists and as a community. The course will examine printmaking as a medium in an expanded field, investigating its constitutive materials, exhibition and installation practices, and its ethics in the 21st century. The seminar will focus on the specific relations between tools, ideas and meanings that arise when artists engage with print media in various incarnations and concepts including editioned prints, multiples, artist-books, other types of printed matter, alternate means of distribution, and strategies of duplication and repetition. The ultimate objective is to provide students with in-depth knowledge of the materials, tools, histories and theories that underlie specific printmaking practices. The seminar combines discussion of students' artwork and research with readings on ethics, performance, cinema, poetics, data, museum practices, politics, and public space as they relate to printmaking.
While the Columbia Visual Arts Program is dedicated to maintaining an interdisciplinary learning environment where students are free to use and explore different mediums while also learning to look at and critically discuss artwork in any medium, we are equally committed to providing in-depth knowledge concerning the theories, histories, practices, tools and materials underlying these different disciplines. Each semester we offer one Graduate Seminar in a different discipline, or combination of disciplines, including moving image, new genres, painting, photography, printmaking, and sculpture. These Discipline Seminars are taught by full-time and adjunct faculty, eminent critics, historians, curators, theorists, writers, and artists. Each seminar focuses on specific relations between tools, ideas and meanings that arise when artists engage with a particular medium. The seminars combine discussions of readings and artworks with presentations of students' individual work and research.
Prerequisites: At least one semester of calculus. A calculus-based introduction to probability theory. Topics covered include random variables, conditional probability, expectation, independence, Bayes rule, important distributions, joint distributions, moment generating functions, central limit theorem, laws of large numbers and Markovs inequality.
Prerequisites: STAT GR5203 or the equivalent, and two semesters of calculus. Calculus-based introduction to the theory of statistics. Useful distributions, law of large numbers and central limit theorem, point estimation, hypothesis testing, confidence intervals, maximum likelihood, likelihood ratio tests, nonparametric procedures, theory of least squares and analysis of variance.
APPLIED MACHINE LEARNING II
Prerequisites: STAT GR5203 and GR5204 or the equivalent. Theory and practice of regression analysis, Simple and multiple regression, including testing, estimation, and confidence procedures, modeling, regression diagnostics and plots, polynomial regression, colinearity and confounding, model selection, geometry of least squares. Extensive use of the computer to analyse data.
Maps have long been used to explore and communicate spatial information for practical tasks such as navigation and more analytic pursuits such as understanding relationships at the intersection of social and natural sciences. Today, most data—whether in spreadsheets, documents, apps, or sensor logs—is tied to a location, making it “mappable”. Learning to analyze this spatial data allows us to discover patterns and quantify relationships which support data driven decisions.
This course introduces students to Geographic Information Systems (GIS) as a modern end-to-end toolset to collect, store, analyze, and visualize spatial data. Through lectures, readings, guided discussions, weekly hands-on exercises (both in class and at home), and an individual term project, students practice core spatial analysis techniques and spatial data visualization. Weekly lectures will cover GIS applications in fields relevant to sustainability management as well as GIS theory and skills. Weekly assigned readings will match lecture topics on both applications and GIS theory/skills. The required term project allows each student to connect and apply GIS methods to a question of personal or professional importance, producing a polished spatial analysis and map product which will be presented to the class using StoryMaps.
Course Overview:
This course introduces Python programming, covering data structures, control-flow, objects, and functions, along with libraries like re, requests, numpy, pandas, scikit-learn, scipy, and more. These skills are applied to real-world data science tasks, including AB testing, data manipulation, modeling, optimization, simulations, and data visualization.
Students will develop computational thinking abilities, including problem decomposition, pattern recognition, data representation, abstraction, and algorithm design, through practical exercises.
Course Overview:
This course introduces Python programming, covering data structures, control-flow, objects, and functions, along with libraries like re, requests, numpy, pandas, scikit-learn, scipy, and more. These skills are applied to real-world data science tasks, including AB testing, data manipulation, modeling, optimization, simulations, and data visualization.
Students will develop computational thinking abilities, including problem decomposition, pattern recognition, data representation, abstraction, and algorithm design, through practical exercises.
Corequisites: GR5203 or the equivalent. Review of elements of probability theory. Poisson processes. Renewal theory. Walds equation. Introduction to discrete and continuous time Markov chains. Applications to queueing theory, inventory models, branching processes.
