COMMUNICATION RESEARCH & INSIGHTS

COMM RESEARCH & INSIGHTS

To make informed decisions about communication, we need a clear understanding of our audience and its motivations. We begin by asking the right questions and interpreting the results. This course covers essential market research methods, including quantitative and qualitative techniques. Students gain direct experience in collecting and analyzing data, developing insights and choosing research-driven communication strategies that meet client objectives.

• Department: Strategic Communication
• W 10:10 a.m.-noon
• Instructor: Laura Milewczik
  Info
• Instructor: Jalisha Jennifer
  Info
• Instructor: Myrlene Laroche
  Info
• 3 points

ADVANCED DATA ANALYSIS

Capstone: R&FM Track

Course Description

STAT GR5291 Advanced Data Analysis serves as one of the required capstone experiences for MA students in statistics. This course is project-based and covers advanced topics in traditional data analysis. Students are presented with a mix of theory and application in homework assignments.  The final project  is a major contribution to the final grade and is arguably considered the capstone project for the MA in Statistics Program.

Students will learn a myriad of topics related to data analysis and hypothesis testing, and are responsible for application through statistical packages or manual programming. Topics include, exploratory data analysis & descriptive statistics, review of sampling distribution, point estimation, review of hypothesis testing & confidence interval procedures, non-parametric tests, computational methods (Monte Carlo, bootstrap, permutation tests), categorical data analysis, linear regression, diagnostics & residual analysis, robust regression, model selection, non-linear regression & smoothers, aspects of experimental design (ANOVA, two-way ANOVA, blocking, multiple comparisons, ANCOVA, semi-parametric procedures, random effects models, mixed effects models, nested models, repeated measures), and general linear models (logistic regression, penalized logistic, multinomial regression, link functions).

Also, time permitting the class covers:
survival analysis (hazard function, survival curve), time series analysis (stationarity, ACF/PACF, MA, AR, ARMA, ARIMA, order selection, forecasting).

• Department: Statistics
• F 10:10 a.m.-12:40 p.m.
• Instructor: Gabriel Young
  CULPA: 7 Info
• 3 points

ADVANCED DATA ANALYSIS

Capstone: ASP Track

Course Description

STAT GR5291 Advanced Data Analysis serves as one of the required capstone experiences for MA students in statistics. This course is project-based and covers advanced topics in traditional data analysis. Students are presented with a mix of theory and application in homework assignments.  The final project  is a major contribution to the final grade and is arguably considered the capstone project for the MA in Statistics Program.

Students will learn a myriad of topics related to data analysis and hypothesis testing, and are responsible for application through statistical packages or manual programming. Topics include, exploratory data analysis & descriptive statistics, review of sampling distribution, point estimation, review of hypothesis testing & confidence interval procedures, non-parametric tests, computational methods (Monte Carlo, bootstrap, permutation tests), categorical data analysis, linear regression, diagnostics & residual analysis, robust regression, model selection, non-linear regression & smoothers, aspects of experimental design (ANOVA, two-way ANOVA, blocking, multiple comparisons, ANCOVA, semi-parametric procedures, random effects models, mixed effects models, nested models, repeated measures), and general linear models (logistic regression, penalized logistic, multinomial regression, link functions).

Also, time permitting the class covers:
survival analysis (hazard function, survival curve), time series analysis (stationarity, ACF/PACF, MA, AR, ARMA, ARIMA, order selection, forecasting).

• Department: Statistics
• F 10:10 a.m.-12:40 p.m.
• Instructor: Gabriel Young
  CULPA: 7 Info
• 3 points

ADVANCED DATA ANALYSIS

Hon Capstone: T&M Track

Course Description

STAT GR5291 Advanced Data Analysis serves as one of the required capstone experiences for MA students in statistics. This course is project-based and covers advanced topics in traditional data analysis. Students are presented with a mix of theory and application in homework assignments.  The final project  is a major contribution to the final grade and is arguably considered the capstone project for the MA in Statistics Program.

Students will learn a myriad of topics related to data analysis and hypothesis testing, and are responsible for application through statistical packages or manual programming. Topics include, exploratory data analysis & descriptive statistics, review of sampling distribution, point estimation, review of hypothesis testing & confidence interval procedures, non-parametric tests, computational methods (Monte Carlo, bootstrap, permutation tests), categorical data analysis, linear regression, diagnostics & residual analysis, robust regression, model selection, non-linear regression & smoothers, aspects of experimental design (ANOVA, two-way ANOVA, blocking, multiple comparisons, ANCOVA, semi-parametric procedures, random effects models, mixed effects models, nested models, repeated measures), and general linear models (logistic regression, penalized logistic, multinomial regression, link functions).

Also, time permitting the class covers:
survival analysis (hazard function, survival curve), time series analysis (stationarity, ACF/PACF, MA, AR, ARMA, ARIMA, order selection, forecasting).

• Department: Statistics
• F 10:10 a.m.-12:40 p.m.
• Instructor: Gabriel Young
  CULPA: 7 Info
• 3 points

ADVANCED DATA ANALYSIS

Advanced Data Analysis

Course Description

STAT GR5291 Advanced Data Analysis serves as one of the required capstone experiences for MA students in statistics. This course is project-based and covers advanced topics in traditional data analysis. Students are presented with a mix of theory and application in homework assignments.  The final project  is a major contribution to the final grade and is arguably considered the capstone project for the MA in Statistics Program.

