Global greenhouse gas (GHG) emissions are now at a record high, and the world’s scientific community agrees that continued unabated release of greenhouse gases will have catastrophic consequences. Many efforts to curb greenhouse gas emissions, both public and private, have been underway for decades, yet it is now clear that collectively these efforts are failing, and that far more concerted efforts are necessary. In December 2015, the world’s nations agreed in Paris to take actions to limit the future increase in global temperatures well below to 2°C, while pursuing efforts to limit the temperature increase even further to 1.5°C. Achieving this goal will require mitigation of greenhouse gas emissions from all sectors, both public and private. Critical to any attempt to mitigate greenhouse gas emissions is a clear, accurate understanding of the sources and levels of greenhouse gas emissions. This course will address all facets of greenhouse gas emissions accounting and reporting and will provide students with tangible skills needed to direct such efforts in the future.
Students in this course will gain hands-on experience designing and executing greenhouse gas emissions inventories for companies, financial institutions and governments employing all necessary skills including the identification of analysis boundaries, data collection, calculation of emissions levels, and reporting of results. In-class workshops and exercises will complement papers and group assignments. A key component of this course will be critical evaluation of both existing accounting and reporting standards as well as GHG emissions reduction target setting practices.
This course will introduce many of the challenges facing carbon accounting practitioners and will require students to recommend solutions to these challenges derived through critical analysis. Classes will examine current examples of greenhouse gas reporting efforts and will allow students the opportunity to recommend improved calculation and reporting methods.
Prerequisites: BUSI PS5001 Intro to Finance and BUSI PS5003 Corporate Finance or Professor Approval required. If you have not taken PS5001 or PS5003 at Columbia University, please contact the course instructor for approval. Students will learn about the valuation of publicly traded equity securities. By the end of the semester students will be able to perform fundamental analysis (bottoms-up, firm-level, business and financial analysis), prepare pro forma financial statements, estimate free cash flows and apply valuation models.
Environmental, social and governance issues (‘ESG’) are moving to center stage for corporate boards and executive teams. This elective course complements management and operations courses by focusing on the perspective and roles of the board and C-suite of corporations, financial institutions and professional firms in addressing ESG risks as well as promoting and overseeing governance aligned with ESG principles. The course focuses on the interchange between the external legal, competitive, societal, environmental and policy ‘ecosystems’ corporations face (which vary around the world) and a company’s internal structure, operations and pressures. We will use the United Nations Guiding Principles on Business and Human Rights and the UN Global Compact Principles (which incorporate all aspects of ESG) as the central frameworks to explore the concept of a corporation’s responsibility to respect and remedy human rights and environmental harms. We will also examine the Equator Principles and other frameworks that spell out good practices for project finance and other investment decisions, and reference a wide range of the myriad indices, supplier disclosure portals and benchmarks that exist in this inter-disciplinary field. Relevant regulations, corporate law regimes and court cases will be discussed from the point of view of what business managers need to know. While most of the course will deal with companies and firms serving global, regional or national markets, several examples will deal with the question of how the ESG ecosystem affects or offers opportunities to start-ups.
Often, our progress toward the remediation of persistently accumulating human damage to our collective home, the biosphere, is attributed to large-scale entities having a rather amorphous quality. Such are the industrial revolution, the global north, capitalism, colonialism, and countless preoccupied, habituated or denialist components of the human population. Yet, the dynamics of all types of leadership and management, whether in public, civic or private organizations, frequently push back on the progress desired, in more specific ways. These dynamics are so characteristic that climate ethics, an offshoot of environmental ethics, may seem to be cornered or futile. However, looking more closely at the essential functions of leadership and management, we may find the possibilities of change for the better: change that reverses climate change, or more widely, unsustainability. Conversely, we may find inadequate possibilities for such critical change.
In this course, leadership and management are explored to determine their dynamics are and how these afflict our biospheric home—including virtually all life. The course is divided into 4 sections, the 1st is two weeks long, the 2nd and 3rd are each four weeks long, and the 4th is two weeks long. The topic of the 1st section is climate ethics, their content and context: how they work and how they are tripped by surrounding problematic discourses. The topic of the 2nd section is leadership: at its becomingly best, and how it demeans itself with incapability, irresponsibility and corruptibility. The topic of the 3rd section is management: at its operationally best, and how it degrades itself with dysfunctional hierarchy, captive systematization, and offensive behavior. The topic of the 4th section reverts to climate ethics: the necessity of accruing and maintaining value—of the right kind, and the necessity of creating and applying guidance—of the right kind. It is not only because the impacts of problematic ways of doing things are harmful to the biosphere but also because those impacts have others, which are increasingly desperate, rancorous and volatile.
