This course covers the basic elements of crisis communication and the procedures for creating crisis communications plans and for reacting to crises when they occur. How best to develop various plans for different critical audiences and understand the most effective strategies for communicating your organization’s message during a crisis is explored. The course examines various types of crises that can occur with corporations and nonprofit organizations and the differences and similarities among them. How to avoid the classic and common pitfalls of crisis communication are addressed, as are ethical issues that arise during crises. Numerous case studies are discussed in class and exercises both in and outside of class are assigned so students gain experience in crisis communication situations.
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.
In an era of growing environmental and social awareness, supply chains have emerged as a powerful lever for driving
sustainability in operations. Supply chain emissions are, on average, 11.4 times higher than operational emissions (1)
making them a critical focal point for impactful change in operations. This course explores the essential role of supply
chains in achieving sustainable outcomes and equips students with the tools and insights needed to transform
conventional practices into innovative, responsible, and efficient systems. This course is part of a broader curriculum
aimed at cultivating leaders who can integrate sustainability into the heart of business strategy. It is designed for
students from diverse professional and academic backgrounds, no prior experience in operations or supply chain
management is required to excel in this course.
Through this interdisciplinary journey, students will gain a robust foundation in supply chain management, learning
to integrate sustainability principles across operations. The course balances analytical skills with creative problem-
solving, preparing students to address real-world challenges. Upon completing this course, students will gain a
comprehensive skillset to analyze, design, and implement sustainable operations solutions in their future careers.
Students will gain a comprehensive understanding of the strategic role of supply chains in modern economies,
including their critical impact in decarbonization efforts. Students will also learn to apply key analytical tools such as
demand forecasting and risk assessment, while mastering strategies for sourcing, supplier management, and logistics
optimization.
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.
Prerequisites: three semesters of Biology or the instructors permission. The course examines current knowledge and potential medical applications of pluripotent stem cells (embryonic stem cells and induced pluripotent stem cells), direct conversions between cell types and adult, tissue-specific stem cells (concentrating mainly on hematopoietic and gut stem cells as leading paradigms). A basic lecture format will be supplemented by presentations and discussions of research papers. Recent reviews and research papers, together with extensive instructor notes, will be used in place of a textbook. SCE and TC students may register for this course, but they must first obtain the written permission of the instructor, by filling out a paper Registration Adjustment Form (Add/Drop form). The form can be downloaded at the URL below, but must be signed by the instructor and returned to the office of the registrar.
http://registrar.columbia.edu/sites/default/files/content/reg-adjustment.pdf
The course introduces practitioners of sustainability management to the data analysis techniques and statistical methods which are indispensable to their work. The class teaches how to build statistical substantiation and to critically evaluate it in the context of sustainability problems. The statistics topics and examples have been chosen for their special relevance to sustainability problems, including applications in environmental monitoring, impact assessment, and econometric analyses of sustainable development. Students are assumed to have had no previous exposure to statistics.
This course demonstrates how to conduct a quantitative analysis of an organization’s work processes and operations, resource utilization, and environmental impact necessary to create a rationale for implementing sustainability initiatives. Statistical topics, including probability and random variables, will be discussed in both theory and in their practical applications for sustainability managers. This course will provide students with the skills to conduct regression analysis, to conduct hypothesis and estimation testing, to design surveys, and to prepare statistics packages. These quantitative skills are necessary for a professional manager responsible for the management of people, finances and operations toward sustainability goals.
In its first few months, the Trump administration has enacted mandates and policies that pose an existential threat to nonprofit organizations, particularly those that serve marginalized groups (i.e., BIPOC, LGBTQ+, immigrants). Anchored on current research on LGBTQ+ organizations, this special topic course explores how nonprofits are resisting the current regime, testing their organizational resiliency, and planning for an uncertain future.
In this seminar, students will examine the unique challenges nonprofits face in times of crisis and the crucial role these organizations have played in sustaining communities during pivotal moments in recent history. Students will delve into organizational and leadership resilience and learn the principles and practice of crisis management. This encompasses identifying risks, developing crisis management plans, communicating effectively, and building coalitions.
An elective of the M.S. Nonprofit Management program, this course is open to graduate level SPS and Columbia students with a focus on nonprofits and/or civil society. Classes will be highly interactive, centered on discussion of course readings, current events, and students’ personal and professional experience. It will culminate with student presentations based on research on an existing nonprofit that has been impacted by the current administration’s
policies.
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).
APPLIED MACHINE LEARNING I
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.
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.
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 will focus on using ceramics as a primary art making machine by breaking out of the constraints wedded to this traditional material. Building on the foundation set in Ceramics1, this course will delve further into the technical and historical aspects of the ceramic process as well as into the conceptual ideas in artmaking.
Students will use a self-directed working process to facilitate the incorporation of ceramic materials into their existing art making while also being allowed room to go in their own conceptual direction. Rigorous group and individual critiques will be held on a regular basis.