Students will learn a myriad of topics related to data analysis and hypothesis testing, and are responsible for application through statistical packages or manual programming. Topics include, exploratory data analysis & descriptive statistics, review of sampling distribution, point estimation, review of hypothesis testing & confidence interval procedures, non-parametric tests, computational methods (Monte Carlo, bootstrap, permutation tests), categorical data analysis, linear regression, diagnostics & residual analysis, robust regression, model selection, non-linear regression & smoothers, aspects of experimental design (ANOVA, two-way ANOVA, blocking, multiple comparisons, ANCOVA, semi-parametric procedures, random effects models, mixed effects models, nested models, repeated measures), and general linear models (logistic regression, penalized logistic, multinomial regression, link functions).

Also, time permitting the class covers:
survival analysis (hazard function, survival curve), time series analysis (stationarity, ACF/PACF, MA, AR, ARMA, ARIMA, order selection, forecasting).

• Department: Statistics
• F 10:10 a.m.-12:40 p.m.
• Instructor: Gabriel Young
  CULPA: 7 Info
• 3 points

TOPICS IN MODERN STATISTICS

INTERPTBLE MACHN LEARNING

Topics in Modern Statistics will provide MA Statistics students with an opportunity to study a specialized area of statistics in more depth and to meet the educational needs of a rapidly growing field.

• Department: Statistics
• TR 2:40 p.m.-3:55 p.m.
• Instructor: Joyce T Robbins
  CULPA: 5 Info
• 3 points

TOPICS IN MODERN STATISTICS

Generative AI using Large

Topics in Modern Statistics will provide MA Statistics students with an opportunity to study a specialized area of statistics in more depth and to meet the educational needs of a rapidly growing field.

• Department: Statistics
• F 4:10 p.m.-6:40 p.m.
• Instructor: Parijat Dube
  Info
• 3 points

TOPICS IN MODERN STATISTICS

ADVANCED STATISTICAL MODELING

Topics in Modern Statistics will provide MA Statistics students with an opportunity to study a specialized area of statistics in more depth and to meet the educational needs of a rapidly growing field.

• Department: Statistics
• MW 2:40 p.m.-3:55 p.m.
• Instructor: Andrew Gelman
  CULPA: 6 Wikipedia h-index: 112 Info
• 3 points

TOPICS IN MODERN STATISTICS

Stat Aspects of Finance

Topics in Modern Statistics will provide MA Statistics students with an opportunity to study a specialized area of statistics in more depth and to meet the educational needs of a rapidly growing field.

• Department: Statistics
• T 10:10 a.m.-12:40 p.m.
• Instructor: Gabriel Young
  CULPA: 7 Info
• 3 points

TOPICS IN MODERN STATISTICS

APP MACH LEARN COMP VIS

Topics in Modern Statistics will provide MA Statistics students with an opportunity to study a specialized area of statistics in more depth and to meet the educational needs of a rapidly growing field.

• Department: Statistics
• M 1:10 p.m.-3:40 p.m.
• Instructor: Xiaofu He
  h-index: 21 Info
• 3 points

RESEARCH DESIGN

RESEARCH DESIGN ONLINE

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

STRATEGIC COMMUNICATIONS FOR RISK PROFES

STRATEGIC COMM FOR RISK P

Workshop-like course that addresses a variety of communication skills, including listening skills, presentation skills, leadership communications, conflict resolution, management interactions, and professional communication techniques.

• Department: Enterprise Risk Management
• M 6:10 p.m.-8 p.m.
• W 8:10 p.m.-10 p.m.
• Instructor: Harish Dakshina
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• Instructor: Neil Barman
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• 3 points

QUALITATIVE METHODS & RESEARCH

• Department: Narrative Medicine
• M 6:10 p.m.-9 p.m.
• Instructor: Carlos Decena
  Info
• 4 points

SCULPTURE I

• Department: Visual Arts
• F 10 a.m.-4 p.m.
• Instructor: Jon Kessler
  CULPA: 5 Wikipedia Info
• 3 points

INVESTMENT PLANNING

The Investment Planning course explores the essential principles of investing and how to apply them wisely as
wealth advisors. Students will examine how investment wisdom and theory has evolved – from the insights of
Benjamin Graham to Modern Portfolio Theory, the Capital Asset Pricing Model, factor-based investing and more --
and identify how these theories can be utilized as a framework for understanding and using investments of the present and future. Students will calculate and apply mathematical formulas to learn how to manage risk and return in investment portfolios. This course will compare and contrast each of the major asset classes, ranging from cash and near-cash investments to public and private equity, debt and alternative investments. Students will learn how to apply investment skills to deliver and demonstrate value to clients, net of fees and adjusted risk. In addition, this course will emphasize the parallel development of investment knowledge and communication and counseling skills to conduct investment relationships with clients effectively.

