AI/ML for Leaders
Generative AI represents a pivotal technological evolution with profound implications for the global economy and modern society. This course delves into the decades-long development of AI and machine learning, emphasizing its emergence as a critical economic and strategic force. As we explore this technology, we will assess its potential to revolutionize industries, enhance capabilities, and introduce complex challenges related to security, identity, and ethical considerations.
In this dynamic landscape, both incumbent businesses and governmental bodies face the urgent need to adapt to this disruption and the transformative changes it heralds. This course seeks to unpack the catalysts of this technological surge, its foundational principles, and the critical knowledge required for modern leadership in the AI era.
- Department: Technology Management
- T 6:10 p.m.-8 p.m.
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Instructor:
Christopher Kuo
Info - 3 points
CERAMICS I
- Department: Visual Arts
- M 10 a.m.-4 p.m.
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Instructor:
Jacq Groves
Info - 3 points
NONFICTION WORKSHOP
- Department: Writing
- F 10 a.m.-1 p.m.
- W 2 p.m.-5 p.m.
- T 1:10 p.m.-4:10 p.m.
- T 10 a.m.-1 p.m.
- T 1:10 p.m.-4:10 p.m.
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Instructor:
Cristen A Beam
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Instructor:
Chloe Jones
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Instructor:
Jaquira Diaz
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Instructor:
Lars Horn
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Instructor:
Leslie S Jamison
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Instructor:
Wendy Walters
Info - 6 points
Global Economic Environment
- Department: Business Economics
- S 8:30 a.m.-11:30 a.m.
- F 12:30 p.m.-3:30 p.m.
- SS 12:30 p.m.-3:30 p.m.
- S 3:45 p.m.-6:45 p.m.
- MU 8:30 a.m.-11:30 a.m.
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Instructor:
Conor Walsh
Info - 1.5 points
CERAMICS II
This course will focus on using ceramics as a primary art making machine by breaking out of the constraints wedded to this traditional material. Building on the foundation set in Ceramics1, this course will delve further into the technical and historical aspects of the ceramic process as well as into the conceptual ideas in artmaking.
Students will use a self-directed working process to facilitate the incorporation of ceramic materials into their existing art making while also being allowed room to go in their own conceptual direction. Rigorous group and individual critiques will be held on a regular basis.
Content is a priority in this class, along with the further understanding of ceramic processes and materials. The goal is for the student to be proficient in producing their ideas without the obstruction of technical difficulties.
- Department: Visual Arts
- R 10 a.m.-4 p.m.
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Instructor:
Patrice R Washington
Info - 3 points
Quantitative Methods - LAB
Lab section corresponding to CLMT 5002 Quantitative Methods for Climate Applications
- Department: Climate School
- W 4:10 p.m.-6 p.m.
- W 6:10 p.m.-8 p.m.
- R 6:10 p.m.-8 p.m.
- 0 points
PROBABILITY
Prerequisites: At least one semester of calculus. A calculus-based introduction to probability theory. Topics covered include random variables, conditional probability, expectation, independence, Bayes rule, important distributions, joint distributions, moment generating functions, central limit theorem, laws of large numbers and Markovs inequality.
- Department: Statistics
- TR 6:10 p.m.-7:25 p.m.
- TR 1:10 p.m.-3:40 p.m.
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Instructor:
Marco A Avella Medina
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Instructor:
Jingchen Liu
CULPA: 2 h-index: 19 Info - 3 points
STATISTICAL INFERENCE
Prerequisites: STAT GR5203 or the equivalent, and two semesters of calculus. Calculus-based introduction to the theory of statistics. Useful distributions, law of large numbers and central limit theorem, point estimation, hypothesis testing, confidence intervals, maximum likelihood, likelihood ratio tests, nonparametric procedures, theory of least squares and analysis of variance.
- Department: Statistics
- TR 6:10 p.m.-7:25 p.m.
- TR 1:10 p.m.-3:40 p.m.
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Instructor:
Ashley Datta
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Instructor:
Michael Sobel
CULPA: 5 Wikipedia h-index: 35 Info - 3 points
APPLIED MACHINE LEARNING II
APPLIED MACHINE LEARNING II
- Department: Applied Analytics
- T 8:10 a.m.-10 a.m.
- T 8:10 p.m.-10 p.m.
- W 6:10 p.m.-8 p.m.
- R 8:10 p.m.-10 p.m.
- M 6:10 p.m.-8 p.m.
- W 8:10 p.m.-10 p.m.
- M 8:10 p.m.-10 p.m.
- R 8:10 p.m.-10 p.m.
