SUSTAINABILITY IN THE FACE OF NATURAL DI

SUST IN FACE OF NATRL DIS

Natural hazards, naturally occurring phenomena, which can lead to great damage and loss of life, pose a great challenge for the sustainability of communities around the world. This course aims to prepare students to tackle specific hazards relevant to their life and work by providing them the scientific background and knowledge of the environmental factors that combine to produce natural disasters. The course will also train students about the methods used to study certain aspects of natural hazards and strategies for assessing risk and preparing communities and businesses for natural disasters. The course will cover a range of natural hazards, including geological, hydro-meteorological, and biological. The course will emphasize the driving physical, chemical and biological processes controlling the various hazards, and the observation and modeling methods used by scientists to assess and monitor events. Many case examples, including hurricanes, earthquakes and volcanic eruptions that occurred in the last five years, will be given and analyzed for the characteristics of the event, the preparation, and the response. By providing students with a solid understanding of past natural disasters, the course prepares them to think more critically about creating more resilient communities, which can resist catastrophic events. Students will be studying the underpinning scientific principles of natural disasters but will also learn specific strategies for planning, mitigation, and response. During the course, students will master cutting-edge tools and technologies that will prepare them to work in the complex and demanding field of disaster management. After completing the course, students will be able to understand past events, communicate risk, and make critical decision related to disaster and preparedness. In increasingly unpredictable times, there is a need for more resilient and connected communities, and this particular course will train students in both the knowledge and skills needed to lead and strengthen those communities and resilience efforts at scale.
Advising Note:
Students are expected to have taken college-level Calculus, Physics, and Introductory Statistics. Students are expected to have experience with computer based data analysis (Excel, R, Matlab or Python).

• Department: Sustainability Technology
• R 6:10 p.m.-8 p.m.
• 3 points

MATH FINANCE PRACTITIONERS SEM

Prerequisites: MATH W5010 or knowledge of J. Hulls book Options, futures. Prerequisites: Math GR5010 or knowledge of J. Hulls book Options, futures. Seminar consists of presentations and mini-courses by leading industry specialists in quantitative finance. Topics include portfolio optimization, exotic derivatives, high frequency analysis of data and numerical methods. While most talks require knowledge of mathematical methods in finance, some talks are accessible to general audience.

• Department: Mathematics
• TR 7:40 p.m.-8:55 p.m.
• Instructor: Lars T Nielsen
  h-index: 17 Info
• 3 points

INTRODUCTION TO HEALTH CARE NEGOTIATION

TBA

• Department: Auditing
• Instructor: Rodney K Jr. Erb
  Info
• 0 points

INTRODUCTION TO HEALTH CARE NEGOTIATION

TBA

• Department: Negotiation & Conflict Resolution
• Instructor: Rodney K Jr. Erb
  Info
• 3 points

INTERNSHIP IN SOCIAL RESEARCH

This course gives students two credits of academic credit for the work they perform in such an social science oriented internships.

• Department: Quantitative Methods/Social Sciences
• Instructor: Gregory M Eirich
  CULPA: 1 Info
• 1 points

GEO INFO SYSTEMS (GIS) FOR SUST SCIENCE

Many environmental and sustainability science issues have a spatial, location-based component. Increasingly available spatial data allow location-specific analysis and solutions to problems and understanding issues. As result, analyzing and identifying successful and sustainable solutions for these issues often requires the use of spatial analysis and tools. This course introduces common spatial data types and fundamental methods to organize, visualize and analyze those data using Geographic Information Systems (GIS). Through a combination of lectures and practical computer activities the students will learn and practice fundamental GIS and spatial analysis methods using typical sustainable science case studies and scenarios. A key objective of this course is to provide students with essential GIS skills that will aid them in their professional career and to offer an overview of current GIS applications. In the first part, the course will cover basic spatial data types and GIS concepts. The students will apply those techniques by analyzing potential impacts of storms on New York City as part of a guided case study. A mid-term report describing this case study and the results is required. In the second part, building on the basic concepts introduced in the first part, students will be asked to identify a sustainable science question of their choice that they would like to address as a final project. Together with the instructor they will be developing a strategy of analyzing and presenting related spatial data. While the students are working on their projects additional GIS method and spatial analysis concepts will be covered in class. At the end of the course Students will briefly present their final project and submit a paper describing their project. This course does not assume that students have had any previous experience with GIS.

• Department: Sustainability Technology
• M 6:10 p.m.-8 p.m.
• Instructor: Frank Nitsche
  CULPA: 1 h-index: 29 Info
• 3 points

INTERNSHIP IN SOCIAL RESEARCH II

INTERNSHIP IN SOCIAL RSRC

• Department: Quantitative Methods/Social Sciences
• Instructor: Gregory M Eirich
  CULPA: 1 Info
• 1 points

PRACTICUM IN DATA ANALYSIS

This practicum course is meant to offer valuable training to students. Specifically, this practicum will mimicthe typical conditions that students would face in an internship in a large data-intense institution. Thepracticum will focus on four core elements involved in most internships: (1) Developing the intuition andskills to properly scope ambiguous project ideas; (2) practicing organizing and accessing a variety oflarge-scale data sources and formats; (3) conducting basic and advanced analysis of big data; and (4)communicating and “productizing” results and findings from the earlier steps, in things like dashboards,reports, interactive graphics, or apps. The practicum will also give students time to reflect on their work, andhow it would best translate into corporate, non-profit, start-up and other contexts.