• Department: Wealth Management
• Instructor: Stephen Bodurtha
  Info
• 3 points

POETRY WORKSHOP

• Department: Writing
• T 5 p.m.-8 p.m.
• M 10 a.m.-1 p.m.
• W 9:30 a.m.-12:30 p.m.
• Instructor: Alan Gilbert
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• Instructor: Lynn Melnick
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• Instructor: Deborah Paredez
  CULPA: 3 Wikipedia Info
• 6 points

Foundations of Valuations

Foundations of valuation is an introductory finance course required for all MBA students. It is designed to cover those areas of finance that are important to all managers, whether they specialize in finance or not. At the end of the course, you will be familiar with the most common financial instruments (stocks, bonds, options) and the methods to value them. More specifically, we will cover the following topics:

1. General framework for valuation (present value formula)
2. Bond and bond valuation (spot rates, yield to maturity, duration, convexity)
3. Stocks (stock valuation, dividend growth model)
4. Basic concepts of risk and return and the CAPM
5. Options (Black-Scholes formula)

The course will be a mix of lectures and cases. Students are expected to come prepared to class since the course relies on several in-class exercises students will solve in excel.

• Department: Finance
• F 12:30 p.m.-3:30 p.m.
• F 3:45 p.m.-6:45 p.m.
• Instructor: Andrew Hertzberg
  h-index: 7 Info
• 1.5 points

INTERNATIONAL ENVIRONMENTAL LAW

INTL ENVIRONMENTAL LAW

International Environmental Law is a fascinating field that allows students to consider some of the most important questions of the 21st century – questions that have profound ramifications for the quality of life for our generation as well as future generations. Global environmental problems are real and urgent. Their resolution requires creative and responsible thought and action from many different disciplines. 

 

Sustainability practitioners must understand global environmental issues and their effects on what they are charged to do. At one level, this course will consider the massive challenge of the 21st century:  how to alleviate poverty on a global scale and maintain a high quality of life while staying within the bounds of an ecologically limited and fragile biosphere -- the essence of sustainable development.  From a more practical perspective, the course will provide students with an understanding of international environmental policy design and the resulting body of law in order to strengthen their ability to understand, interpret and react to future developments in the sustainability management arena.

 

After grounding in the history and foundational concepts of international environmental law and governance, students will explore competing policy shapers and the relevant law in the areas of stratospheric ozone protection, climate change, chemicals and waste management, and biodiversity. The course satisfies the public policy course requirement for the M.S. in Sustainability Management program.

• Department: Sustainability Management
• W 4:10 p.m.-6 p.m.
• Instructor: Eran Sthoeger
  Info
• 3 points

SCULPTURE II

• Department: Visual Arts
• T 10 a.m.-4 p.m.
• Instructor: Sable Smith
  Wikipedia Info
• 3 points

Corporate Finance (Half-Term)

Corporate finance is an introductory course required for all MBA students. It is designed to cover those areas of finance that are important to all managers, whether they specialize in finance or not. At the end of the course, you will be able to value a firm. To reach this goal, the course covers the following topics:

1. Introduction to frameworks for firm valuation (enterprise DCF and multiples)
2. Multiple valuations
3. Free cash flows (definition, projections)
4. Residual value
5. Weighted average cost of capital
6. Optimal capital structure

The course will consist of approximately one‐half lecture and one‐half in‐class case discussions, for which students should prepare carefully. The course aims to provide students with an understanding of sound theoretical principles of finance and the practical environment in which financial decisions are made.

• Department: Finance
• FSS 12:30 p.m.-3:30 p.m.
• F 8:30 a.m.-1 p.m.
• Instructor: Andrew Hertzberg
  h-index: 7 Info
• 1.5 points

SCULPTURE III

• Department: Visual Arts
• T 10 a.m.-4 p.m.
• Instructor: Sable Smith
  Wikipedia Info
• 3 points

DIGITAL WORKPLACE AND DIGITAL TRANSFORMA

DIGITAL WRKPLC & DGTL TRA

How do organizational leaders invest in digital technologies and capabilities to catalyze digital transformation? Moreover, how do corporations and institutions create an effective portfolio of digital investments that are aligned — continuously over time — with the organization’s mission and strategy? This course provides an introduction to digital transformation, and the modern (digital) “place” of work, such as intranets, search appliances, analytic dashboards, enterprise social media, mixed reality, and content management. Feeding the digital workplace are “sources of record,” including Enterprise Resource Planning (ERP), HR systems, Customer Relationship Management (CRM), IoT sensors, and digital marketing. Finally, we look at likely future scenarios for work and how organizations can prepare for digital transformation and beyond.

• Department: Information & Knowledge Strat
• W 6:10 p.m.-8 p.m.
• Instructor: Kate G Bruce
  Info
• Instructor: Khuong Le-Nguyen
  Info
• 3 points

BUSINESS ANALYTICS

OVERVIEW: Business analytics (BA), in essence, is the discipline of using data analysis - ranging from simple descriptive statistics to advanced, AI-based predictions - to illuminate all quantitative aspects relevant to a specific organization, from its own performance, to the behavior of its customers, and challenges from competitors. This course covers the entire value chain of a BA process, including formulating the question, collecting and managing the relevant data, analyzing said data to answer the question, and finally effectively communicating the results (e.g., data visualization) to stakeholders. While the course teaches some hands-on data analysis/statistics (e.g., database structures, conditional averages, correlations, confidence intervals), the emphasis of the course is on educating users and managers of BA, and as such includes stakeholder engagement and implementation planning.

CONTENT: Following an introduction to the history of BA, weekly lectures and associated assignments (some spreadsheet-based, others in essay format) teach all above elements of the BA value chain one by one. Accompanying readings cover academic foundations and practitioner commentary, from Alan Turing's work (1912-1952) to latest advances in quantum computing. A short individual presentation and a group white paper allow students to combine and hone the various acquired skills in an end-end application. As an overarching objective, upon successful completion of the course, students will be able to devise and "pitch" an innovate BA process to an organization, including strategic recommendations on its business value and implementation.