This course examines the discipline of global marketing communication, including the environmental factors that enabled global marketing. The course assesses early models of communication management and the current factors that enable global communication programs: the identification of global target audiences; the kinds of products and services that lend themselves to global communication and those that don’t; and the characteristics of leadership brands that are preeminent in global communication today. Students consider how levels of development and cultural values affect communication programs and how local differences can be reflected in global programs. Message creation and the available methods of message distribution are evaluated in the context of current and future trends. Students learn how to approach strategy and develop an integrated, holistic global communication program and how to manage such a program.
Students explore the grammatical rules and narrative elements of cinematic storytelling by completing a minimum of three short, nondialogue exercises and two sound exercises, all shot and edited in video. Emphasizes using the camera as an articulate narrator to tell a coherent, grammatically correct, engaging, and cinematic story. Technical workshops on camera, lighting, sound, and editing accompany the workshops, as well as lectures that provide a methodology for the director.
Students explore the grammatical rules and narrative elements of cinematic storytelling by completing a minimum of three short, nondialogue exercises and two sound exercises, all shot and edited in video. Emphasizes using the camera as an articulate narrator to tell a coherent, grammatically correct, engaging, and cinematic story. Technical workshops on camera, lighting, sound, and editing accompany the workshops, as well as lectures that provide a methodology for the director.
This course will present students with the architecture, data, methods, and use cases of environmental indicators, from national-level indices to spatial indices. The course will draw on the instructor’s experience in developing environmental sustainability, vulnerability and risk indicators for the Yale/Columbia EPI as well as for a diverse range of clients including the Global Environmental Facility, UN Environment, and the US Agency for International Development. Guest lecturers will provide exposure to Lamont experience in monitoring the ecological and health impacts of environmental pollution and the use of environmental indicators in New York City government. Beyond lecture and discussion, classroom activities will include learning games, role play and case study methods.
The course will explore alternative framings of sustainability, vulnerability and performance, as well as design approaches and aggregation techniques for creating composite indicators (e.g., hierarchical approaches vs. data reduction methods such as principal components analysis). The course will examine data sources from both in-situ monitoring and satellite remote sensing, and issues with their evaluation and appropriateness for use cases and end users. In lab sessions, the students will use pre-packaged data and basic statistical packages to understand the factors that influence index and ranking results, and will construct their own simple comparative index for a thematic area and region or country of their choice. They will learn to critically assess existing indicators and indices, and to construct their own. In addition, students will assess the impacts of environmental performance in several developing and developed countries using available data (e.g., pollutant levels in soils and air in Beijing and NYC), and project future changes based on the trends they see in their assessments. The course will also examine theories that describe the role of scientific information in decision-making processes, and factors that influence the uptake of information in those processes. The course will present best practices for designing effective indicators that can drive policy decisions.
Advising Note:
Students are required to have had prior coursework in descriptive and inferential statistics.
Conflict and communications technologies are inextricably connected and this relationship is increasingly mediated by social networks. Individuals and organizations face many challenges in using online technology for collaboration and conflict mediation purposes. Recent software innovations can facilitate knowledge acquisition, network building, and the analysis and presentation of conflict-related data. For professionals working in the field of conflict resolution, it is imperative to understand the role developments in communications technologies has played in exacerbating and/or resolving conflicts.
This course will analyze the relationship between conflict and communications technologies. It will explore the challenges that individuals and networks face in using online technology for collaboration and conflict mediation purposes. It will demonstrate how recent software and social media innovations can facilitate knowledge acquisition, network building, and the analysis and presentation of conflict-related data. Finally, it will analyze contemporary cases where developments in communications technologies have played a critical role in exacerbating and/or resolving conflicts.
The course focuses on international peacebuilding and business and human rights cases. The former cases include Israel-Palestine, refugees, African peacebuilding, genocide prevention, and election violence monitoring. The latter cases include online harassment, cross-national email conflicts, sex trafficking, new business models such as Uber and AirBnB, and extractive resource conflicts.
The course will also instruct students in the use of social software (such as blogs, social media curation, and networking/visual mapping) and improve their “digital literacy” on a range of technologies. The course will provide practical (and often provocative) examples and challenge students to reflect on how these experiences and tools will be useful in their professional development and work environments.