The signing of the Paris Treaty in 2015 signaled a recognition by nearly all the world’s governments of the need to reduce greenhouse gas emissions to avoid the worst effects of climate change. Meanwhile, the changing climate is already having negative impacts on business assets and operations around the world. Despite evidence that climate change poses a threat to business as usual for many companies, the financial sector has yet to form a consistent view on how to value risks and opportunities associated with climate change. There are multiple reasons for this. Climate-related disclosures vary widely from company to company, as do the ways that climate risks affect different sectors and geographies. The policy landscape is varied and fast changing. Unfortunately, many financial analysts lack the technical knowledge to assess corporate disclosures and actions pertaining to climate.
This 6-week course provides a practical overview of how analysts in the financial sector can assess corporate climate risk and opportunity among publicly traded corporates, using public data. The class will begin with the concept of how business leaders and financial analysts understand climate risk – alongside other concepts such as decarbonization, transition planning and climate impacts from a policy perspective.
We will then move to focus on industry-specific analysis in four sectors – 1) oil and gas, 2) consumer staples, 3) mining, and 4) financial services. In each, we will survey the tools that investors have to assess climate risk and opportunity, taking into account policy, voluntary frameworks, and technology. For each of these elements, we will review both how these tools can assist with climate risk analysis as well as their limitations and inconsistencies. We will consider ways the analyst can work with relevant data and reconcile public corporate claims with evidence through corporate disclosures.
The application of Machine Learning (ML) to climate science and environmental sustainability has become increasingly popular in recent years, promising to revolutionize how we analyze and address critical environmental challenges. This course will introduce students to the fundamental concepts and methods of ML, emphasizing their practical applications to climate science and environmental sustainability efforts.
Students will gain both theoretical knowledge and practical skills through hands-on experience with machine learning methods and coding. The course is designed to provide familiarity with the design, implementation, and evaluation of machine learning models towards addressing specific problems in climate science and sustainability. By working with real-world datasets, students will develop a deeper understanding of both the capabilities and limitations of ML tools in climate research and for evaluating environmental sustainability solutions. This course will cover essential topics such as data preprocessing, model selection, evaluation metrics, and the ethical implications of ML in climate science.
As ML tools become increasingly important to these application areas, this course will be invaluable for those looking to interact with scientists and engineers, manage scientific projects, and develop policies in the realm of climate science and sustainability.
Globally, there are over 2 billion people suffering from moderate-to-severe food insecurity, with an estimated 600 million people projected to be chronically undernourished by 2030. One key aspect to understanding food insecurity is its spatial distribution and trends that contribute to how food secure a population is. This course will teach students how to collect and analyze spatial data related to food security, as well as touch on important topics in food insecurity. The course will focus on taking real-life food security questions and applying spatial analysis techniques to these questions. In the course, we will cover an introduction to spatial analysis, natural experiments in geography, applying remote sensing to food insecurity, climate shocks and food security, and seasonal forecasting and food security.
It will have an in-class aspect, which will mainly focus on topics in food security and how they relate to data collection, and a lab section which will be an opportunity for students to collect data directly, clean the data, and analyze the data using the R programming language with spatial research methods. Example topics in class will be climate variability and food insecurity, women’s role in agriculture and their rates of food insecurity relative to men, and population and health. These topics will then be further explored in the lab section of the class: specifically focusing on downloading weather data for time series analysis, using a convergence of datasets to map hotspots, and investigating how survey data intersects with spatial datasets.
In this course, there will be two components; a lecture and a lab. The lecture will be short and focus on relevant topics in Food Security and methodology used to quantitative analyze these topics. The lab will be a computer-based lab in R, analyzing relevant food security data using techniques discussed during the lecture to provide a practical base for quantitative analyses.
Computing and data analysis have become an indispensable tool for researchers and industry professionals working in virtually any aspect of the modern world. This course will introduce students to the fundamental concepts and methods that are broadly applicable to any data science project, with a thematic focus on climate and environmental data. This includes an introduction to Unix, programming, common data formats, analysis, and visualization. The primary focus will be to teach students the foundations of Python in a climate data science context, which is of the most widely used and accessible programming languages today. Students will also be introduced to cloud computing, which will be the primary tool for in class assignments and projects.
The course is designed to be accessible for any students with an interest in being able to ask and answer questions using data. This course will also be invaluable for those looking to interact with scientists and engineers, manage scientific projects, and develop policies in the realm of climate science and sustainability.
The topic of health care continues to capture the attention of the nation in ongoing debates fueled by rising costs, overutilization and the implementation of much needed reforms (Affordable Care Act). As the healthcare industry continues to rapidly evolve, it provides immense opportunities for learning and applying concepts, theories and research related to negotiation and conflict resolution in procurement of medical devices and difficult conversations such as advanced directives to name a few. This course is applicable not only to students pursuing careers in health care, but is also designed for students who are interested in applying negotiation skills that they have learned in an environment that can be emotionally charged and conceptually complex.