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Instructor:
Kitty K Chan
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Instructor:
Vishal Lala
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Instructor:
Birol Emir
CULPA: 14 Info -
Instructor:
Andrew Assing
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Instructor:
Evgeniya Reshetnyak
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Instructor:
Adrian Heilbut
h-index: 13 Info -
Instructor:
Vinay P Mahadeo
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Instructor:
Zachary Kurtz
Info - 3 points
LINEAR REGRESSION MODELS
Prerequisites: STAT GR5203 and GR5204 or the equivalent. Theory and practice of regression analysis, Simple and multiple regression, including testing, estimation, and confidence procedures, modeling, regression diagnostics and plots, polynomial regression, colinearity and confounding, model selection, geometry of least squares. Extensive use of the computer to analyse data.
STAT COMP & INTRO DATA SCIENCE
STAT COMP & INTRO TO DATA SCI
Course Overview:
This course introduces Python programming, covering data structures, control-flow, objects, and functions, along with libraries like re, requests, numpy, pandas, scikit-learn, scipy, and more. These skills are applied to real-world data science tasks, including AB testing, data manipulation, modeling, optimization, simulations, and data visualization.
Students will develop computational thinking abilities, including problem decomposition, pattern recognition, data representation, abstraction, and algorithm design, through practical exercises.
- Department: Statistics
- F 10:10 a.m.-12:40 p.m.
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Instructor:
Benjamin K Goodrich
Info - 3 points
Foundations of Clinical Medicine: Tutori
FNDATION CLINICAL MED: TU
- Department: Medicine
- 0 points
Mediation: Practitioner Development
On a daily basis we may encounter conflicts and seek to resolve them through negotiations and other forms of conflict resolution. Some of these are simple and easy to resolve, while others are complex and may require the support of a third party, or
mediator
. In this course we will explore mediation from several points of view and approaches, as listed below under the session headings. We will explore the theories that underlie the field of mediation as we concentrate on building the skills necessary to practice mediation professionally.
Note: This course qualifies as the prerequisite for an apprenticeship opportunity in anticipation of
mediation certification
through a number of Community Dispute Resolution Centers statewide. This course is also Part 146A approved, which is necessary to qualify for participation on a roster in the New York State Court System.
- Department: Negotiation & Conflict Resolution
- U 9 a.m.-5 p.m.
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Instructor:
Jenny Besch
Info - 3 points
ELEMENTARY STOCHASTIC PROCESSE
Corequisites: GR5203 or the equivalent. Review of elements of probability theory. Poisson processes. Renewal theory. Walds equation. Introduction to discrete and continuous time Markov chains. Applications to queueing theory, inventory models, branching processes.
- Department: Statistics
- MW 11:40 a.m.-12:55 p.m.
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Instructor:
Mark Brown
CULPA: 18 Wikipedia Info - 3 points
PYTHON FOR DATA ANALYSIS
PYTHON FOR DATA ANALYSIS ONLNE
- Department: Applied Analytics
- T 8:10 p.m.-10 p.m.
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Instructor:
Max Vilenchik
Info - 3 points
COMMUNICATION AND GLOBAL BRANDS
COMMUNICATION & GLOBAL BRANDS
This course examines the discipline of global marketing communication, including the environmental factors that enabled global marketing. The course assesses early models of communication management and the current factors that enable global communication programs: the identification of global target audiences; the kinds of products and services that lend themselves to global communication and those that don’t; and the characteristics of leadership brands that are preeminent in global communication today. Students consider how levels of development and cultural values affect communication programs and how local differences can be reflected in global programs. Message creation and the available methods of message distribution are evaluated in the context of current and future trends. Students learn how to approach strategy and develop an integrated, holistic global communication program and how to manage such a program.
- Department: Strategic Communication
- T 7:30 p.m.-9:20 p.m.
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Instructor:
Cheryl Fenelle-Dixon
Info - 3 points
CONFLICT RESOLUTION AND DYNAMICAL SYSTEM
CONF RESOLUTION/DYNAMIC S
Dynamical Systems Theory (DST) is a methodology developed in the hard sciences to understand complex systems—from the weather to the functioning of cells, using mathematical algorithms. We added the lens of social-psychological concepts and practices to better understand how to apply DST to conflict. We are now applying DST to conflict analysis and resolution for larger social problems and conflicts that are protracted, deeply embedded and have multiple complex issues. This DST approach goes beyond linear problem-solving and embraces complexity in new ways. Dynamical Systems and Conflict Resolution (NECR 5210) is a required 3-credit course in the Negotiation and Conflict Resolution Program (NECR). Students are expected to spend on average 20 hours per week on this course, including media, group work, readings, and other assignments. NECR 5210 builds on concepts from Understanding Conflict and Cooperation (NECR 5101), where students became familiar with conflict resolution frames, theories, and models, as well as a basic understanding of the DST approach. This course will further develop and advance student understanding and use of advanced DST concepts and tools that will be useful for scholar-practitioners facing situations that require a systemic approach for more highly complex conflicts. It is a complementary approach that rounds out the other concepts and skills student learn in the program. Throughout this course students will work individually and in groups on multiple case studies, to understand and apply DST methodology, while developing an appreciation for the more fluid and non-linear DST approach.