• Department: Quantitative Methods/Social Sciences
• M 8:10 a.m.-10 a.m.
• Instructor: Aracelis Z Torres
  Info
• 3 points

METHODS WORKSHOP

Introducing students to a series of methods, methodological discussions, and questions relevant to the focus of the Masters program: urban sociology and the public interest. Three methodological perspectives will frame discussions: analytical sociology, small-n methods, and actor-network theory.

• Department: Sociology
• M 4:10 p.m.-6 p.m.
• Instructor: Ryan A Hagen
  Info
• 4 points

PRACTICUM IN DATA ANALYSIS II

This practicum will mimic the typical conditions that students would face in an internship in a large data-intense institution. The practicum will focus on four core elements involved in most internships: • developing the intuition and skills to properly scope ambiguous project ideas; • practicing organizing and accessing a variety of large-scale data sources and formats; • conducting basic and advanced analysis of big data; and • communicating and “productizing” results and findings from the earlier steps, in things like dashboards, reports, interactive graphics, or apps. The practicum will also give students time to reflect on their work, and how it would best translate into corporate, non-profit, start-up and other contexts.

• Department: Quantitative Methods/Social Sciences
• M 8:10 a.m.-10 a.m.
• Instructor: Aracelis Z Torres
  Info
• 3 points

INTERNSHIP IN SOCIAL III

INTERNSHP III

Students enrolled in the Quantitative Methods in the Social Sciences M.A. program have a number of opportunities for internships with various organizations in New York City. Over the past three years, representatives from a number of different organizations – including ABC News, Pfizer, the Manhattan Psychiatric Center, Merrill Lynch, and the Robert Wood Johnson Foundation – have approached students and faculty in QMSS about the possibility of having QMSS students work as interns. Many of these internships require students to receive some sort of course credit for their work. All internships will be graded on a pass/fail basis.

• Department: Quantitative Methods/Social Sciences
• Instructor: Gregory M Eirich
  CULPA: 1 Info
• 1 points

PRACTICUM IN DATA ANALYSIS

This practicum course is meant to offer valuable training to students. Specifically, this practicum will mimicthe typical conditions that students would face in an internship in a large data-intense institution. Thepracticum will focus on four core elements involved in most internships: (1) Developing the intuition andskills to properly scope ambiguous project ideas; (2) practicing organizing and accessing a variety oflarge-scale data sources and formats; (3) conducting basic and advanced analysis of big data; and (4)communicating and “productizing” results and findings from the earlier steps, in things like dashboards,reports, interactive graphics, or apps. The practicum will also give students time to reflect on their work, andhow it would best translate into corporate, non-profit, start-up and other contexts.

• Department: Quantitative Methods/Social Sciences
• M 6:10 p.m.-8 p.m.
• Instructor: Charlie Riemann
  Info
• 3 points

PRACTICUM IN DATA ANALYSIS

This practicum course is meant to offer valuable training to students. Specifically, this practicum will mimicthe typical conditions that students would face in an internship in a large data-intense institution. The practicum will focus on four core elements involved in most internships: (1) Developing the intuition andskills to properly scope ambiguous project ideas; (2) practicing organizing and accessing a variety oflarge-scale data sources and formats; (3) conducting basic and advanced analysis of big data; and (4)communicating and “productizing” results and findings from the earlier steps, in things like dashboards,reports, interactive graphics, or apps. The practicum will also give students time to reflect on their work, andhow it would best translate into corporate, non-profit, start-up and other contexts.

• Department: Quantitative Methods/Social Sciences
• M 6:10 p.m.-8 p.m.
• Instructor: Charlie Riemann
  Info
• 3 points

SUSTAINABLE FASHION AND STARTUP STRATEGY

SUST FASHION & STARTUP ST

Fashion’s consistent ranking among the top 3 global polluters has become a decades old fact struggling to gain a proportionate response among the brand startup and sourcing community. With industry revenues set to exceed $1 trillion, there is an opportunity to critically address existing revenue models predicated on traditional metrics, such as constant growth, and singular bottom lines. The course attempts to create a nexus between the fashion entrepreneur and systems thinker to explore strategic solutions that address sustainability though an environmental, social and economic lens. The aim is to foster a mindful, yet critical discourse on fashion industry initiatives, past and present, and to practice various tools that help transition existing organizations and incubate new startups towards sustainable outcomes.