Throughout this course students will be given the opportunity to apply the skills they have learned from previous classes as well as solidify key concepts including but not limited to negotiation preparation, quantitative/qualitative analysis, influence, social cognition, asymmetrical information, and conflict resolution in a healthcare context. This course is designed to challenge each student to harness their critical thinking skills, uncover nuances and recognize the complexities associated with multiparty negotiations in healthcare. This course aims to enable students to develop and implement strategic processes that help bring parties together and promote new perspectives that will bridge the gap between the classroom and real-life scenarios.
During the course, students will gain insight into the history of the US healthcare system as well as the changing dynamics associated with the Health Care Reform, and end of life discussions. This course will emphasize the role of negotiations from multiple perspectives and will utilize an expert panel videos of such subject matter experts as hospital administrators/executives, physicians and medical device manufacturers in order to provide historical case studies as well as review real-life negotiations. Students will actively engage in negotiation planning and role plays, read case studies and other materials about negotiation and the healthcare field, as well as, use industry software to help them prepare for negotiations.
Social scientists need to engage with natural language processing (NLP) approaches that are found in computer science, engineering, AI, tech and in industry. This course will provide an overview of natural language processing as it is applied in a number of domains. The goal is to gain familiarity with a number of critical topics and techniques that use text as data, and then to see how those NLP techniques can be used to produce social science research and insights. This course will be hands-on, with several large-scale exercises. The course will start with an introduction to Python and associated key NLP packages and github. The course will then cover topics like language modeling; part of speech tagging; parsing; information extraction; tokenizing; topic modeling; machine translation; sentiment analysis; summarization; supervised machine learning; and hidden Markov models. Prerequisites are basic probability and statistics, basic linear algebra and calculus. The course will use Python, and so if students have programmed in at least one software language, that will make it easier to keep up with the course.
Artificial intelligence (AI) and generative AI – like ChatGPT, MidJourney, and Gemini – are poised to change the world for everyone. It is critical that students understand (and utilize) this new technology at several levels. In this class – through readings and a dozen hands-on activities – students will come to deeply understand AI. Specifically, students will construct (using Python) some of the basic building-blocks of AI, like machine learning (like recommendation systems), natural language processing (like word embeddings) and chatbots. They will test out AI’s capabilities and refine prompts in real-world settings, whether in art, video, writing or Internet-of-Things. They will learn about how generative AI fits into the history of technology adoption and the diffusion of innovation, answering questions like: Will AI be able to replace whole jobs? And if so, when? They will use the lenses of psychology and economics to explore the impact of AI in people’s lives, including in the context of algorithmic fairness, regulation and intellectual property. They will be pushed to take human creativity in new directions, augmented by AI’s “weirdness.” Lastly, students will be pushed to further develop their own uniquely-human skills – like in critical thinking and empathy – in response to the power of generative AI to mimic humans. As best-selling author Seth Stephen-Davidowitz has recently (Dec. 2023) written, “So far, my newest book has higher ratings than either of my previous two books -- even though it was written in 1/36th of the time, thanks to AI. AI is wild!" By the end of this class, students will feel empowered technically and philosophically to handle all new generative AI developments. There are no specific prerequisites for this class.
Digital media opens new opportunities for increasingly targeted communications across a variety of channels, which rapidly expands the importance of analytics in tracking and measuring key performance indicators (KPIs). This course prepares students to work within data- and model-driven environments with an emphasis on using analytics to develop insights and support strategic decisions.
Foundational ERM course. Addresses all major ERM activities: risk framework; risk governance; risk identification; risk quantification; risk decision making; and risk messaging. Introduces an advanced yet practical ERM approach based on the integration of ERM and value-based management that supports integration of ERM into decision making. Provides a context to understand the differences between (a) value-based ERM; (b) traditional ERM; and (c) traditional "silo" risk management.
This required NECR course will introduce the concepts and skills of mediation, a type of third-party conflict intervention. This course will provide students with theory, research, and practice to effectively use mediation skills in a wide variety of contexts. Mediation practices are frequently applied to a variety of conflicts and are employed in conflict resolution strategies. Thus it is imperative for a conflict resolution practitioner to develop knowledge and skills of this practice. In this course students will be introduced to mediation philosophies, approaches, applications, and skills through readings, scholarly reflections, role-plays, a collaborative group project, and a term paper. This course will provide a deeper understanding of problem-solving and relational styles of mediation and the goals aligned with each. Students will learn to identify when mediation is appropriate, prepare for a mediation, employ communication skills, deal with negative emotions, address ethical dilemmas, and consider the cultural influences surrounding the parties and conflict.