- Department: Negotiation & Conflict Resolution
- USSU 9 a.m.-5 p.m.
- 3 points
SOLID WASTE MANAGEMENT
- Department: Sustainability Management
- R 6:10 p.m.-8 p.m.
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Instructor:
Haralambos Vasiliadis
Info - 3 points
SOLID WASTE MANAGEMENT
- Department: Auditing
- R 6:10 p.m.-8 p.m.
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Instructor:
Haralambos Vasiliadis
Info - 0 points
MICROECONOMIC ANALYSIS II
- Department: Economics
- MW 10:10 a.m.-11:25 a.m.
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Instructor:
Guillaume Haeringer
CULPA: 2 Info - 3 points
MACROECONOMCS ANALYSIS II
- Department: Economics
- MW 2:40 p.m.-3:55 p.m.
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Instructor:
Irasema Alonso
CULPA: 12 Info - 3 points
DIRECTING II
- Department: Film
- T 10 a.m.-1 p.m.
- M 2 p.m.-5 p.m.
- W 2 p.m.-5 p.m.
- M 10 a.m.-1 p.m.
- W 9:30 a.m.-12:30 p.m.
- R 6 p.m.-9 p.m.
- R 10 a.m.-1 p.m.
- M 6 p.m.-9 p.m.
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Instructor:
Bogdan G Apetri
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Instructor:
Ian W Olds
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Instructor:
Hilary Brougher
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Instructor:
Stephen Lee
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Instructor:
Anocha Suwichakornpong
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Instructor:
Carlo Mirabella-Davis
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Instructor:
Anocha Suwichakornpong
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Instructor:
Sean R Dunn
Info - 3 points
FOUNDATIONS OF SPORTS MANAGEMENT
FOUNDATIONS OF SPORTS MGM
- Department: Sports Management
- M 2:10 p.m.-4 p.m.
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Instructor:
Laurajean Holmgren
Info - 3 points
SUSTAINABLE ENTREPRENEURSHIP
- Department: Sustainability Management
- M 6:10 p.m.-8 p.m.
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Instructor:
Jonathan Hollander
Info - 3 points
SOCIAL JUSTICE: NARRATIVES OF INEQUITY (
- Department: Narrative Medicine
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Instructor:
Courtni K Jeffers
Info - 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.
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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.
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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.
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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.
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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.
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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
- S 9 a.m.-5 p.m.
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Instructor:
Aldo Civico
Wikipedia Info - 1.5 points
THE EARTH'S CLIMATE SYSTEM
- Department: Sustainability Management
- T 4:10 p.m.-6 p.m.
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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.
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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.
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Instructor:
Rongning Wu
CULPA: 1 Info - 3 points
DIRECTING ACTORS II
- Department: Film
- M 2 p.m.-5 p.m.
- M 6 p.m.-9 p.m.
- R 2 p.m.-5 p.m.
- T 6 p.m.-9 p.m.
- R 10 a.m.-1 p.m.
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Instructor:
Shira-Lee Shalit
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Instructor:
Emil Benjamin
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Instructor:
Jodie Markell
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Instructor:
Abigail Zealey Bess
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Instructor:
Lisa Milinazzo
Info - 3 points
The Future of Work
Future of Work course to complement 1.5 credit internship course.
- Department: Human Capital Management
- M 6:10 p.m.-8 p.m.
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Instructor:
Joshua Bellis
Info - 1.5 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.
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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
- MW 7:40 p.m.-8:55 p.m.
- R 6:10 p.m.-8:40 p.m.
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Instructor:
Alex Pijyan
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Instructor:
Haiyuan Wang
Info - 3 points
PURPOSE-DRIVEN COMMUNICATION
- Department: Strategic Communication
- W 5:10 p.m.-7 p.m.
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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 6:10 p.m.-8 p.m.
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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.
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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.
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Instructor:
Rich Lauria
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Instructor:
Rajat Baijal
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Instructor:
Chris Lee
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Instructor:
Muriel Rachid Campomizzi
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Instructor:
Kerry Gendron
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Instructor:
Anthony Wong
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Instructor:
Violet Diamant
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Instructor:
Melody Feinberg
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Instructor:
Chris Lee
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Instructor:
Juan Echeverri
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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.
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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
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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.
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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.
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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.
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.
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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.
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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.
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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.
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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
- MTWRU 9 a.m.-5 p.m.
- M 10:10 a.m.-noon
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Instructor:
Kristine Billmyer
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Instructor:
Ciara Ungar
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.
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Instructor:
Nabeel Ahmad
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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.
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Instructor:
Laura Milewczik
Info - 3 points