• Department: Sustainability Management
• T 6:10 p.m.-8 p.m.
• Instructor: Ammar Belal
  Info
• 3 points

STATISTICS, DATA ANALYSIS, AND CODING FO

STATS, DATA, ANLYS&CODING

Students in the Master of Science in Sustainability Science will encounter a range of scientific problems throughout their Science-specific courses that require a strong foundational level of mathematical and statistical knowledge.  In addition, course-work will involve computer coding to read, analyze, and visualize data sets.  This course provides an overview of essential mathematical concepts, an introduction to new concepts in statistics and data analysis, and provides computer coding skills that will prepare students for coursework in the Master of Science in Sustainability Science program as well as to succeed in a career having a sustainability science component.  In addition to an overview of essential mathematical concepts, the skills gained in this course include statistics, and coding applied to data analysis in the Sustainability Sciences. Many of these skills are broadly applicable to science-related professions, and will be useful to those having careers involving interaction with scientists, managing projects utilizing scientific analysis, and developing science-based policy. Students enrolled in this course will learn through lectures, class discussion, and hands-on exercises that address the following topics: Review of mathematical concepts in calculus, trigonometry, and linear algebra; Mathematical concepts related to working on a spherical coordinate system (such as that for the Earth); Probability and statistics, including use of probability density functions to calculate expectations, hypothesis testing, and the concept of experimental uncertainty; Concepts in data analysis, including linear least squares, time-series analysis, parameter uncertainties, and analysis of fit; Computer coding skills, including precision of variables, arrays and data structures, input/output, flow control, and subroutines, and coding tools to produce basic X-Y plots as well as images of data fields on a global map.

• Department: Sustainability Technology
• W 6:10 p.m.-8 p.m.
• Instructor: Michael Previdi
  Info
• 3 points

SOCIAL NETWORK ANALYSIS

The course is designed to teach students the foundations of network analysis including how to manipulate, analyze and visualize network data themselves using statistical software. We will focus on using the statistical program R for most of the work. Topics will include measures of network size, density, and tie strength, measures of network diversity, sampling issues, making ego-nets from whole networks, distance, dyads, homophily, balance and transitivity, structural holes, brokerage, measures of centrality (degree, betweenness, closeness, eigenvector, beta/Bonacich), statistical inference using network data, community detection, affiliation/bipartite networks, clustering and small worlds; positions, roles and equivalence; visualization, simulation, and network evolution over time.

• Department: Quantitative Methods/Social Sciences
• F 11:10 a.m.-1 p.m.
• Instructor: Gregory M Eirich
  CULPA: 1 Info
• 3 points

DATA VISUALIZATION

This course is designed to the interdisciplinary and emerging field of data science. It will cover techniques and algorithms for creating effective visualizations based on principles from graphic design, visual art, perceptual psychology, and cognitive science to enhance the understanding of complex data. Students will be required to complete several scripting, data analysis and visualization design assignments as well as a final project. Topics include: data and image models, social and interactive visualizations, principles and designs, perception and attention, mapping and cartography, network visualization. Computational methods are emphasized and students will be expected to program in R, Javascript, D3, HTML and CSS and will be expected to submit and peer review work through Github. Students will be expected to write up the results of the project in the form of a conference paper submission.

• Department: Quantitative Methods/Social Sciences
• W 6:10 p.m.-8 p.m.
• Instructor: Thomas Brambor
  h-index: 9 Info
• 3 points

PROSEMINAR II

• Department: Sociology
• T 4:10 p.m.-6 p.m.
• Instructor: Denise Milstein
  CULPA: 9 h-index: 5 Info
• 1 points

BAYESIAN STATS FOR THE SOC SCI

An introduction to Bayesian statistical methods with applications to the social sciences. Considerable emphasis will be placed on regression modeling and model checking. The primary software used will be Stan, which students do not need to be familiar with in advance. Students in the course will access the Stan library via R, so some experience with R is necessary. Any QMSS student is presumed to have sufficient background. Any non-QMSS students interested in taking this course should have a comparable background to a QMSS student in basic probability. Topics to be covered are a review of calculus and probability, Bayesian principles, prediction and model checking, linear regression models, Bayesian calculations with Stan, hierarchical linear models, nonlinear regression models, missing data, and decision theory.

• Department: Quantitative Methods/Social Sciences
• M 4:10 p.m.-6 p.m.
• Instructor: Benjamin K Goodrich
  Info
• 3 points

FIELD WORK II

• Department: Sociology
• F 8:10 a.m.-10 a.m.
• Instructor: Denise Milstein
  CULPA: 9 h-index: 5 Info
• 1 points

NATURAL LANG PROCESSING SOCIAL SCIENCES

Social scientists need to engage with natural language processing (NLP) approaches that are found in computer science, engineering, AI, tech and in industry. This course will provide an overview of natural language processing as it is applied in a number of domains. The goal is to gain familiarity with a number of critical topics and techniques that use text as data, and then to see how those NLP techniques can be used to produce social science research and insights. This course will be hands-on, with several large-scale exercises. The course will start with an introduction to Python and associated key NLP packages and github. The course will then cover topics like language modeling; part of speech tagging; parsing; information extraction; tokenizing; topic modeling; machine translation; sentiment analysis; summarization; supervised machine learning; and hidden Markov models. Prerequisites are basic probability and statistics, basic linear algebra and calculus. The course will use Python, and so if students have programmed in at least one software language, that will make it easier to keep up with the course.