LOGISTICS: Required course for IKNS students, open to all Columbia University graduate students; no prerequisites other than beginner's familiarity with spreadsheet software and simple statistics (e.g., average, error margin). Online course meets once a week (live via zoom) for the duration of the semester.

• Department: Information & Knowledge Strat
• W 4:10 p.m.-6 p.m.
• T 8:10 p.m.-10 p.m.
• Instructor: Christoph J Meinrenken
  h-index: 15 Info
• Instructor: Kathy Koontz
  Info
• 3 points

NARRATIVE ETHICS (CERT)

• Department: Narrative Medicine
• Instructor: Elizabeth Lanphier
  Info
• 3 points

SQL

SQL & RELATIONAL DB

• Department: Applied Analytics
• T 8:10 p.m.-10 p.m.
• Instructor: Day Yi
  Info
• 3 points

SQL

SQL & RELATIONAL DB ONLINE

• Department: Applied Analytics
• W 8:10 p.m.-10 p.m.
• Instructor: Nikolaos Machairas
  Info
• 3 points

ETHICAL DECISION MAKING FOR COMMUNICATOR

• Department: Strategic Communication
• S 8:30 a.m.-12:30 p.m.
• Instructor: Skye Cleary
  Info
• Instructor: Kevin Visconti
  Info
• 3 points

STRATEGIC RISK MANAGEMENT

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.

• Department: Enterprise Risk Management
• W 6:10 p.m.-8 p.m.
• R 6:10 p.m.-8 p.m.
• T 6:10 p.m.-8 p.m.
• R 8:10 p.m.-10 p.m.
• Instructor: H.S. Bob Kostakopoulos
  Info
• Instructor: Raj Mittal
  Info
• Instructor: Celia Kapsomera
  Info
• Instructor: Carlo Di Florio
  Info
• 3 points

FINANCIAL RISK MGMT & REGULATION

Prerequisites: student expected to be mathematically mature and familiar with probability and statistics, arbitrage pricing theory, and stochastic processes. The course will introduce the notions of financial risk management, review the structure of the markets and the contracts traded, introduce risk measures such as VaR, PFE and EE, overview regulation of financial markets, and study a number of risk management failures. After successfully completing the course, the student will understand the basics of computing parametric VaR, historical VaR, Monte Carlo VaR, cedit exposures and CVA and the issues and computations associated with managing market risk and credit risk. The student will be familiar with the different categories of financial risk, current regulatory practices, and the events of financial crises, especially the most recent one.

• Department: Mathematics
• W 7:40 p.m.-9:30 p.m.
• Instructor: Harvey Stein
  h-index: None Info
• 3 points

NONPROFIT FINANCIAL MANAGEMENT

NONPROFIT FINANCIAL MGMT

This course provides a comprehensive set of financial management tools for nonprofit professionals, including managers and staff, whether they oversee financial statements and reporting or need to translate financial statements and reporting across stakeholders. This course emphasizes the requirements for nonprofits in recording and budgeting the financials to support the organization’s mission. Additionally, the course will provide students with the ability to analyze financial statements and answer financial questions typically asked by stakeholders such as the governing board, donors, the public, beneficiaries, media, and regulators. Finally, the course will identify the risks and opportunities found in an organization's financial information to increase the public's confidence in and understanding of the organization's mission and operations.

• Department: Non Profit Management
• W 6:10 p.m.-8 p.m.
• T 6:30 p.m.-8 p.m.
• Instructor: Erwin Vincent S de Leon
  Info
• 3 points

SUSTAINABLE INVESTING & ECONOMIC GROWTH

• Department: Sustainability Management
• T 4:10 p.m.-6 p.m.
• Instructor: Satyajit Bose
  CULPA: 4 Info
• 3 points

LAW & BIOETHICS

This course introduces students to selected legal and policy texts that have addressed issues in bioethics and shaped their development. Students will explore and contrast legal reasoning and bioethical analysis, often of the same issues. By the end of the course, students will understand the legal or regulatory status of selected issues and have begun to independently navigate major legal, regulatory, and policy texts. Individual sessions will be focused around particular issues or questions that have been addressed by (usually) American courts and/or in legislation, regulation or policy, and that have been the subject of scholarship and debate within bioethics.

The course begins with a theoretical look at the relationship between law and ethics, and includes a brief introduction to legal decision-making and policy development. We then survey a range of bioethics issues that have been addressed by the courts and/or in legislation, regulation, or significant policy documents, contrasting and comparing legal argument and reasoning with arguments utilized in the bioethics literature.

• Department: Bioethics
• T 9:10 a.m.-11 a.m.
• W 5:30 p.m.-7:30 p.m.
• Instructor: David N Hoffman
  h-index: 2 Info
• 3 points

DIGITAL COMMUNICATION STRATEGY

As digital media increasingly drives the field of strategic communication, leading successful communication efforts also require a platform specific, evidence-based strategic approach. Leaders must know how to use a broad and rapidly changing mix of digital media platforms and tools to connect their message with the right audience. To that end, this course covers major topics in digital media and communication, such as content strategy, digital experience, channel planning, online reputation management, programmatic marketing, audience targeting, artificial intelligence and more. Through in-class lectures, discussion, case studies, guest speakers, group projects and individual writing assignments, students in this course will be introduced to strategic decision-making and communications planning for social media, mobile, digital advertising, search, email, digital out-of-home and interactive media (video, radio, podcasts). Students will also gain an in-depth understanding of how to integrate digital strategies and tactics with traditional communication efforts.