Prerequisite: NECR 5105 Introduction to Negotiation
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In this course, we will explore negotiation from several points of view and approaches. We will also look at characteristics that impact the quality of our negotiations and the outcomes, such as the role of emotions, cultural considerations, effectiveness of our communication, and opportunities to seek out negotiation to transform relationships. The course will be a blend of concepts and skills, theory and practice. On some occasions, you will be introduced to a concept and then asked to apply those concepts in an experiential activity. At other times, you will be asked to engage the activity or simulation and then the concepts will be elicited based on your experience. You will have several opportunities to practice developing your skills throughout the course, in terms of enhancing your practice and honing your analytical and conceptual understanding.
This course provides an opportunity for students in the Economics Master of Arts Program to engage in off-campus internships for academic credit that will count towards their requirements for the degree. The internships will facilitate the application of economic skills that students have developed in the program and prepare them for future work in the field.
Design-based Innovation is a set of perspectives and processes that organizations of all kinds, in any kind of industry or context, can use to navigate ambiguity to find the best possible opportunities to create change. It is also a well-developed set of practices to devise and deliver solutions for those potential audiences that result in valuable product, service, and other experiences that customers, consistent, and others respond to with satisfaction, delight, and a sense of value.
This class is a journey into the “fat edge” of technological innovations that could transform our economy and society over the coming years. We will tackle big questions: How do innovations redefine jobs and industries? What is the real impact of these changes from the C-suite to citizens? This course is about igniting a passion for change, a realization of its risks, and equipping you to lead with vision and principle.
This course provides a comprehensive examination of modern software product development, focusing on creating solutions that address clear user needs and challenges. A “product” in this context refers to a software program that instructs computer hardware to operate, solve problems, and manage tasks effectively.
Modern product development benefits from systematic practices that enhance efficiency, sustainability, and continuity. These practices, including flexibility, iterative development, customer feedback, and efficient project management, are essential for adapting quickly to rapidly evolving market and technology landscapes.
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With the advent of generative AI and the impending arrival of quantum computing, risks to organizations and individuals have grown exponentially. Innovation in offensive and defensive tools and technologies continues to increase. How does a leader keep up? Leaders must know how to work with internal experts and to manage these issues internally, with Boards, and for the public. Proficiency in strategies and principles, some of which date back to the ancient Greeks and Chinese, prevail over tools.
Existing energy sources and the infrastructures that deliver them to users around the world are undergoing a period of rapid change. Limits to growth, rapidly fluctuating raw material prices, and the emergence of new technology options all contribute to heightened risk and opportunity in the energy sector. The purpose of this course is to establish a core energy skill set for energy students and prepare them for more advanced energy courses by providing a basic language and toolset for understanding energy issues.
Using theoretical and practical understanding of the process by which energy technologies are developed, financed, and deployed, this course seeks to highlight the root drivers for change in the energy industry, the technologies that are emerging, and the factors that will determine success in their commercialization. Understanding these market dynamics also informs good policy design and implementation to meet a broad range of social welfare goals.
Upon completing the course, students should not only understand the nature of conventional and emerging energy generation and delivery, but also the tools for determining potential winners and losers and the innovative pathways to drive their further deployment.
This course is designed either for students who wish to embark on or further careers in politics and for those interested in exploring the dynamic field of political communication. Three themes anchor the course material: 1.) strategic communication, or deliberate and goal-oriented communication, which enables professionals to analyze and execute political strategy; 2.) message, which enables the crafting and critique of more or less effective political communication; and 3,) research, which political professionals use to formulate, shift and optimize their strategies.
Java is a versatile and powerful programming language widely used to build scalable, secure, and reusable applications. It is invaluable for processing large datasets, automating data workflows, and integrating analytical models with enterprise systems. Java’s extensive libraries and frameworks, combined with platform independence, make it an essential tool for creating robust data-driven solutions. From building data pipelines to creating APIs that connect analytical models to operational systems, Java equips students with the skills needed to tackle real-world analytical challenges.
This elective course introduces graduate students to Java programming with the overall goal of technical fluency in the programming language. Through a practical and application-focused approach, students will learn to write, compile, and execute Java programs while mastering foundational programming concepts. Key topics include object-oriented programming (OOP) principles, Java's role in modern software development, and the essential tools, libraries, and frameworks.
The course emphasizes developing problem-solving skills through hands-on programming assignments. It blends conceptual learning with practical experience in one of the most widely used programming languages in enterprise software development.
This course examines how international nongovernmental organizations (INGOs) can and often do contribute to social change, confronting and addressing various problems such as poverty, human rights violations, conflict, and climate change, among others. Students will leave with a deep appreciation of what it means to work in or with an advocacy-based NGOs. The course will help prepare them for future careers as an NGO leader, staff person, consultant, analyst, donor, or manager. Students will understand how NGOs are structured and the definition and differences between key concepts such as strategy, theory of change, governance, leadership, management, and program design.