• Department: Quantitative Methods/Social Sciences
• T 4:10 p.m.-6 p.m.
• Instructor: Patrick Houlihan
  Info
• 3 points

THESIS SEMINAR II

• Department: Sociology
• T 10:10 a.m.-noon
• Instructor: Denise Milstein
  CULPA: 9 h-index: 5 Info
• 3 points

HISTOIRE ET LITTERATURE

• Department: French
• Instructor: Christine Valero
  Info
• 3 points

APPLIED DATA SCI FOR SOC SCIENTISTS

• Department: Quantitative Methods/Social Sciences
• W 10:10 a.m.-noon
• Instructor: Marco A Morales Barba
  Info
• 3 points

MODERN DATA STRUCTURES

This course is intended to provide a detailed tour on how to access, clean, “munge” and organize data, both big and small. (It should also give students a flavor of what would be expected of them in a typical data science interview.) Each week will have simple, moderate and complex examples in class, with code to follow. Students will then practice additional exercises at home. The end point of each project would be to get the data organized and cleaned enough so that it is in a data-frame, ready for subsequent analysis and graphing. Therefore, no analysis or visualization (beyond just basic tables and plots to make sure everything was correctly organized) will be taught; and this will free up substantial time for the “nitty-gritty” of all of this data wrangling.

• Department: Quantitative Methods/Social Sciences
• R 4:10 p.m.-6 p.m.
• Instructor: Marco A Morales Barba
  Info
• 3 points

MACHINE LEARNING SOC SCI

Prerequisites: basic probability and statistics, basic linear algebra, and calculus This course will provide a comprehensive overview of machine learning as it is applied in a number of domains. Comparisons and contrasts will be drawn between this machine learning approach and more traditional regression-based approaches used in the social sciences. Emphasis will also be placed on opportunities to synthesize these two approaches. The course will start with an introduction to Python, the scikit-learn package and GitHub. After that, there will be some discussion of data exploration, visualization in matplotlib, preprocessing, feature engineering, variable imputation, and feature selection. Supervised learning methods will be considered, including OLS models, linear models for classification, support vector machines, decision trees and random forests, and gradient boosting. Calibration, model evaluation and strategies for dealing with imbalanced datasets, n on-negative matrix factorization, and outlier detection will be considered next. This will be followed by unsupervised techniques: PCA, discriminant analysis, manifold learning, clustering, mixture models, cluster evaluation. Lastly, we will consider neural networks, convolutional neural networks for image classification and recurrent neural networks. This course will primarily us Python. Previous programming experience will be helpful but not requisite. Prerequisites: basic probability and statistics, basic linear algebra, and calculus.

• Department: Quantitative Methods/Social Sciences
• T 6:10 p.m.-8 p.m.
• Instructor: Michael Parrott
  Info
• 3 points

PROJECTS IN ADVANCED MACHINE LEARNING

ADV MACHINE LEARNING

Machine learning algorithms continue to advance in their capacity to predict outcomes and rival human judgment in a variety of settings.  This course is designed to offer insight into advanced machine learning models, including Deep Learning, Recurrent Neural Networks, Adversarial Neural Networks, Time Series models and others.  Students are expected to have familiarity with using Python, the scikit-learn package, and github.  The other half of the course will be devoted to students working in key substantive areas, where advanced machine learning will prove helpful -- areas like computer vision and images, text and natural language processing, and tabular data.  Students will be tasked to develop team projects in these areas and they will develop a public portfolio of three (or four) meaningful projects.  By the end of the course, students will be able to show their work by launching their models in live REST APIs and web-applications.

• Department: Quantitative Methods/Social Sciences
• R 6:10 p.m.-8 p.m.
• Instructor: Marco A Morales Barba
  Info
• 3 points

ORAL HISTORY INTERNSHIP

• Department: Oral History
• R 3:10 p.m.-4 p.m.
• Instructor: Amy A Starecheski
  h-index: 5 Info
• 2-4 points

THE AUTHENTIC LEADER

Effective leaders are able to think critically about problems and opportunities, imagine unexpected futures, craft a compelling vision, and drive change. In this course, we study the theoretical underpinnings of leadership communication, relying on empirical evidence as a guide for practice. Students gain important perspective on leadership styles, mastering the competencies required for a variety of contexts.

• Department: Strategic Communication
• T 10:10 a.m.-noon
• T 2:10 p.m.-4 p.m.
• None None-None
• Instructor: Kevin Visconti
  Info
• 3 points

THE DOCUMENTARY TRADITION

• Department: Film
• M 2 p.m.-5:45 p.m.
• Instructor: Nico Baumbach
  Info
• 3 points

MULTIMEDIA STORYTELLING

n/a

• Department: Oral History
• M 3:10 p.m.-6 p.m.
• Instructor: Nyssa Chow
  Info
• 4 points