Content is a priority in this class, along with the further understanding of ceramic processes and materials. The goal is for the student to be proficient in producing their ideas without the obstruction of technical difficulties.
Lab section corresponding to CLMT 5002 Quantitative Methods for Climate Applications
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
APPLIED MACHINE LEARNING II
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.
Corequisites: STAT GR5204 and GR5205 or the equivalent. 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.
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.
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.
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.
Prerequisites: STAT GR5205 Statistical inference without parametric model assumption. Hypothesis testing using ranks, permutations, and order statistics. Nonparametric analogs of analysis of variance. Non-parametric regression, smoothing and model selection.
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.
Change is a necessary and constant part of any organization. The change may be expected, or it may be in reaction to unanticipated external and/or internal factors. In fact, organizations that do not change do not last.
Change initiatives can be exceedingly complex and disorienting, however. The success of a given changeinitiative often rests on the clarity of vision of an organization’s leaders; an accurate and sensitiveunderstanding of the organization’s culture; the involvement, input and buy-in of multiple internal andexternal stakeholders to the change objectives and process; leaders’ ability to leverage technology tocommunicate and drive change; and an organization’s analytical capabilities to document and measureprogress, and continue to iterate and improve.
In light of these requirements, this course seeks to ask: What is the role of the HCM leader in facilitatingchange within an organization? The aims of this course are not abstract. This course will help studentsdevelop skills to support actual organizations (their own and/or others) through change. Lectures, readings,videos, in-class and asynchronous discussions, and assignments will all focus on the practical application ofchange theory and empirical research to real-world organizational contexts.
This course is an advanced elective within the Master of Science in Human Capital Management program.Prerequisites include “HCMPS5100: Introduction to Human Capital Management,” and “HCMPS5150:Integrated Talent Management Strategies.” Some familiarity with people analytics and digital approaches toHuman Capital Management will also be helpful.
The course offers an in-depth exploration of the foundational principles and skills of conflict coaching. This rigorous curriculum is designed to equip students with the expertise necessary to assist themselves and others in cultivating perspectives, mindsets, and strategies that espouse a constructive and collaborative conflict approach.
Inherent to human experience, conflict has outcomes primarily shaped by one's chosen approach. A confrontational stance often results in hampered communication, obstructionism, and a power struggle. Conversely, a collaborative approach accentuates effective communication, amiability, assistance, trust, and coordinated endeavors. This methodology frames conflicting interests not as adversarial positions but as shared challenges necessitating shared resolution. Central to the ethos of this course is the recognition of conflict as a conduit for growth, its potential for constructive engagement, and the imperative for adaptive and visionary leadership embodying executive presence.
Conflicts typically evoke a spectrum of emotions in individuals, making them one of the most demanding challenges a coach might assist clients with. Such moments of contention serve as a litmus test for what renowned executive coach John Mattone terms the "Inner Core" of an astute leader. Properly navigated, conflicts become avenues for leaders to refine their "Inner Core" and bolster their executive maturity.
This course is specifically designed for graduate students who aim to expand their expertise in navigating and mediating conflicts within the workplace. Additionally, it is well-suited for students seeking to enhance their interpersonal skills, develop a more profound understanding of conflict dynamics, and foster a more collaborative and harmonious work environment.
Prerequisites: STAT GR5205 Survival distributions, types of censored data, estimation for various survival models, nonparametric estimation of survival distributions, the proportional hazard and accelerated lifetime models for regression analysis with failure-time data. Extensive use of the computer.
Prerequisites: STAT GR5204 Introductory course on the design and analysis of sample surveys. How sample surveys are conducted, why the designs are used, how to analyze survey results, and how to derive from first principles the standard results and their generalizations. Examples from public health, social work, opinion polling, and other topics of interest.
Prerequisites: STAT GR5206 or the equivalent. 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.
Prerequisites: Pre-requisite for this course includes working knowledge in Statistics and Probability, data mining, statistical modeling and machine learning. Prior programming experience in R or Python is required. This course will incorporate knowledge and skills covered in a statistical curriculum with topics and projects in data science. Programming will covered using existing tools in R. Computing best practices will be taught using test-driven development, version control, and collaboration. Students finish the class with a portfolio of projects, and deeper understanding of several core statistical/machine-learning algorithms. Short project cycles throughout the semester provide students extensive hands-on experience with various data-driven applications.
Agriculture is highly dependent on stable climate conditions to produce the world’s food with sufficient nutritional quality at an affordable cost. Climate change is threatening the breadbaskets of the world with shifting rainfall, pests, and weather patterns. Farmers face enormous challenges in adapting to this volatility that is affecting their livelihoods and communities locally, and threatens the global food systems stability. Adaptation to these changes has become a high priority for policy makers, corporations, and investors around the world. Climate smart agriculture presents solutions to the existential threat to the global food supply by utilizing a range of tech enabled methods for producing more food with less resources. The challenge is daunting because there is no “one size fits all” solution. Instead, localized solutions that meet the social, environmental, and economic realities of farmers need to be developed, accelerated, and implemented.