The course will bring a scholar-practitioner perspective focusing on debates about strategy development, measuring impact, donor strategies, theories of change, institutional representation, diversity and equity, ethics, research methodologies, partnerships, networks, venues of engagement, campaigning, capacity-building, fundraising, resilience, sustainability, and external and internal communications.
The course will explore distinctions, similarities, and relationships among nongovernmental (national and international), government, and private actors as they seek to solve problems and have impact and create a better world. Throughout this exploration, we will identify major ethical issues raised by the very notions of charity, philanthropy and nonprofits. As a focus, the course will especially draw on examples from the international human rights movement, and often critically employ a “donor perspective” to draw out the hard strategic choices that INGOs (and their donors) are compelled to make. The course will also use documentary film about INGOs and their work, and various media produced about and by INGOs to help provide additional understanding.
The course will be discussion intensive and require students to utilize and reflect critical and analytical thinking; students will write individual papers, participate in group presentations, write occasional reflection papers, actively participate in discussion both in class and through postings on Canvas and present material to classroom colleagues.
This is an elective course in the M.S. Nonprofit Management Program and will be open, space permitting, to cross-registrants.
The course will draw on material from the management course offered as part of the core curriculum. It is not a prerequisite for taking the course but the syllabus ass
This is an interdisciplinary workshop for scientists, future NGO workers and journalists seeking skills in communicating 21st-century global science to the public. Scientists will be given journalism skills; journalists will learn how to use science as the basis of their story-telling. The course is designed to give students exercises and real-world experiences in producing feature stories on global science topics. While most scientists and international affairs professionals have been trained to write in the style of peer-reviewed journals, we will focus on journalism techniques, learning how to translate global science into accessible true stories that reach wide audiences.
Science is performed by passionate individuals who use their intelligence and determination to seek answers from nature. By telling their histories and uncovering the drama of discovery, we believe that there are ways for science to be successfully communicated to readers who might otherwise fear it.
Effective dialogue is one of the single most important activities of leaders today. Whether you are confronting a team member who is not keeping commitments, critiquing a colleague’s work, disagreeing with a spouse about financial decisions, or telling someone no, critical conversations are often avoided or handled in clumsy ways. This course will provide the theory underpinning these conversations, diagram their structure, and provide specific strategies for approaching them successfully.
This course is designed to provide students with working knowledge on how to make successful investments in sustainable companies and to prepare students to be conversationally literate in financial reporting. As you leave the school and become leaders of organizations financial literacy will be a skill set that will be vital to success no matter what career path you go down. It starts with a strong foundation in accounting and corporate finance, then moves on to ESG/Impact screening of potential investments, along with valuation techniques used to arrive at a purchase price. It will explore financial models that can aggregate multiple variables used to drive investment decisions.
To understand and lead a transition to a sustainability-aware business, managers must first be familiar with the terminology, practices and consequences of traditional accounting and finance. Students will learn traditional financial and accounting methods and tools. We will examine how these methods and tools are changing to improve product and service design, resource efficiency and allocation, employee productivity and sustainability performance outcomes. Students will learn how value is created in a company and the different methods employed to create that value, conduct due diligence, discuss optimal capital structure to finance a transaction, execute a transaction, and implement a Sustainability-based value-added operating plan to the target company. The course will conclude with students preparing a persuasive investment memo and accompanying financial model to the investment committee of an impact investing asset management firm. The course also provides a practical introduction to selected non-financial accounting topics including sustainability reporting standards, ESG corporate performance indicators and corporate social responsibility report (CSR Reporting).
This course will build on the topics and tactics covered in Business Intelligence in Sports to create a real-life learning lab where students can apply key concepts and expand their techniques against real data from a partner professional sports team. More advanced skills around SQL, Tableau, and R will be developed and applied to relevant scenarios using available data such as customer demographics, behaviors, tickets, attendance, social media, marketing, surveys, and sponsorships. Students will leave the class prepared to join a team’s business intelligence department and make immediate contributions.
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.
This course explores the intersection of theory and practice in conflict resolution, giving students the opportunity to apply the models, frameworks, and theories they have studied in the NECR program to real-world scenarios. Students will analyze case studies, review current events, and bring to bear their own experiences in international, organizational, community, and interpersonal conflicts in an interactive setting as they continue to develop and hone their critical thinking skills.
Drawing from the disciplines of social psychology and clinical psychology, political science, international relations, and the latest advances in neuroscience, conflict resolution practitioners have at their disposal a wealth of research that can inform their analysis of how to assist parties to mitigate, de-escalate, and prevent conflict.