MONITORING AND ANALYSIS OF MARINE & ESTU

MONIT & ANLYS OF MARINE &

From a global perspective, many of the earth’s most important environments and resources for global sustainability are located in marine and estuarine areas.  This class will explore open-ocean and estuarine processes, reviewing what is known about the temporal variability and interconnectedness of these physical and biologic systems.. A few examples include; 1.) oceanic environments were incompletely understood processes regulate the exchange of heat, water and carbon dioxide gas with the atmosphere, 2.) the relationship between nutrients and primary production and fisheries in open ocean, estuarine and coral reef environments and climatic phenomenon such as El Niño South Oscillation (ENSO), the Pacific Decadal Oscillation (PDO) and Atlantic Multidecadal Oscillation (AMO). 3.) For estuaries, current sea level and urbanization stresses on the coastal environments will be discussed.  Professionals working in the environmental and engineering fields will benefit from a wide-ranging discussion of the multi-scaled processes influencing estuaries. Knowledge of the processes operating in these environments will lead to a more thorough understanding of the complex issues that may influence infrastructure and coastal development in and around estuarine environments in the near-future. Throughout the class we will explore marine and estuarine processes by studying regional and local responses to broader scale climatic forcing. Reading of textbook chapters and journal articles will supplement in-class lectures and discussion. Grading will be based on class participation, a two exams and a research paper. At the end of the course, students will have a strong scientific understanding about the impacts made on marine and estuary systems through physical, chemical, and biological processes. The course will prepare students to be well-trained in the core features of these systems and the relationship between natural and human processes, and equip them with the skills needed to explore marine and estuary systems in diverse scales and functions in the future.

• Department: Sustainability Technology
• W 6:10 p.m.-8 p.m.
• Instructor: Braddock Linsley
  h-index: 42 Info
• 3 points

VASTE DESERT D'HOMMES

• Department: French
• Instructor: Christine Valero
  Info
• 3 points

DIGITAL MEDIA & ANALYTICS

Digital media opens new opportunities for increasingly targeted communications across a variety of channels, which rapidly expands the importance of analytics in tracking and measuring key performance indicators (KPIs). This course prepares students to work within data- and model-driven environments with an emphasis on using analytics to develop insights and support strategic decisions.

• Department: Strategic Communication
• M 10:10 a.m.-noon
• M 12:10 p.m.-2 p.m.
• None None-None
• Instructor: Ethan Pew
  h-index: 0 Info
• 3 points

Serious Play: Oral History and the Art o

OH and the Art of Story

In this workshop, OHMA students will deepen their exploration of core tensions in the practice of oral history through the creation of narrative art in a range of genres and forms, including writing and performance. We ask of each form: What lines are marked by conventions of genre, and how do those compare to lines drawn by the ethics of oral history? How can we draw on narrative and performance in our own creative and scholarly contributions to oral history?   This class will be a space for experimentation and serious play, where students will discuss questions raised by the work of others, and grapple with those questions by making their own creative work. Pedagogically, we will simultaneously explore two areas of creation: oral history on the page, and oral history in performance. Students will make new work and engage in discussion about existing work. Class time will be spent discussing texts, workshopping students’ creative projects, and participating in activities designed to prompt collaboration and engineered to inspire new work. Over the course of the semester students will write, perform, and create prompts inspired by oral history.

• Department: Oral History
• R 10:10 a.m.-1 p.m.
• 4 points

COMPLEXITY OF CONFLICT AND CHANGE MANAGE

Complexity of Conflict and Change Management (NECR K5095) is an elective course in the Negotiation and Conflict Resolution (NECR) Program. The course explores how change can create conflict and also how conflict requires change. Conflict is generally about differences in how people think, know, prefer, believe, and understand. By entering into a conflict resolution process, people can shift their understanding and beliefs about the conflict, the other party or parties, and possible outcomes. The course reviews literature and case studies of how people are impacted at a fundamental level when change occurs. Understanding this elemental human experience can lead to greater self-awareness and the ability to manage change professionally and personally, in order to become effective change agents, negotiators, mediators, and peacemakers. We will also explore how leaders at all levels in organizations can play an important role in implementing change in an organizational context. Thoughtful and strategic approaches that consider the impact of a change management process can mitigate and even prevent conflict. We will review change management models and links to developments in neuroscience and how humans are biologically wired to resist change. Balancing theory and practice, this course will focus on the experience and expertise of the students. They will learn to apply practical conflict resolution approaches to change efforts at the individual and organizational levels as well as consider national and international applications.

• Department: Auditing
• Instructor: Susan Levin
  Info
• 0 points

COMPLEXITY OF CONFLICT AND CHANGE MANAGE

Complexity of Conflict and Change Management (NECR K5095) is an elective course in the Negotiation and Conflict Resolution (NECR) Program. The course explores how change can create conflict and also how conflict requires change. Conflict is generally about differences in how people think, know, prefer, believe, and understand. By entering into a conflict resolution process, people can shift their understanding and beliefs about the conflict, the other party or parties, and possible outcomes. The course reviews literature and case studies of how people are impacted at a fundamental level when change occurs. Understanding this elemental human experience can lead to greater self-awareness and the ability to manage change professionally and personally, in order to become effective change agents, negotiators, mediators, and peacemakers. We will also explore how leaders at all levels in organizations can play an important role in implementing change in an organizational context. Thoughtful and strategic approaches that consider the impact of a change management process can mitigate and even prevent conflict. We will review change management models and links to developments in neuroscience and how humans are biologically wired to resist change. Balancing theory and practice, this course will focus on the experience and expertise of the students. They will learn to apply practical conflict resolution approaches to change efforts at the individual and organizational levels as well as consider national and international applications.