• Department: Strategic Communication
• R 12:10 p.m.-2 p.m.
• Instructor: Lilian Ore
  Info
• 3 points

Special Topics: Consulting on Organizati

Conflicts in organizations can be productive or destructive, depending on the nature, frequency and intensity of the conflicts and how they are managed. When handled well, they can spark dialogue and innovation. Too often, however, they are not managed well and can have adverse effects on the people directly and indirectly involved, and the organization itself. They can cause absenteeism and lack of commitment, which can reduce productivity and increase the costs of doing business. They create unpleasant working environments and, when prolonged, can cause stress resulting in emotional and physical illness. There are different reasons for these conflicts, ranging from skirmishes within teams, to insufficient communication, to lack of enforced accountability measures, and indecisive leadership. The direct impact is to those involved in the conflict, while the indirect impact is more widely felt. By embracing a comprehensive conflict consulting framework, organizations can address disputes constructively, enhance communication, improve team collaboration, and create a more productive and harmonious work environment. 

 

This course is designed for those who would like to consult to organizations to address their internal conflict dynamics. It offers a structured process for engaging clients and partnering with them to effectively address and resolve conflicts within an organization. This course fits in well within the NECR programs’ course offerings, focused on skill building, systems, and for those interested in organizational dynamics. It covers a systemic approach to engaging in addressing organizational conflict by focusing on the client-consultant relationship. It draws on conflict analysis tools and conflict resolution methodologies from within the NECR program and the field, which also works to inform the credibility of the consultant. 

This course is an elective and will meet one weekend, March 28th and 29th, a full Saturday and Sunday, from 9:00-5:00. There will be a pre-work module to lay the foundation for the course, to allow the two days in person, on campus, to be spent engaged in hands-on activities. This course is open to NECR students. Students from other programs with some organizational experience and focus, and some knowledge of conflict resolution, can be permitted to join upon Instructor approval. It is preferred that NECR 6050 and NECR 5101 be completed before taking this course.

• Department: Negotiation & Conflict Resolution
• SU 9 a.m.-5 p.m.
• Instructor: Beth Fisher-Yoshida
  Info
• 1.5 points

Environmental Investigation and Sustaina

ENV INVESTIGATION &REMEDI

Environmental Investigation and Sustainable Remediation covers the major steps in the investigation, assessment and remediation of contaminated sites. The course will introduce the student to the multidisciplinary aspects of environmental remediation including sustainability considerations, an important background for any environmental career, such as an environmental consultant, a corporate remediation manager or a government regulator. Management and remediation of contaminated sites is an important consideration in sustainable regional development, since failure to control contamination usually yields an ever-increasing area of impact, with greater environmental and societal costs. Using US EPA Superfund guidance as a framework, the course will explore the major steps in identifying a site, establishing the degree of contamination, identifying the likely ecological and human receptors, and selecting and implementing a remedial action. Sustainable remediation in particular has received increased emphasis by the EPA and is now a required component of remedy selection. The Superfund process has been extensively developed through more than 30 years of legislature and agency guidance, and now provides a robust approach for pollution assessment and remediation. Contaminated sites typically involve a broad spectrum of contaminants across at least two media, including soils, sediments, groundwater, surface water, and air. This course examines the main steps involved in environmental investigation and remediation primarily from a technical perspective, although legal aspects will be incorporated at the major decision points in the process. In particular, the course will focus on the main environmental sampling and analytical techniques needed to conduct a remedial investigation, and cover some of the main remedial engineering considerations for the successful selection and implementation of a sustainable and resilient remedy. Students will be assigned one of several completed Superfund sites to track the application of the Superfund process to a real-world example as the class proceeds, providing a regular link between theory and application.

• Department: Sustainability Science
• W 4:10 p.m.-6 p.m.
• Instructor: Edward A Garvey
  Info
• 3 points

Environmental Investigation and Sustaina

ENV INVESTIGATION &REMEDI

Environmental Investigation and Sustainable Remediation covers the major steps in the investigation, assessment and remediation of contaminated sites. The course will introduce the student to the multidisciplinary aspects of environmental remediation including sustainability considerations, an important background for any environmental career, such as an environmental consultant, a corporate remediation manager or a government regulator. Management and remediation of contaminated sites is an important consideration in sustainable regional development, since failure to control contamination usually yields an ever-increasing area of impact, with greater environmental and societal costs. Using US EPA Superfund guidance as a framework, the course will explore the major steps in identifying a site, establishing the degree of contamination, identifying the likely ecological and human receptors, and selecting and implementing a remedial action. Sustainable remediation in particular has received increased emphasis by the EPA and is now a required component of remedy selection. The Superfund process has been extensively developed through more than 30 years of legislature and agency guidance, and now provides a robust approach for pollution assessment and remediation. Contaminated sites typically involve a broad spectrum of contaminants across at least two media, including soils, sediments, groundwater, surface water, and air. This course examines the main steps involved in environmental investigation and remediation primarily from a technical perspective, although legal aspects will be incorporated at the major decision points in the process. In particular, the course will focus on the main environmental sampling and analytical techniques needed to conduct a remedial investigation, and cover some of the main remedial engineering considerations for the successful selection and implementation of a sustainable and resilient remedy. Students will be assigned one of several completed Superfund sites to track the application of the Superfund process to a real-world example as the class proceeds, providing a regular link between theory and application.