This is the discussion that corresponds with the course CLMT 5015 Climate Change Adaptation. Students are required to register for a discussion section.
This is the discussion that corresponds with the course CLMT 5015 Climate Change Adaptation. Students are required to register for a discussion section.
This is the discussion that corresponds with the course CLMT 5015 Climate Change Adaptation. Students are required to register for a discussion section.
This is the discussion that corresponds with the course CLMT 5015 Climate Change Adaptation. Students are required to register for a discussion section.
This is the discussion that corresponds with the course CLMT 5015 Climate Change Adaptation. Students are required to register for a discussion section.
This is the discussion that corresponds with the course CLMT 5015 Climate Change Adaptation. Students are required to register for a discussion section.
Prerequisites: Knowledge of statistics basics and programming skills in any programming language. Surveys the field of quantitative investment strategies from a buy side perspective, through the eyes of portfolio managers, analysts and investors. Financial modeling there often involves avoiding complexity in favor of simplicity and practical compromise. All necessary material scattered in finance, computer science and statistics is combined into a project-based curriculum, which give students hands-on experience to solve real world problems in portfolio management. Students will work with market and historical data to develop and test trading and risk management strategies. Programming projects are required to complete this course.
Prerequisites: STAT GR5205 Least squares smoothing and prediction, linear systems, Fourier analysis, and spectral estimation. Impulse response and transfer function. Fourier series, the fast Fourier transform, autocorrelation function, and spectral density. Univariate Box-Jenkins modeling and forecasting. Emphasis on applications. Examples from the physical sciences, social sciences, and business. Computing is an integral part of the course.
This course is designed to furnish students with a conceptual framework for understanding climate tech innovation and an overview of practical ways to professionally engage in it. We focus on climate tech because the current global rate of decarbonization is not sufficient to limit warming to 1.5°C. To accelerate the rate of change and stabilize our planet’s climate, innovative technology development and diffusion is required. Beyond the moral imperative, rapid decarbonization represents an unprecedented economic opportunity. To realize the promise of a low-carbon economy, new practitioners must join the innovation ecosystem and drive it forward. This course will prepare students to do so.
The course starts by framing what climate tech means (i.e., all technologies focused on mitigating greenhouse gas emissions and addressing the impacts of climate change) and how climate tech innovation will occur (i.e., as a complex process including co-evolution of technology, regulations, infrastructure, and consumer behavior). It then provides an overview of the innovation value chain including various stakeholders and avenues for professional involvement. It concludes with a survey of sectoral innovation opportunities. Considerations of equity and just transition are covered throughout.
This course is designed to furnish students with a conceptual framework for understanding climate tech innovation and an overview of practical ways to professionally engage in it. We focus on climate tech because the current global rate of decarbonization is not sufficient to limit warming to 1.5°C. To accelerate the rate of change and stabilize our planet’s climate, innovative technology development and diffusion is required. Beyond the moral imperative, rapid decarbonization represents an unprecedented economic opportunity. To realize the promise of a low-carbon economy, new practitioners must join the innovation ecosystem and drive it forward. This course will prepare students to do so.
The course starts by framing what climate tech means (i.e., all technologies focused on mitigating greenhouse gas emissions and addressing the impacts of climate change) and how climate tech innovation will occur (i.e., as a complex process including co-evolution of technology, regulations, infrastructure, and consumer behavior). It then provides an overview of the innovation value chain including various stakeholders and avenues for professional involvement. It concludes with a survey of sectoral innovation opportunities. Considerations of equity and just transition are covered throughout.
Discussion for CLMT 5023: Climate Justice: Theory, Practice, and Policy.
Discussion for CLMT 5023: Climate Justice: Theory, Practice, and Policy.
Discussion for CLMT 5023: Climate Justice: Theory, Practice, and Policy.
Discussion for CLMT 5023: Climate Justice: Theory, Practice, and Policy.
This course introduces the Bayesian paradigm for statistical inference. Topics covered include prior and posterior distributions: conjugate priors, informative and non-informative priors; one- and two-sample problems; models for normal data, models for binary data, Bayesian linear models, Bayesian computation: MCMC algorithms, the Gibbs sampler; hierarchical models; hypothesis testing, Bayes factors, model selection; use of statistical software.