Building especially on the material covered in Understanding Conflict and Cooperation (PS5101), the participants in this class will engage with the course readings, instructors, and each other to critically analyze and deconstruct complex conflicts in a variety of contexts. A focus on the actors, issues, structures, strategies, and processes inherent in a conflict will be used in the effort to identify opportunities to change conflict dynamics. Multiculturalism, negotiation and mediation frameworks, accounting for bias, interdependency, intergroup conflict, social identity, peacebuilding, and power dynamics are among the key learnings integrated into the course.
The competencies advanced in this class are intended to be applicable beyond the program into other areas of life. Students will be empowered to reflect critically on a text, select relevant data, understand the applicability of a theory, and offer results-based recommendations in contexts ranging from global to personal.
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.
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.
Prerequisites: STAT GU5204 and STAT GU5205 Open to MA students in Statistics only Introduction to programming in the R statistical package: functions, objects, data structures, flow control, input and output, debugging, logical design, and abstraction. Writing code for numerical and graphical statistical analyses. Writing maintainable code and testing, stochastic simulations, paralleizing data analyses, and working with large data sets. Examples from data science will be used for demonstration.
On a daily basis we may encounter conflicts and seek to resolve them through negotiations and other forms of conflict resolution. Some of these are simple and easy to resolve, while others are complex and may require the support of a third party, or
mediator
. In this course we will explore mediation from several points of view and approaches, as listed below under the session headings. We will explore the theories that underlie the field of mediation as we concentrate on building the skills necessary to practice mediation professionally.
Note: This course qualifies as the prerequisite for an apprenticeship opportunity in anticipation of
mediation certification
through a number of Community Dispute Resolution Centers statewide. This course is also Part 146A approved, which is necessary to qualify for participation on a roster in the New York State Court System.
Dynamical Systems Theory (DST) is a methodology developed in the hard sciences to understand complex systems—from the weather to the functioning of cells, using mathematical algorithms. We added the lens of social-psychological concepts and practices to better understand how to apply DST to conflict. We are now applying DST to conflict analysis and resolution for larger social problems and conflicts that are protracted, deeply embedded and have multiple complex issues. This DST approach goes beyond linear problem-solving and embraces complexity in new ways. Dynamical Systems and Conflict Resolution (NECR 5210) is a required 3-credit course in the Negotiation and Conflict Resolution Program (NECR). Students are expected to spend on average 20 hours per week on this course, including media, group work, readings, and other assignments. NECR 5210 builds on concepts from Understanding Conflict and Cooperation (NECR 5101), where students became familiar with conflict resolution frames, theories, and models, as well as a basic understanding of the DST approach. This course will further develop and advance student understanding and use of advanced DST concepts and tools that will be useful for scholar-practitioners facing situations that require a systemic approach for more highly complex conflicts. It is a complementary approach that rounds out the other concepts and skills student learn in the program. Throughout this course students will work individually and in groups on multiple case studies, to understand and apply DST methodology, while developing an appreciation for the more fluid and non-linear DST approach.
Open to MA students in Statistics only Prerequisites: STAT GU4205 or the equivalent. 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 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.
Prerequisites: STAT GR5206 or the equivalent. Open to MA students in Statistics only The course will provide an introduction to Machine Learning and its core models and algorithms. The aim of the course is to provide students of statistics with detailed knowledge of how Machine Learning methods work and how statistical models can be brought to bear in computer systems - not only to analyze large data sets, but to let computers perform tasks that traditional methods of computer science are unable to address. Examples range from speech recognition and text analysis through bioinformatics and medical diagnosis. This course provides a first introduction to the statistical methods and mathematical concepts which make such technologies possible.
Provides a global review of ERM requirements of regulators, rating agencies, and shareholders. Addresses three industry sectors: (1) insurance; (2) banking; and (3) corporate.
The elective "Open Source Intelligence: Research for Conflict Analysis"
course is designed to introduce students to key practical insights, tips, and professional skills necessary for any successful conflict resolution practitioner. In this course, students will be required to practically apply some of the tools and techniques of NECR, and appreciate the importance of combining and reformulating the basic NECR concepts in order to serve their exact needs in the field.
Through this course, students have the opportunity to apply what they have learned in the classroom, learn additional practical research skills, and adjust them to their own very specific professional aspirations in the field. This course also helps students strategize their next professional steps in the field in a concise, methodical way.
It is important to keep in mind that the Conflict Resolution field at large is quite diverse, and our students have unique backgrounds and future aspirations. Therefore, this course is customized in coordination with each student during 1-on-1 sessions that take place at the beginning of the semester, in order for each student to be working on something that is clear, and has practical value for his/her very specific professional interests.
As with many things in life, proactiveness, creativity, and an entrepreneurial spirit are keys to success for our very challenging field. Each student will be having a required 1-on-1 session with the instructor, where the instructor will help the student explore ways to creatively strategize their next professional steps as practitioners and also develop the instructions for the final paper that match the needs of the student.