• Department: Negotiation & Conflict Resolution
• Instructor: Susan Levin
  Info
• 3 points

APPLIED ANALYTICS IN ORGANIZATIONAL CONT

APP AN IN ORG CONTEXT

• Department: Applied Analytics
• W 6:10 p.m.-8 p.m.
• T 6:10 p.m.-8 p.m.
• Instructor: Cory E Labanow
  Info
• Instructor: Lori Cenci
  Info
• 3 points

ESTIMATING PROJECT COSTS

• Department: Construction Administration
• T 6:10 p.m.-8 p.m.
• Instructor: Jason I Levine
  Info
• 3 points

VALUE-BASED ENTERPRISE RISK MGMT

VALUE-BASED ERM

• Department: Enterprise Risk Management
• R 8:10 p.m.-10 p.m.
• T 6:10 p.m.-8 p.m.
• R 6:10 p.m.-8 p.m.
• M 6:10 p.m.-8 p.m.
• W 8:10 p.m.-10 p.m.
• T 8:10 p.m.-10 p.m.
• W 6:10 p.m.-8 p.m.
• Instructor: Rich Lauria
  Info
• Instructor: Mary Ellen Luning
  Info
• Instructor: Aristargos Christodoulou
  Info
• Instructor: Rajeev Dave
  Info
• Instructor: Benjamin M Perlman
  Info
• Instructor: Duncan Campbell
  Info
• Instructor: Marianna Belyavskiy
  Info
• 3 points

VALUE-BASED ENTERPRISE RISK MGMT

• Department: Auditing
• R 2:10 p.m.-4 p.m.
• R 8:10 p.m.-10 p.m.
• Instructor: Sim Segal
  Info
• Instructor: David A. Bartholomew
  Info
• 0 points

VALUE-BASED ENTERPRISE RISK MGMT

VALUE-BASED ERM (ONLINE)

• Department: Enterprise Risk Management
• R 2:10 p.m.-4 p.m.
• R 8:10 p.m.-10 p.m.
• Instructor: Sim Segal
  Info
• Instructor: David A. Bartholomew
  Info
• 3 points

INTRODUCTION TO HUMAN CAPITAL MANAGEMENT

• Department: Human Capital Management
• W 8:30 p.m.-10 p.m.
• Instructor: Louis Scenti
  Info
• 3 points

SELF & OTHER IN CLIN ENCOUNTER

• Department: Narrative Medicine
• M 6:10 p.m.-9 p.m.
• T 10:10 a.m.-1 p.m.
• Instructor: Craig Irvine
  Info
• Instructor: Michael E Davidovits
  Info
• 4 points

PAINTING I

• Department: Visual Arts
• T 10 a.m.-4 p.m.
• R 10 a.m.-4 p.m.
• Instructor: Samantha A Nye
  Info
• Instructor: Henry G Anker
  Info
• 3 points

FICTION WORKSHOP

• Department: Writing
• F 1:10 p.m.-4:10 p.m.
• R 10 a.m.-1 p.m.
• W 2 p.m.-5 p.m.
• F 1:10 p.m.-4:10 p.m.
• M 10 a.m.-1 p.m.
• Instructor: Hannah L Assadi
  Info
• Instructor: Diksha Basu
  Wikipedia Info
• Instructor: James Canon
  Wikipedia Info
• Instructor: Bonnie Chau
  Wikipedia Info
• Instructor: Joanna B Hershon
  CULPA: 3 Info
• 6 points

FINANCE AND ACCOUNTING FOR THE CONSTRUCT

FIN & ACCTG CONSTRCTN INDUSTRY

• Department: Construction Administration
• M 6:10 p.m.-8 p.m.
• Instructor: William Fischer
  Info
• 3 points

Business Analytics

• Department: Decision, Risk and Operations
• Instructor: Yashodhan Kanoria
  h-index: 18 Info
• 1.5 points

Business Analytics

• Department: Decision, Risk and Operations
• Instructor: Yashodhan Kanoria
  h-index: 18 Info
• 1.5 points

Business Analytics

• Department: Decision, Risk and Operations
• Instructor: Yashodhan Kanoria
  h-index: 18 Info
• 1.5 points

Business Analytics

• Department: Decision, Risk and Operations
• Instructor: Yashodhan Kanoria
  h-index: 18 Info
• 1.5 points

UNDERSTAND CONFLICT & COOPERATION

UNDERSTAND CONFL & COOPER

• Department: Negotiation & Conflict Resolution
• W 5:10 p.m.-6:50 p.m.
• Instructor: Peter T Coleman
  h-index: 35 Info
• 3 points

UNDERSTAND CONFLICT & COOPERATION

UNDERSTAND CONFL & COOPER

• Department: Auditing
• W 5:10 p.m.-6:50 p.m.
• None None-None
• Instructor: Peter T Coleman
  h-index: 35 Info
• Instructor: Fulya N Beriker
  Info
• 0 points

UNDERSTAND CONFLICT & COOPERATION

UNDERSTAND CONFL & COOPER

• Department: Negotiation & Conflict Resolution
• Instructor: Fulya N Beriker
  Info
• 3 points