Prerequisites: A course in the theory of statistical inference, such as STAT GU4204/GR5204 a course in statistical modeling and data analysis such as STAT GU4205/GR5205.
The global sports industry is substantial, encompassing various aspects such as sporting events, merchandise, broadcasting, and more. In 2024, the industry's revenue amounted to nearly $470 billion. By 2028, the global sports market is expected to surpass $680 billion. By 2027, the global sports market is expected to surpass $623 billion. However, the influence of sports extends far beyond the field. Fans are both dedicated and passionate supporters who contribute to the industry's success and have a massive following across continents. From local matches to international tournaments, fans engage through attendance, viewership, merchandise purchases, social media interactions, and so much more.
As the market continues to grow, the sports industry has made significant progress toward embracing sustainability practices. Brands are increasingly transparent about their sustainability efforts, businesses are looking to partner with sustainability-focused organizations that have reputable certifications and initiatives, real estate developers and investors are designing environmentally friendly facilities, and athletes and their fan bases are demanding climate action, just to name a few. Despite some progress, there's ample room for growth within emerging sustainability practices in sports. Continued innovation can lead to eco-friendly materials, sustainable event management, ensuring sustainability across supply chains, and greening stadiums, venues, and event infrastructure, which can further minimize resource consumption and pollution and contribute to a healthier planet.
This course introduces the concept of sustainability and its relevance to the sports industry. It examines the environmental, social, and economic impacts of sports activities, events, and organizations and explores the strategies and practices that can enhance the sustainability performance of the sports sector. The course covers topics such as the definitions and dimensions of sustainability and how they relate to sports; the drivers and challenges of sustainability in sports (climate change, stakeholder expectations, governance, and innovation); frameworks and tools for assessing and reporting on sustainability in sports; best practices and case studies of sustainability in sports; and opportunities and benefits of sustainability in sports (fan engagement, athlete activism, business development, and social impact).
This course will be structured in the following main se
The global sports industry is substantial, encompassing various aspects such as sporting events, merchandise, broadcasting, and more. In 2022, the industry's revenue amounted to nearly $487 billion. By 2027, the global sports market is expected to surpass $623 billion.
1
However, the influence of sports extends far beyond the field. Fans are both dedicated and passionate supporters who contribute to the industry's success and have a massive following across continents. From local matches to international tournaments, fans engage through attendance, viewership, merchandise purchases, social media interactions, and so much more.
As the market continues to grow, the sports industry has made significant progress toward embracing sustainability practices. Brands are increasingly transparent about their sustainability efforts, businesses are looking to partner with sustainability-focused organizations that have reputable certifications and initiatives, real estate developers and investors are designing environmentally friendly facilities, and athletes and their fan bases are demanding climate action, just to name a few. Despite some progress, there's ample room for growth within emerging sustainability practices in sports. Continued innovation can lead to eco-friendly materials, sustainable event management, ensuring sustainability across supply chains, and greening stadiums, venues, and event infrastructure, which can further minimize resource consumption and pollution and contribute to a healthier planet.
This course introduces the concept of sustainability and its relevance to the sports industry. It examines the environmental, social, and economic impacts of sports activities, events, and organizations and explores the strategies and practices that can enhance the sustainability performance of the sports sector. The course covers topics such as the definitions and dimensions of sustainability and how they relate to sports; the drivers and challenges of sustainability in sports (climate change, stakeholder expectations, governance, and innovation); frameworks and tools for assessing and reporting on sustainability in sports; best practices and case studies of sustainability in sports; and opportunities and benefits of sustainability in sports (fan engagement, athlete activism, business development, and social impact).
A workshop in which the student explores the craft and vocabulary of the actor through exercises and scene study as actors and the incorporation of the actor's vocabulary in directed scenes. Exploration of script analysis, casting, and the rehearsal process.
Our interpersonal experiences and the personal identities we hold both shape and contribute to our individual concepts of health, as well as to our awareness of the beliefs and identities held by others. This course examines how various marginalized groups have historically organized and advocated to bring about change in communities impacted by health disparities and social injustice. How can understanding their stories and the strategies they've implemented to construct, share, and collect their narratives, inform health professionals and their allies in developing new and innovative approaches to hear, interpret, and respond to the needs of the communities they are charged with serving? At a time when a renewed focus is being placed on health equity, social justice, race, bias, resource distribution, and access, it is imperative to look more closely at the experiences of communities and the individuals within them who have been placed at greater vulnerability. With an attentiveness to intersectionality, critical race theory, and media studies, course materials will guide an exploration of narrative and its relationship to activism, advocacy, and messaging around community health.
