SOCIAL JUSTICE: NARRATIVES OF INEQUITY (

• Department: Narrative Medicine
• 3 points

TIME SERIES ANALYSIS

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.

• Department: Statistics
• S 10:10 a.m.-12:40 p.m.
• Instructor: Franz Rembart
  Info
• 3 points

Climate Technology and Innovation

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.

• Department: Sustainability Management
• R 6:10 p.m.-8 p.m.
• Instructor: Luke C Apicella
  Info
• 3 points

NONPARAMETRIC STATISTICS

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.

• Department: Statistics
• MW 10:10 a.m.-11:25 a.m.
• Instructor: Marco A Avella Medina
  Info
• 3 points

BAYESIAN STATISTICS

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.

• Department: Statistics
• TR 7:40 p.m.-8:55 p.m.
• Instructor: Dobrin Marchev
  Info
• 3 points

CHANGE MANAGEMENT

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.

• Department: Human Capital Management
• M 8:30 p.m.-10 p.m.
• Instructor: Solange Charas
  h-index: 4 Info
• 3 points

Executive Conflict Coaching

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.

• Department: Negotiation & Conflict Resolution
• US 9 a.m.-5 p.m.
• Instructor: Aldo Civico
  Wikipedia Info
• 1.5 points

THE EARTH'S CLIMATE SYSTEM

• Department: Sustainability Management
• T 4:10 p.m.-6 p.m.
• Instructor: Benjamin I Cook
  CULPA: 3 h-index: 56 Info
• 3 points

SURVIVAL ANALYSIS

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.

• Department: Statistics
• TR 2:40 p.m.-3:55 p.m.
• Instructor: Ashley Datta
  Info
• 3 points

SAMPLE SURVEYS

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.

• Department: Statistics
• TR 2:40 p.m.-3:55 p.m.
• Instructor: Rongning Wu
  CULPA: 1 Info
• 3 points

BUSINESS INTELLIGENCE

BUSINESS INTELLIGENCE IN SPRTS

• Department: Sports Management
• M 6:10 p.m.-8 p.m.
• W 6:10 p.m.-8 p.m.
• 3 points

STATISTICAL MACHINE LEARNING

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.

• Department: Statistics
• MW 10:10 a.m.-11:25 a.m.
• Instructor: Genevera Allen
  Info
• 3 points

APPLIED DATA SCIENCE

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.

• Department: Statistics
• W 6:10 p.m.-8:40 p.m.
• R 6:10 p.m.-8:40 p.m.
• Instructor: Alex Pijyan
  Info
• Instructor: Haiyuan Wang
  Info
• 3 points

PURPOSE-DRIVEN COMMUNICATION

• Department: Strategic Communication
• W 5:10 p.m.-7 p.m.
• Instructor: Hayley Berlent
  Info
• 3 points

Smart Agriculture for a Changing Climate

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.

• Department: Sustainability Management
• M 4:10 p.m.-6 p.m.
• Instructor: Henry A Gordon-Smith
  Info
• 3 points

Industrial Organization

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.

• Department: Economics
• W 6:10 p.m.-8 p.m.
• Instructor: Ildiko Magyari
  Info
• 3 points

EXTERNAL STAKEHOLDER REQUIREMENTS

Provides a global review of ERM requirements of regulators, rating agencies, and shareholders. Addresses three industry sectors: (1) insurance; (2) banking; and (3) corporate.

• Department: Enterprise Risk Management
• W 8:10 p.m.-10 p.m.
• T 8:10 p.m.-10 p.m.
• M 6:10 p.m.-8 p.m.
• Instructor: Rich Lauria
  Info
• Instructor: Rajat Baijal
  Info
• Instructor: Chris Lee
  Info
• Instructor: Muriel Rachid Campomizzi
  Info
• Instructor: Kerry Gendron
  Info
• Instructor: Anthony Wong
  Info
• Instructor: Violet Diamant
  Info
• Instructor: Melody Feinberg
  Info
• Instructor: Chris Lee
  Info
• Instructor: Juan Echeverri
  Info
• Instructor: R S Forston
  Info
• 3 points

Building a Sustainable Detroit: A Case

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

• Department: Sustainability Management
• W 6:10 p.m.-8 p.m.
• Instructor: Donna Givens Davidson
  Info
• 3 points

Applied Integrative Seminar for Duals II

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.