PSYCHIATRIC MEDICINE

• Department: Psychiatry
• 0 points

SAFETY IN THE CONSTRUCTION INDUSTRY

SAFETY IN THE CONSTR IND

• Department: Construction Administration
• T 6:10 p.m.-8 p.m.
• Instructor: Joseph Schwed
  Info
• 3 points

Operations Management & Strate

• Department: Decision, Risk and Operations
• Instructor: Hongyao Ma
  h-index: 7 Info
• 1.5 points

Operations Management & Strate

• Department: Decision, Risk and Operations
• Instructor: Hongyao Ma
  h-index: 7 Info
• Instructor: Cyrus Mohebbi
  Info
• 1.5 points

Operations Management & Strate

• Department: Decision, Risk and Operations
• Instructor: Cyrus Mohebbi
  Info
• 1.5 points

PAINTING III

• Department: Visual Arts
• W 10 a.m.-4 p.m.
• Instructor: Thomas White
  Info
• 3 points

LEGAL ISSUES IN BUILDING CONSTRUCTION

LEGAL ISSUES-BLDG CONSTR

• Department: Construction Administration
• W 6:10 p.m.-8 p.m.
• Instructor: Dana E Gold
  Info
• 3 points

ELEMENTAL TOPICS IN CONSTRUCTION MANAGEM

ELEMENTAL TOPICS IN CNSTR

This course is designed to provide students with introductory knowledge and basic skills they will need to understand and apply as they progress through the program. Students receive an overview of key topics that will be covered in greater detail through core courses and electives during subsequent terms. Each class session provides a primer on a specific area of vital importance, including construction techniques, legal issues, contracts, blueprint reading, scheduling, sustainability, claims and more. Upon completion students will be familiar with basic concepts, terminology and procedures associated with the industry, and well prepared to study these subjects in greater depth.

• Department: Construction Administration
• T 6:10 p.m.-8 p.m.
• 1.5 points

INTRODUCTION TO NEGOTIATION

INTRO TO NEGO (NECR ONLY)

• Department: Negotiation & Conflict Resolution
• R 6:10 p.m.-8 p.m.
• TWRF 9 a.m.-5 p.m.
• Instructor: Bodi Regan
  Info
• Instructor: Martin E Epstein
  Info
• 3 points

INTRODUCTION TO NEGOTIATION

INTRO TO NEGO (NECR ONLY)

• Department: Negotiation & Conflict Resolution
• TWRF 9 a.m.-5 p.m.
• Instructor: Martin E Epstein
  Info
• 3 points

NEGOTIATION & DISPUTE RESOLUTION IN SPRT

• Department: Sports Management
• MTWRF 9 a.m.-5 p.m.
• Instructor: Scott Rosner
  Info
• 3 points

FOUNDATIONS OF CLINICAL MEDICINE II

• Department: Medicine
• 0 points

INTRODUCTION TO MEDIATION

INTRO TO MEDIATION (NECR ONLY)

This required NECR course will introduce the concepts and skills of mediation, a type of third-party conflict intervention. This course will provide students with theory, research, and practice to effectively use mediation skills in a wide variety of contexts. Mediation practices are frequently applied to a variety of conflicts and are employed in conflict resolution strategies. Thus it is imperative for a conflict resolution practitioner to develop knowledge and skills of this practice. In this course students will be introduced to mediation philosophies, approaches, applications, and skills through readings, scholarly reflections, role-plays, a collaborative group project, and a term paper. This course will provide a deeper understanding of problem-solving and relational styles of mediation and the goals aligned with each. Students will learn to identify when mediation is appropriate, prepare for a mediation, employ communication skills, deal with negative emotions, address ethical dilemmas, and consider the cultural influences surrounding the parties and conflict.
Prerequisite: NECR 5105 Introduction to Negotiation
.

• Department: Negotiation & Conflict Resolution
• R 6:10 p.m.-8 p.m.
• MTWRF 9:30 a.m.-3:30 p.m.
• Instructor: Michele Riley
  Info
• Instructor: Yxa J Bazan
  Info
• 3 points

THE BODY IN HEALTH & DISEASE I

• Department: Medicine
• 0 points

Negotiation for Everyday Use

In this course, we will explore negotiation from several points of view and approaches. We will also look at characteristics that impact the quality of our negotiations and the outcomes, such as the role of emotions, cultural considerations, effectiveness of our communication, and opportunities to seek out negotiation to transform relationships. The course will be a blend of concepts and skills, theory and practice. On some occasions, you will be introduced to a concept and then asked to apply those concepts in an experiential activity. At other times, you will be asked to engage the activity or simulation and then the concepts will be elicited based on your experience. You will have several opportunities to practice developing your skills throughout the course, in terms of enhancing your practice and honing your analytical and conceptual understanding.

• Department: Negotiation & Conflict Resolution
• M 6:10 p.m.-8 p.m.
• Instructor: Clarence D Jr. Coaxum
  Info
• 3 points

Negotiation for Everyday Use

In this course, we will explore negotiation from several points of view and approaches. We will also look at characteristics that impact the quality of our negotiations and the outcomes, such as the role of emotions, cultural considerations, effectiveness of our communication, and opportunities to seek out negotiation to transform relationships. The course will be a blend of concepts and skills, theory and practice. On some occasions, you will be introduced to a concept and then asked to apply those concepts in an experiential activity. At other times, you will be asked to engage the activity or simulation and then the concepts will be elicited based on your experience. You will have several opportunities to practice developing your skills throughout the course, in terms of enhancing your practice and honing your analytical and conceptual understanding.