This is a topics course in industrial organization intended for MA students. The focus of the class is to familiarize students with the way economists in academic, antitrust regulatory and private sector settings approach research questions related to topics such as conduct, pricing, competition or ownership and control in various market structures (e.g., homogenous product, differentiated product, two-sided, vertical markets). The goal of the course is threefold. For each of the market structures considered:
(i)
familiarize you with the foundational economic theories;
(ii)
provide you with the empirical tools you can apply in the future to conduct your own research; and
(iii)
introduce to you key antitrust issues regulators have been focusing on and approaches used in practice to analyze these issues by antitrust economists.
Provides a global review of ERM requirements of regulators, rating agencies, and shareholders. Addresses three industry sectors: (1) insurance; (2) banking; and (3) corporate.
Once known as the arsenal of Democracy, the birthplace of the automobile assembly line, and the model city of America, 21st Century Detroit was emblematic of deindustrialization, decay, and insolvency. Following the largest municipal bankruptcy in US history, Detroit is now being reframed in both local and national media as a comeback city with opportunity and possibility for all - urban pioneers, global investors, a creative class of new professionals, and suburbanites seeking a return to urban grit.
Despite these narratives, Detroit remains highly segregated - racially, geographically, economically, and socially. While downtown is prospering, neighborhoods are still largely blighted and contaminated with legacy uses that remain unremediated. Over 30,000 houses and other structures have been demolished in the past 8 years, a process that is under-regulated and contributes to both environmental and infrastructure harm. To the extent new investments are improving the condition of housing and infrastructure in some strategic areas, these investments are displacing long term residents who remain at risk of eviction or foreclosure from their homes. Detroit remains one of the poorest big city in America and the poverty that remains is seemingly intractable. At present, only 36% of residents earn a living wage.
Detroit’s present condition is rooted in a protracted history of racist laws, policies, and practices that deny full citizenship to Black Detroiters, undermine Democracy, and position the city as a poor colony within a thriving metropolis. Racism has disfigured the social, physical and economic landscape of Detroit to produce profound levels of neglect, abuse, and exploitation of its residents, resulting in wealth extraction, housing insecurity, healthy food and water scarcity, educational malpractice, and environmental destruction, all within the framework of wealth attraction, tax incentives, subsidized growth and capital accumulation in the greater downtown.
Through this course, we will examine the thesis that sustainability and racism cannot co-exist; that sustainability is rooted in inclusive social wellbeing now and in future generations, whereas racism is rooted in hoarding of power and resources for one dominant group. This hoarding of resources for a favored population impairs preservation for future generations. Furthermore, environmental racism disconnects the consequences of environmental destruction from its beneficiari
The Applied Integrative Experience for Duals (1 credit) is a year-long, pass/fail program requirement that supports the integrative learning goals of students pursuing dual degrees between the MS in Climate and either the MS in Carbon Management (SEAS) or the MS in Architecture and Urban Design (GSAPP). Students engage in cross-school experiences and guided written reflections to deepen their understanding of how their dual programs intersect and support their professional aspirations.
Students are expected to work closely with their respective faculty advisors throughout the year to identify appropriate events and ensure that their integrative experiences and reflections align with their academic and professional goals. Advisor consultation is essential for shaping meaningful engagement during your time at the Climate School.
This course covers programming with applications to finance. The applications may include such topics as yield curve building and calibration, short rate models, Libor market models, Monte Carlo simulation, valuation of financial instruments such as options, swaptions and variance swaps, and risk measurement and management, among others. Students will learn about the underlying theory, learn coding techniques, and get hands-on experience in implementing financial models and systems.
Prerequisites: STAT GR5204 or the equivalent. STAT GR5205 is recommended. 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.
Prerequisites: STAT GR5203 or the equivalent. Basics of continuous-time stochastic processes. Wiener processes. Stochastic integrals. Ito's formula, stochastic calculus. Stochastic exponentials and Girsanov's theorem. Gaussian processes. Stochastic differential equations. Additional topics as time permits.
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.
Prerequisites: STAT GR5264 Available to SSP, SMP. Mathematical theory and probabilistic tools for modeling and analyzing security markets are developed. Pricing options in complete and incomplete markets, equivalent martingale measures, utility maximization, term structure of interest rates.
The global knowledge economy, cross-border market permeability, and worldwide talent mobility have accelerated the rise of multinational and domestic organizations comprised of individuals from many different cultural and linguistic backgrounds. As these trends strengthen, so, too, does the likelihood that the 21st-century worker will spend a significant part of her/his professional career in a multicultural workplace. While such diversity affords great benefits to organizations, their employees and clients, it is often accompanied by a rise in communication misfires and misunderstandings that can undermine individual, team, and organizational performance.