• Department: Auditing
• W 4:10 p.m.-6 p.m.
• Instructor: Edward A Garvey
  Info
• 0 points

SPORTS ENTREPRENEURSHIP

• Department: Sports Management
• T 6:10 p.m.-8 p.m.
• Instructor: Grant J Son
  Info
• 3 points

DEI in Nonprofits: Leading Inclusive Org

Apart from its justice and equity imperative, Diversity, Equity, and Inclusion (DEI) has become an operational imperative as organizations become increasingly diverse. This course aims to equip students with critical faculties and practical tools to be informed and ethical practitioners of DEI in the charitable sector. This course prepares students to manage and lead the practice of DEI in core operational functions, as directors of DEI offices/initiatives or as DEI champions within their organizations. It will equip students with an understanding of the advantages and challenges of leading diverse teams and will provide the knowledge, critical analysis, and practical tools required to lead inclusive organizations. It provides a framework and strategic foundation for driving an organization through the stages of gaining awareness about DEI, practicing DEI, and amplifying the work of equity and inclusion beyond the workplace.

• Department: Non Profit Management
• R 6:30 p.m.-8 p.m.
• Instructor: Erwin Vincent S de Leon
  Info
• 3 points

DIGITAL PRODUCT INNOVATION & ENTREPRENEU

DGTL PROD INNOV & ENTRPRN

Digital Product Innovation and Entrepreneurship aims to provide students with the knowledge and expertise in innovation and new product development required to create, test, and launch a new digital product. In this course, students will undertake the following: perform a competitive analysis, investigate novel knowledge-based digital products, gather user requirements, validate the feasibility of proposed products, devise a go-to-market strategy, construct a financial plan, develop a high-fidelity digital product prototype, and pitch their business idea to a panel of venture capitalists. Students can expect to engage in a fast-paced, rigorously hands-on curriculum focused on developing a pre-revenue business.

The exponential increase in data and information, coupled with the combination of increasingly potent analytics and natural language processing platforms, AI, and LLMs, provides entrepreneurs with tremendous opportunities to bring innovative, customer-focused digital products to market. While there are no direct paths to bring a new product idea to market successfully, the application of the lean startup methodology provides a well-tested path from idea to profit.

• Department: Information & Knowledge Strat
• W 8:10 p.m.-10 p.m.
• Instructor: Ralph Poole
  h-index: 0 Info
• 3 points

REPRODUCTIVE ETHICS

• Department: Bioethics
• R 7:30 p.m.-9:30 p.m.
• Instructor: Arthur Kuflik
  Info
• 3 points

OPERATIONAL RISK MANAGEMENT

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.

• Department: Enterprise Risk Management
• R 6:10 p.m.-8 p.m.
• T 6:10 p.m.-8 p.m.
• M 8:10 p.m.-10 p.m.
• W 8:10 p.m.-10 p.m.
• Instructor: Rossano Rossi
  Info
• Instructor: Kiran Bhujle
  Info
• Instructor: Lisa Broomer
  Info
• Instructor: Penny Cagan
  Info
• 3 points

FUNDRAISING FOR LARGE INSTITUTIONS: EDs

FUND FOR LRGE INST: EDs &

This course’s goal is to enable students to understand the specific challenges and particularities to medical and educational institutions’ fundraising, administration and community engagement. The successful student will complete the course with an extensive understanding of fundraising strategy, revenue streams, governance, organizational structure, leadership models, public policy, trends in the industry, and fundraising best practices as they relate to medical and educational organizations (“Eds and Meds”).

• Department: Non Profit Management
• R 6:10 p.m.-8 p.m.
• Instructor: Patrick O'Connell
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• 3 points

NEUROSCIENCE & ETHICS

TBD

• Department: Bioethics
• M 8 p.m.-10 p.m.
• Instructor: Judy S Fine-Edelstein
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• 3 points

INTRO TO QUANTITATIVE RISK MANAGEMENT

INTRO TO QUANT RISK MGMT

Students without a strong math background and experience with Excel will require significant additional time and effort to achieve the learning objectives and work through the course assignments.

This course builds a foundation in the mathematics and statistics of risk management. Students are empowered to understand the output of quantitative analysts and to do their own analytics. Concepts are presented in Excel and students will have the opportunity to practice those concepts in Excel, R or Python.

This course is a required prerequisite for registering for the following courses: Coding for Risk Management, Financial Risk Management, Quantitative Risk Management, Credit Risk Management, Market Risk Management, Credit Risk Analytics, Applied Coding for Risk Management, Derivatives Risk Management, Model Risk Management, ERM Modeling, and Machine Learning for Risk Management.

• Department: Enterprise Risk Management
• R 8:10 p.m.-10 p.m.
• M 8:10 p.m.-10 p.m.
• Instructor: Oleksandra V Lyulko
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• Instructor: Witold Czubala
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• 3 points

FUNDAMENTALS OF SPORTS ANALYTICS

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

CODING FOR RISK MANAGEMENT

Equips students with the ability to adopt the programming culture typically present in the ERM/risk areas of most financial organizations. By studying Python, SQL, R, git, and AWS, students gain exposure to different syntaxes. Students apply these skills by coding up market risk and credit risk models. Students also gain familiarity with working in the cloud.