• Department: Auditing
• M 6:10 p.m.-8 p.m.
• Instructor: Clarence D Jr. Coaxum
  Info
• 0 points

PRACTICUM: FACILITATING NARRATIVE MEDICI

PRACTICUM: FACILITATING W

TBA

• Department: Narrative Medicine
• F 10:10 a.m.-noon
• 3 points

The Camera as Historian: Photography and

The emergence of photography in the early nineteenth century was a technological revolution, as significant as the print revolution. This course aims to introduce students to French history through public and private uses of photography and this medium’s relationship to artistic, social and political issues. Historical episodes include the craze for photographs in the Second Empire, the birth of war photography, the relationship between photographic identity and national security, the practice of militant images in the interwar period, and the representation of crimes against humanity. In addition to readings of academic texts and photographs, the study of diaries, letters, and novels written by photographers, poets, and writers will bring additional perspective that is closer to the photographic experience itself. The course’s organization will encourage students to explore the role of private and public organizations as well as various printed forms in disseminating and giving meaning to photographs. Students will learn the language of formal description and hone skills in cultural and historical analysis. Ultimately, students will be asked throughout the course what, if anything, distinguishes a photographic “document” from a photographic “artwork” or from a visual “archive”.

• Department: French
• Instructor: Jean-Philippe Dedieu
  Info
• 3 points

Freedom Times: Postcoloniality and decol

FREEDOM TIMES

This course will examine some of the major debates, contested genealogies, epistemic and political interventions, and possible futures of the body of writing that has come to be known as postcolonial theory, in relation to histories and practices of decolonization. The course title, “Freedom Times,” is adapted from Gary Wilder’s
Freedom Time: Negritude, Decolonization, and the Future of the World
(2015); the plural,
freedom times,
gestures toward our consideration of multiple and successive moments in which liberation from colonial or imperial rule has been imagined and fought for. What did the mid-20th century theorists of Negritude whom Wilder analyzes mean by “decolonization,” and how do those aspirations differ from those working for “decolonization” around the world today? How do these different struggles draw from – or talk past or even repudiate – one another? How do they imagine the relationship between politics and aesthetics, or (following Frantz Fanon) national liberation and national culture? Or think beyond the nation?   We’ll discuss foundational texts associated with multiple European empires (French, as well as British and Portuguese), with some particular attention to Paris as a site of postcoloniality. One goal of the course will be to develop a historical understanding of key debates and longstanding concerns in postcolonial studies that will help us to contextualize contemporary discussions in France about colonial/imperial history, postcolonial citizenship, and the ongoing transformation of cultural institutions and civic life. Our syllabus will be a mix of literary and theoretical texts, and at least two films (
The Battle of Algiers
and
Bamako).
We’ll consider what counts as “theory” in postcolonial theory: in what ways have novels, memoirs, films, or revolutionary manifestos, for example, offered seminal, generalizable statements about the colonial and postcolonial condition?

• Department: French
• Instructor: Jennifer Wenzel
  CULPA: 3 h-index: 15 Info
• 3 points

Aesthetics and Philosophy of History

Aesthetics and Phil of Hi

None

• Department: French
• Instructor: Christine Valero
  Info
• 3 points

MARKETING RESEARCH

Understanding customers is vital for any business to meet financial goals. Marketing research helps companies gain valuable insights about the most important people in the world: their customers.  Marketing research can inform managers about consumer attitudes, buying behaviors, product and service preferences, communication messages, and distribution channels in order for management to forecast the size of the opportunity, to minimize risk in the decision-making process, to determine what is working/not working and how to best allocate and prioritize resources.

• Department: School of Professional Studies (DVSP)
• M 6:10 p.m.-8 p.m.
• Instructor: Andrew Blum
  Info
• 3 points

SCHEDULNG FOR MODERN CONSTRUCTION

A comprehensive introduction to the principles, methods and tools required for the development and implementation of scheduling in the construction industry. Topics covered include: the crucial role of the scheduling development plans, budgeting and its impact on project timelines, identification and analysis of critical paths (CPM), resource and cost loading, schedule updating, and schedule management. Coursework is integrated with hands‐on utilization of Oracle Primavera P3 and P6 scheduling and Microsoft Project 2007 software. Students may need to bring their own laptops/notebooks for some class sessions. Guest lecturers may be featured for certain topics.

OBJECTIVE:
 This course should prepare the student to prepare a CPM schedule, calculate the schedule manually or by use of computer software, evaluate the output of such software, and present such analysis both to field personnel for implementation and to upper management for overview.

• Department: Construction Administration
• M 6:10 p.m.-8 p.m.
• Instructor: Sadia I Janjua
  Info
• 1.5 points

SCREENWRITING II

• Department: Film
• W 9:30 a.m.-12:30 p.m.
• Instructor: Richard Dresser
  Info
• 3 points