Overall, the goal is to provide students with an enriching, personal experience that helps them rethink their role as practitioners and strategize better their short/ long term goals in Negotiation and Conflict Resolution.
The creation and maintenance of sports leagues is a nuanced and complex endeavor. This course examines the format, hierarchy, membership, governance, and operational efficiencies of several sports leagues that have been launched with varying levels of success. Through a combination of lectures, case studies and guest speakers, students will learn about the ideation, funding, legal aspects, marketing, media strategy and monetization of these businesses, both domestically and globally. Students will gather data about emerging sports leagues of the past and present and conduct research on the leagues of their choice. The culminating project in this course will be an original proposal by student groups of a new sports league, addressing all of the aforementioned dimensions in a formal presentation to potential ‘investors.’ Students will present their proposal via online video conference for instructor feedback following the block week. This course is ideal for students who have an interest in the structural and operational decisions that affect the success and sustainability of sports leagues and their members.
This is an elective course for the M.S. program in Sports Management; students in the program may take this course when allowed by their curriculum requirements. Students outside of the Sports Management program may take this course upon approval of the Academic Program Director.
Prerequisites: STAT GR5204 or the equivalent. STAT GR5205 is recommended. Open to MA students in Statistics only A fast-paced introduction to statistical methods used in quantitative finance. Financial applications and statistical methodologies are intertwined in all lectures. Topics include regression analysis and applications to the Capital Asset Pricing Model and multifactor pricing models, principal components and multivariate analysis, smoothing techniques and estimation of yield curves statistical methods for financial time series, value at risk, term structure models and fixed income research, and estimation and modeling of volatilities. Hands-on experience with financial data.
This course provides strategic communication students with the foundational notions and methods of design needed to collaborate with designers and amplify their work. It examines the impact technology and social transformations are having on design: the application of digital and generative technology, the redirection toward human-centric approaches, and the discipline’s standing in embracing social and ethical concerns related to ensuring inclusivity and preventing cultural bias. The course begins with a historical overview of design’s evolution and contemporary methods, setting the stage for an in-depth exploration of visual perception principles and key design elements like shape, form, color, typography, imagery, and layout. Students will apply the knowledge gained by experimenting with design practices and developing design strategies and applications through serial hands-on, collaborative assignments and workshops.
Sitting at the intersection of business strategy, digital development, user experience, communication, and publishing, content strategy has emerged over the last few years as a discipline examining the purpose behind content (in all manifestations) and how it supports business, organizational, and user goals. While it originated in digital web design and user experience, content strategy now encompasses a much broader set of considerations and addresses content creation, distribution, and governance across multiple channels, especially the interplay among digital, social, and traditional media. Content strategy provides a holistic approach for unlocking the value behind content and for increasing its effectiveness in achieving business and organizational objectives. This course will present the fundamentals of content strategy and explore the discipline’s approaches, techniques, and tools that course participants can apply directly to the content situation in their own organization. It will draw parallels with – and highlight distinctions among – traditional communication strategy, publishing, and content strategy, and provide students with a framework to create a sustainable program grounded in meaningful, actionable content.
Safety is a deceptively simple concept. On one end of the spectrum, it is a tangible state of being (Are you at risk of physical violence?) and immediate feeling (Are you comfortable walking alone at night?). At the other end, safety is a broader system embedded in a complex network of social relations, formal and informal organizations, and political dynamics: Do you trust your neighbors? Do you trust the police? Do you have access to the resources you need to be and feel safe from harm? In New York City, the problem of public safety presents a complex tapestry of conflicts, deeply rooted in varying attitudes and policies. The city's approach to public safety often stirs up debates around policing strategies, with some advocating for a robust, proactive law enforcement presence to deter crime, and others calling for more community-based, social justice-oriented methods. And this is only about policing. Most people will say that for them, safety is about much more than policing. Such complexity has led to a broad array of tensions and conflicts in New York City, particularly in neighborhoods like the three in this course, where residents often feel both over-policed and under-resourced.
In this course, we will draw on an active research project under the leadership of Dr. Peter Dixon and Dr. Geraldine Downey, which is collecting community-based data around the city to answer two questions: how do residents from communities impacted by violence and policing define safety for themselves? And, what makes these grounded definitions more or less relevant for actual public safety policy? Working in three neighborhoods across Manhattan (Harlem), Brooklyn (Bedford-Stuyvesant), and the Bronx (South Bronx), students in this course will work with this community-based data, engaging with municipal decision makers and community members to apply a conflict resolution lens to the rich—and often contradictory—perspectives that city residents bring to the seemingly simple question of what it means to be safe.
This course is scheduled to take place in person, in accordance with campus COVID-19 policies. Students are expected to spend on average, 10 hours per week including class time, group work, readings and other assignments, plus one intensive weekend. Throughout, we will engage with city officials and NYC community members to co-analyze residents’ public safety priorities and co-create policy solutions and resolution strategies.