• Department: Enterprise Risk Management
• M 6:10 p.m.-8 p.m.
• M 8:10 p.m.-10 p.m.
• Instructor: David Weltz
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• Instructor: David J Romoff
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• 3 points

FINANCIAL RISK MANAGEMENT

A survey of market, credit, liquidity, and systemic risk. Includes case studies, risk quantification methods, and common mitigation techniques using portfolio management, hedging, and derivatives. Also addresses traditional risk management practices at banking institutions.

• Department: Enterprise Risk Management
• R 8:10 p.m.-10 p.m.
• T 8:10 p.m.-10 p.m.
• W 6:10 p.m.-8 p.m.
• M 6:10 p.m.-8 p.m.
• Instructor: David J Romoff
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• Instructor: Zaur Nurtaza
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• Instructor: Navin Sharma
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• Instructor: Justin Hon
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• 3 points

MATH MTHDS-FIN PRICE ANALYSIS

Course covers modern statistical and physical methods of analysis and prediction of financial price data. Methods from statistics, physics and econometrics will be presented with the goal to create and analyze different quantitative investment models.

• Department: Mathematics
• S 7 p.m.-9:20 p.m.
• Instructor: Alexei Chekhlov
  CULPA: 3 h-index: 10 Info
• 3 points

EMBODIED BORDERLANDS

• Department: Narrative Medicine
• T 10:10 a.m.-noon
• Instructor: Sayantani T Dasgupta
  CULPA: 2 Info
• 3 points

SPORT ACCOUNTING & FINANCE

• Department: Sports Management
• T 6:10 p.m.-8 p.m.
• Instructor: Destinee Coles
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• 3 points

Agroecology - A Natural Climate Solution

Agroecology A Natural Cli

Natural climate solutions (NCS) refer to actions aimed at protecting, better managing, and restoring nature to achieve climate goals. Adopting sustainable, climate-smart agricultural practices following agroecology principles provides a cost-effective NCS pathway to mitigate climate change, while also ensuring food security and environmental sustainability. This course will introduce the principles of agroecology, the key concepts of carbon and nitrogen dynamics, as well as the commonly adopted agroecological practices across various agricultural landscapes, including croplands, grasslands, and agroforestry systems. A combination of lectures, discussions, and field activities will be utilized to demonstrate how agroecological practices can be monitored in terms of their influence on ecosystem services.

This course will prepare students to apply principles of sustainability science to improved soil and agricultural management, addressing the growing need for better adoption of land based NCS. This course will also delve into the technological aspects of NCS monitoring that will help working professionals in conservation, environmental, and sustainable business organizations develop the necessary skills to evaluate the outcomes of sustainable land management practices to inform management decisions, policy making, and incentive-based programs. This elective course aims to connect scientific methods with decision-making processes to prepare students to be leaders in sustainability and make impacts on both local and large-scale climate issues.

• Department: Sustainability Science
• R 4:10 p.m.-6 p.m.
• Instructor: Yushu Xia
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• 3 points

Disability and Illness Narratives (CERT)

Disability Illness Narrat

This course examines questions such as: What does the telling and reading of narratives do for the ill or disabled individual? How can clinicians effectively elicit, interpret, and act upon such narratives? Who owns a story, and what is the role of co-authorship, power and witnessing in story-telling and story-listening? Whose voice do we hear? What are the roles of power and hierarchy in story-telling and listening? What is the impact of familial, cultural, social, institutional, political contexts on the individual story? And finally, how can personal stories be translated to political advocacy and action? Texts assigned weekly will be broadly interdisciplinary – drawing from memoir, poetry, essays, fiction, feature and documentary films, narrative theory, and disability studies, exploring the relationship between disability/illness experience and narrative. This elective course is open to all students in the Narrative Medicine CPA program. Students should be prepared to engage with each other and with the instructor and to offer their questions, comments, insights, and analysis.

This is an essential, practically applied element of narrative medicine study and it is exemplary as a way to illustrate the impact of narrative study in shaping experience, opening awareness, and highlighting the need for change and new stories. A narrative medicine course focused on disability and illness narratives is an important aspect of narrative medicine study. Exploring narratives presented in a variety of formats by using narrative medicine methods can encourage deeper perspective-taking and promote activism for underrepresented voices.

Disability and Illness Narratives: Storytelling For Awareness and Activism
is an elective course in the Narrative Medicine CPA program. In addition, this course is open to cross-registrants in other programs who demonstrate some understanding of narrative medicine and/or participate in the online asynchronous narrative medicine orientation course before the semester begins. Narrative Medicine CPA students are required to have completed, or be simultaneously enrolled in the course,
Narrative Medicine Methods: Close Reading and Writing
, course number K5120, and have completed the required program online asynchronous orientation course. CPA courses are all 10 weeks/modules long, and they are online and asynchronous, which means there are no meeting times. Each module represents one week of the course. All modules begin on a Tuesday and end on Monday of th

• Department: Narrative Medicine
• Instructor: Joseph H Eveld
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• 3 points

INSURANCE RISK MANAGEMENT

Review of types of insurance risk, such as pricing risk, underwriting risk, reserving risk, etc. Includes case studies, risk quantification methods (e.g., market-consistent economic capital models, dynamic financial analysis (DFA) models, catastrophe models, etc.), and common mitigation techniques, such as asset-liability management (ALM), reinsurance, etc. Also addresses traditional risk management at insurance companies and ERM actuarial standards of practice (ASOPs).