This class provides a broad, quantitative introduction to the science underlying our understanding of the Earth’s climate system. Students will first learn the basic, fundamental concepts of energy transfer, the greenhouse effect, and general circulation in the climate system. We will then build on these ideas to explore more specialized topics, including climate variability now and in the past, the signs of climate change, climate models, extreme events, and projections of future climate. Lectures and slides will draw from the scientific literature, as well as the latest IPCC Assessment Report (AR6). By the end, students will have a working knowledge of the climate system, giving them the knowledge and skills to evaluate statements and claims in the media and from their peers. Limited math (basic algebra) will be necessary for some of the assignments. All lectures will be recorded, and all slide decks will be uploaded to Courseworks after class.
This class provides a broad, quantitative introduction to the science underlying our understanding of the Earth’s climate system. Students will first learn the basic, fundamental concepts of energy transfer, the greenhouse effect, and general circulation in the climate system. We will then build on these ideas to explore more specialized topics, including climate variability now and in the past, the signs of climate change, climate models, extreme events, and projections of future climate. Lectures and slides will draw from the scientific literature, as well as the latest IPCC Assessment Report (AR6). By the end, students will have a working knowledge of the climate system, giving them the knowledge and skills to evaluate statements and claims in the media and from their peers. Limited math (basic algebra) will be necessary for some of the assignments. All lectures will be recorded, and all slide decks will be uploaded to Courseworks after class.
This course is an introduction to Causal Inference at the masters level. Students will be introduced to a broad range of causal inference methods including randomized
experiments, observational studies, instrumental variables, di?erence-in-di?erences, regression discontinuity design, and synthetic controls. In addition, the course will cover modern, controversial debates regarding the foundations and limitations of causal inference.
The primary learning goal of this course will be to familiarize students with a variety of the most popular causal inference methods: which causal e?ects they seek to estimate, basic assumptions required for identi?cation and estimation, and their practical implementation. To this end, the course will focus both on developing the pre-requisite statistical / methodological theory and as well as gaining hands-on experience through implementation exercises with real datasets. By the end of the course, students should have deep familiarity of various causal inference methods and—more importantly—be able to determine which method is most appropriate
for a given applied problem and to judge whether the pre-requisite identifying conditions are appropriate.
Whether alone with ourselves, or in close relationships with important people in our lives, dominant narratives shape our encounters by bringing certain aspects of our experience to the fore and marginalizing others. Narrative Therapy is a school of thought developed by Michael White, the Australian psychotherapist and social activist. Influenced by Social Constructionism and the writings of Michel Foucault (among others), White sought to understand the ways in which systems of power and control on the societal level shape our most intimate experiences. There is a price we pay for the hegemony of dominant narratives (as Foucault would say) as other aspects of our experience become marginalized and pushed out of awareness in this process. But by analyzing the dynamics by which certain narratives come to hold sway over us, and by considering what goes missing from our experience, Narrative Therapy seeks to undo this price by re-evaluating the stories we live by so that they can be more expansive and less limiting.
In this course we will look at the basic concepts and theoretical underpinnings of Narrative Therapy, and then begin to understand the essential techniques and areas of application of this important therapeutic school. This course does not train students to practice therapy. Our emphasis instead will be on developing ideas for ways in which the concepts and techniques introduced by Narrative Therapy can inform the practice of Narrative Medicine.
Questions we will address include:
● What can we learn from Narrative Therapy about the ways people structure stories about themselves, and how does this affect their relationship with their bodies, with illness and their conceptions of healing?
● What are the mechanisms by which dominant narratives from the social sphere are integrated into an individual’s self concept, and how does this then influence power relations in the clinical encounter?
● Theorists within Narrative Therapy strive to foster a non-hierarchical, non-expert stance in the clinical encounter. What are the possibilities and the challenges inherent in maintaining this?
Prerequisites: STAT GR5241 This course covers some advanced topics in machine learning and has an emphasis on applications to real world data. A major part of this course is a course project which consists of an in-class presentation and a written project report.