We would like to offer this course online as well as on campus.
Nonprofit organizations compete for scarce philanthropic and government funding and are expected to account for how these resources are utilized for the greater good. However, understanding how well nonprofit programs and services produce their desired outcomes can be a challenge. This course is designed to provide a broad – yet rigorous – overview of the knowledge and tools available to evaluate the effects of nonprofit and social impact programs and policies.
This course will develop the knowledge and skills necessary for conducting comprehensive and focused health assessments for individuals with emphasis placed on interviewing skills, health histories, and physical and psychosocial findings in the well person. Communication and record keeping skills are developed.
The primary objective of this course is to become familiar with the typical phases of an internal or external consulting project. The course is designed to provide a deep understanding of the typical challenges, opportunities, phases, and methods for conducting a successful consulting assignment for knowledge-based organizations. A typical strategic consulting assignment includes the following phases: organization assessment, sponsor/client relationship, gathering data, diagnosis issues, implementation, and measurement. Drawing on examples from a variety of organizations, this course will focus directly on strategies for building a successful knowledge service or product for organizations or institutions. We will provide knowledge of foundational frameworks and theories and the need for tailored approaches for different clients. Students will get hands-on experience diagnosing and proposing knowledge strategies for improving organizational effectiveness and competitiveness.
Successful consulting, whether internal or external, requires many capabilities and, at heart, is dependent on the client-consultant relationship. Students will be engaged in working on a simulated consulting assignment based on the current organization in which they work. Alternatively, students may discuss with the faculty to be assigned to work with a voluntary organization seeking student input. During the term, each student will complete individual and team assignments that build on the deliverables needed for an actual consulting assignment. By developing expertise in strategic leadership consulting, students will gain credibility, competence, and confidence in their ability to communicate, design, develop, and provide knowledge and change services to an organization and society. During the semester, students will learn strategies for building knowledge services, including the models, methods, processes, and social factors that promote successful change.
This course is designed for students who are or will be working in positions that require internal or external organizational consulting skills or in positions that require managing organizational change initiatives. No prerequisites.
This course is designed to afford students significant opportunity to explore fundamental bioethical issues in a philosophically searching way. For example, it is generally thought that health matters. But then what is health? And how does it matter? What is justice in respect to health-care and the other social determinants of health? Do competing theories of justice (e.g., liberal, libertarian, utilitarian) offer incompatible solutions to the question of healthcare justice? Or can a workable “overlapping consensus” at the public policy level nevertheless be achieved?
Should a healthcare professional be permitted, on grounds of conscience, to refuse to provide a healthcare service to which people are lawfully permitted? Indeed, what should count as “conscience”? In the aftermath of the recent Supreme Court decision concerning abortion, some have argued for a right to conscientiously insist on providing reproductive services that have been legally prohibited. How are we to sort through and resolve this complicated set of issues?
Could a meaningful personal understanding of what it means for someone to have died nevertheless not be suitable as the basis for a legal declaration of death? Why not? Should there be a “conscience clause” option whereby someone can specify in advance the conception of death to be applied in that individual’s own case? Would every possible criterion be available or would certain criteria have to be excluded? Which? Why?
The population in this and many other societies is aging and putting increasingly significant demands on the healthcare delivery system. Should healthcare be rationed according to age? Would it be unfair to young people not to give weight to that factor—lest they lose out on a fair chance to live as long as society’s seniors already have? What is healthcare justice across the generations?
As researchers gain a fuller understanding of the aging process, it may soon be possible to genetically engineer a significant extension (even doubling?) of human life-span. Is this an appropriate objective for healthcare science to be pursuing? Is the point of healthcare to extend human life as far as possible by whatever means? Is aging a kind of “disease” in its own right? Would life so dramatically extended be beneficial or burdensome?
The topics for this course have been selected in view of (i) how fundamental they are to bioethical thinking (e.g., What is health?
Review of the types of strategic risks, such as a flawed strategy, inability to execute the strategy, competitor risk, supply chain risk, governance risk, regulatory risk, M&A risk, international risk, etc. Includes case studies, research, and common mitigation techniques, such as strategic planning practices, management techniques, governance practices, supply-chain management, etc.
In this course, students will develop a working knowledge of the practical application of analysis and models used to make management decisions within an organization and a professional league. Basketball Analytics will explore the use of data and statistics to inform decision making in the National Basketball Association (NBA). Utilizing data made available through the NBA and other publicly available resources, students will learn to use analytics to ask and answer the right questions and provide best practice solutions through critical thinking.
Review of the types of operational risks, such as technology risk (e.g., cyber-security), human resources risk, disasters, etc. Includes case studies, risk analysis frameworks and metrics, and common mitigation techniques, such as insurance, IT mitigation, business continuing planning, etc.