• Department: Enterprise Risk Management
• W 8:10 p.m.-10 p.m.
• Instructor: Ding Dai
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• 3 points

MULTI-ASSET PORTFOLIO MGMT

The course will cover practical issues such as: how to select an investment universe and instruments, derive long term risk/return forecasts, create tactical models, construct and implement an efficient portfolio,to take into account constraints and transaction costs, measure and manage portfolio risk, and analyze the performance of the total portfolio.

• Department: Mathematics
• MW 6:10 p.m.-7:25 p.m.
• 3 points

CREDIT RISK MANAGEMENT

Credit Risk Management requires business acumen, the monitoring of internal and external data, disciplined execution, and organizational intelligence. A solid understanding of this enables a credit risk manager to help organizations achieve their objectives. Through readings, case studies, and modeling projects, students learn how risk managers decide on credit risk management strategy applied throughout the client lifecycle.

• Department: Enterprise Risk Management
• T 8:10 p.m.-10 p.m.
• M 8:10 p.m.-10 p.m.
• Instructor: Christakis Droussiotis
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• Instructor: Weijun Weng
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• 3 points

CAPSTONE

Capstone projects afford a group of students the opportunity to undertake complex, real-world, client-based projects for nonprofit organizations, supervised by a Nonprofit Management program faculty member. Through the semester-long capstone project, students will experience the process of organizational assimilation and integration as they tackle a discrete management project of long or short-term benefit to the client organization. The larger theoretical issues that affect nonprofit managers and their relationships with other stakeholders, both internal and external, will also be discussed within the context of this project-based course.

• Department: Non Profit Management
• T 6:30 p.m.-8 p.m.
• Instructor: Basil A Jr Smikle
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• 3 points

SPORTS REVENUES STRATEGIES & ANALYSIS

Digital, social, and mobile media continue to heavily impact every aspect of sports business, often in profound and unanticipated ways, particularly in managing and optimizing revenue streams. All revenue line items are fully intertwined and integrated with each other, media, sponsorship, ticketing, hospitality, concessions and licensing, etc. Students of this course will learn to analyze and optimize the ecosystem of sports business including content rights, ticketing, sponsorship, merchandising, marketing, etc., as well as make business analytics decisions by leveraging business analytics software to run scenario analysis.

• Department: Sports Management
• R 6:10 p.m.-8 p.m.
• Instructor: Ishwara Glassman Chrein
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• 3 points

MA Mentored Research

MA MENTORED RESEARCH

This course is intended to provide a mechanism to MA students in Statistics who undertake on-campus project work or research. The course may be signed up with a faculty member from the Department of Statistics for academic credit. Students seeking to enroll in the course should identify an on-campus project and a congenial faculty member whose research is appealing to them, and who are able to serve as their mentor. Students should then submit an application to enroll in this course, which will be reviewed and approved by the Faculty Director of the MA in Statistics program.

• Department: Statistics
• Instructor: Demissie Alemayehu
  h-index: 14 Info
• 0-3 points

Statistical Fieldwork

Prerequisites: GR5203; GR5204 &GR5205 and at least 4 approved electives This course is an elective course for students in the M.A. in Statistics program that counts towards the degree requirements. To receive a grade and academic credits for this course, students are expected to engage in approved off-campus internships that can be counted as an elective. Statistical Fieldwork should provide students an opportunity to apply their statistical skills and gain practical knowledge on how statistics can be applied to solve real-world challenges.

• Department: Statistics
• Instructor: Demissie Alemayehu
  h-index: 14 Info
• 1 points

FUNDAMENTALS OF DATA ENGINEERING

FUNDAMENTALS OF DATA ENGINEERING

• Department: Applied Analytics
• R 6:10 p.m.-8 p.m.
• Instructor: Amreeta Choudhury
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• 3 points

FUNDAMENTALS OF DATA ENGINEERING

FUND OF DATA ENG ONLINE

FUNDAMENTALS OF DATA ENGINEERING

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

CLINICAL ETHICS

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

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

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

• Department: Bioethics
• T 2:10 p.m.-4 p.m.
• R 9:30 a.m.-11:30 a.m.
• W 8 p.m.-10 p.m.
• Instructor: Barbra Rothschild
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• 3 points

RESEARCH SEMINAR IN HIST

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

• Department: French
• Instructor: Barry G Bergdoll
  CULPA: 1 Info
• 3 points

OPERATIONS: BACKBONE OF THE COMPANY

OPERATIONS: BACKBONE OF C

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

TAX PLANNING

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

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

MARKET RISK MANAGEMENT

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

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

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

PRACTICAL PRODUCTION II

• Department: Film
• F 9 a.m.-11:15 a.m.
• F 11:15 a.m.-1:30 p.m.
• F 1:30 p.m.-3:45 p.m.
• Instructor: Maureen A Ryan
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• 1.5 points

LEADERSHIP IN SPORTS MANAGEMENT

LDRSHP & PERS MGMT IN SPR

TBA

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

LEADERSHIP IN SPORTS MANAGEMENT

LDRSHP & PERS MGMT IN SPR

TBA

• Department: Sports Management
• T 4:10 p.m.-6 p.m.
• Instructor: Jeffrion L Aubry
  Info
• 3 points

LEADERSHIP IN SPORTS MANAGEMENT

TBA

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