• Department: Climate School
• Instructor: Alix Schroder
  Info
• 0.5 points

DATA ANALYSIS AND VISUALIZATION IN SUSTA

DATA ANALYSIS & VIS IN SU

• Department: Sustainability Management
• T 6:10 p.m.-8 p.m.
• Instructor: Gregory G Yetman
  Info
• 3 points

ORGANIZATIONAL STRATEGY AND LEARNING

ORG STRAT AND LEARNING

• Department: Human Capital Management
• M 6:10 p.m.-8 p.m.
• Instructor: Sara Daly-Padron
  Info
• 3 points

PROG FOR QUANT & COMP FINANCE

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.

• Department: Mathematics
• F 6:10 p.m.-7:50 p.m.
• 3 points

STATISTICAL METHODS IN FINANCE

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.

• Department: Statistics
• S 10:10 a.m.-12:40 p.m.
• Instructor: Zhiliang Ying
  CULPA: 1 Wikipedia h-index: 62 Info
• 3 points

STOCHASTC PROCSSES-APPLICTNS I

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.

• Department: Statistics
• MW 4:10 p.m.-5:25 p.m.
• Instructor: Steven Campbell
  Info
• 3 points

VISUAL COMMUNICATION & DESIGN

STRATEGIC VISUAL COMM

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.

• Department: Strategic Communication
• T 12:10 p.m.-2 p.m.
• Instructor: Diego Kolsky
  Info
• 3 points

STOCHASTIC METHODS IN FINANCE

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.

• Department: Statistics
• TR 6:10 p.m.-7:25 p.m.
• Instructor: Graeme Baker
  Info
• 3 points

GLOBAL COMMUNICATION FOR PROFESSIONALS

GLOBAL COMM FOR PROFESSIONALS

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.

• Department: Strategic Communication
• MTWRF 9 a.m.-5 p.m.
• R 10:10 a.m.-noon
• Instructor: Kristine Billmyer
  Info
• 3 points

DIGITAL HR AND THE DIGITAL WORKPLACE

DIGITAL HR & DIGITAL WORK

• Department: Human Capital Management
• W 6:10 p.m.-8 p.m.
• W 8:30 p.m.-10 p.m.
• Instructor: Nabeel Ahmad
  Info
• Instructor: Joshua Bellis
  Info
• 3 points

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 8:10 a.m.-10 a.m.
• W 10:10 a.m.-noon
• Instructor: Laura Milewczik
  Info
• 3 points

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

Today's data scientist needs to have familiarity with data processing and management tools for processing large volumes of data, so-called Big Data. The class introduces the main principles of database management systems (DBMS) and will provide in depth knowledge in accessing data with SQL.  This class will study techniques and systems for ingesting, efficiently processing, and statistically analyzing large data sets. We will touch on modern technologies developed specifically for Big Data, but also focus on the ways cloud service help to store, access, analyze and model data. Upon completion of the course, you should be able to:

 


Utilize database management systems to parse and explore Big Data

Distribute data processing and statistical summary calculations efficiently

Carry out statistical analysis at different scales using local and distributed computing systems

Use Software Engineering principles to create and share standardized Machine Learning (ML) solutions

• 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

Today's data scientist needs to have familiarity with data processing and management tools for processing large volumes of data, so-called Big Data. The class introduces the main principles of database management systems (DBMS) and will provide in depth knowledge in accessing data with SQL.  This class will study techniques and systems for ingesting, efficiently processing, and statistically analyzing large data sets. We will touch on modern technologies developed specifically for Big Data, but also focus on the ways cloud service help to store, access, analyze and model data. Upon completion of the course, you should be able to:

 


Utilize database management systems to parse and explore Big Data

Distribute data processing and statistical summary calculations efficiently

Carry out statistical analysis at different scales using local and distributed computing systems

Use Software Engineering principles to create and share standardized Machine Learning (ML) solutions

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

TOPICS IN MODERN STATISTICS

DESIGN&ANALY/ONLINE EXPRM

Today's data scientist needs to have familiarity with data processing and management tools for processing large volumes of data, so-called Big Data. The class introduces the main principles of database management systems (DBMS) and will provide in depth knowledge in accessing data with SQL.  This class will study techniques and systems for ingesting, efficiently processing, and statistically analyzing large data sets. We will touch on modern technologies developed specifically for Big Data, but also focus on the ways cloud service help to store, access, analyze and model data. Upon completion of the course, you should be able to:

 


Utilize database management systems to parse and explore Big Data

Distribute data processing and statistical summary calculations efficiently

Carry out statistical analysis at different scales using local and distributed computing systems

Use Software Engineering principles to create and share standardized Machine Learning (ML) solutions

• Department: Statistics
• W 6:10 p.m.-8:40 p.m.
• Instructor: Lei Kang
  Info
• 3 points

TOPICS IN MODERN STATISTICS

BAYES REGRESSN MULTILEVEL

Today's data scientist needs to have familiarity with data processing and management tools for processing large volumes of data, so-called Big Data. The class introduces the main principles of database management systems (DBMS) and will provide in depth knowledge in accessing data with SQL.  This class will study techniques and systems for ingesting, efficiently processing, and statistically analyzing large data sets. We will touch on modern technologies developed specifically for Big Data, but also focus on the ways cloud service help to store, access, analyze and model data. Upon completion of the course, you should be able to:

 


Utilize database management systems to parse and explore Big Data

Distribute data processing and statistical summary calculations efficiently

Carry out statistical analysis at different scales using local and distributed computing systems

Use Software Engineering principles to create and share standardized Machine Learning (ML) solutions

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

RESEARCH DESIGN

• Department: Applied Analytics
• T 8:10 a.m.-10 a.m.
• Instructor: Siddhartha Dalal
  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
  Info
• Instructor: Neil Barman
  Info
• 3 points

QUALITATIVE METHODS & RESEARCH

• Department: Narrative Medicine
• M 6:10 p.m.-9 p.m.
• 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

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.
• 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.
• 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
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• 3 points

NARRATIVE ETHICS (CERT)

• Department: Narrative Medicine
• 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
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• 3 points

ETHICAL DECISION MAKING FOR COMMUNICATOR

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

INTRODUCTION TO PHILOSOPHICAL BIOETHICS

INTRO TO PHILOSOPHICAL BI

In contemporary bioethics, we find ourselves grappling with practically important, and at the same time, philosophically fundamental questions such as: When does someone’s life begin and how should it end? What is the proper role of physicians, nurses and other health care providers and what are the rights of their patients? What is a just and fair way to provide access to health-care services and resources? Which potential uses of new genetic and reproductive technologies would represent a legitimate advance in medicine and which would signify the beginning of a humanly degrading "brave new world"? Indeed, in a society committed to protecting a diversity of lifestyles and opinions, how can citizens resolve significant policy controversies such as whether there should be public funding of human embryonic stem cell research, or a legally protected right to physician assistance in ending one’s life?

The aims of this course are to identify the fundamental ethical questions that underlie contemporary biomedical practice; develop skill in analyzing and clarifying key concepts such as autonomy, justice, health and disease; critically assess the healthcare implications of different ethical outlooks; explore how citizens can reasonably address controversial bioethical issues in a mutually respectful and constructive way.

The course meets once a week for an hour and a half. Live-session interaction and post-session discussion forums play a key role as students explore, in a give-and-take spirit, the pros and cons of each position.

This course is designed for medical students, nursing students, and other healthcare professionals, as well as for students at the graduate or advanced undergraduate level in biology, philosophy, political science, public health, law, and related fields.

• Department: Bioethics
• M 3 p.m.-5 p.m.
• Instructor: Arthur Kuflik
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• 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
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• Instructor: Raj Mittal
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• Instructor: Celia Kapsomera
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• Instructor: Carlo Di Florio
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• 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.
• 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
• R 6:10 p.m.-8 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 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
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• 3 points

SPORTS ENTREPRENEURSHIP

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

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
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• Instructor: Kiran Bhujle
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• Instructor: Lisa Broomer
  Info
• Instructor: Penny Cagan
  Info
• 3 points

FUNDRAISING FOR LARGE INSTITUTIONS: EDs

FUND FOR LRGE INST: EDs &

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

NEUROSCIENCE & ETHICS

TBD

• Department: Bioethics
• M 8 p.m.-10 p.m.
• Instructor: Judy S Fine-Edelstein
  Info
• 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.
• Instructor: Joanna Levy
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• 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.
• Instructor: David Weltz
  Info
• 3 points