NUMERICAL METHODS IN FINANCE

Prerequisites: some familiarity with the basic principles of partial differential equations, probability and stochastic processes, and of mathematical finance as provided, e.g. in MATH W5010. Prerequisites: some familiarity with the basic principles of partial differential equations, probability and stochastic processes, and of mathematical finance as provided, e.g. in MATH W5010. Review of the basic numerical methods for partial differential equations, variational inequalities and free-boundary problems. Numerical methods for solving stochastic differential equations; random number generation, Monte Carlo techniques for evaluating path-integrals, numerical techniques for the valuation of American, path-dependent and barrier options.

• Department: Mathematics
• MW 7:40 p.m.-8:55 p.m.
• MW 5:40 p.m.-6:55 p.m.
• Instructor: Tat Sang Fung
  Info
• Instructor: Luca Capriotti
  Info
• 3 points

OBSERVING AND UNDERSTANDING SEA LEVEL CH

OBS & UNDRSTNDNG SEA LEVE

This course provides an overview of the science related to observing and understanding sea-level rise, which has a profound impact on the sustainability of coastal cities and ecosystems. In modern research, sea-level rise is viewed as a complex response of the Earth “system of systems” to climate change. Measuring ongoing sea-level change is challenging due to the great natural variability of sea level on short time scales caused by tides, weather, and ocean currents.  Interpreting measurements so that one can assess (and mitigate against) potential economic and societal impacts of sea-level rise is crucial but can be complicated, since so many Earth-system processes play a role. Some of these processes are related and others are unrelated to climate change; some of the latter are natural and others are of anthropogenic origin. Students enrolled in this course will through lectures and class discussions address topics related to the underlying observational basis for sea-level rise. Given the complexity of sea level rise, it is important for those in technical positions to understand the systems level interactions that not only lead to rising waters but also the consequences that these changes inflict on other parts of our environment. What we hear most commonly is that sea level rise will affect hundreds of millions of people living in coastal areas and make those populations susceptible to flooding. But in addition to this community effect, sea level rise also have dramatic effects on coastal habitats, leading to issue such as erosion, soil contamination, and wetland flooding, just to name a few. This course will introduce and prepare students to develop a more comprehensive and holistic approach to sea level rise. By training students to observe, measure, interpret, and begin to predict how sea level rise affects populations and communities differently, students will be in strong positions to address, mitigate, and adapt to the challenges more effectively using evidence-based approaches.

• Department: Sustainability Science
• R 4:10 p.m.-6 p.m.
• Instructor: James L Davis
  h-index: 57 Info
• 3 points

Genetics

Prerequisites: BIOL UN2005 and BIOL UN2006 or the equivalent. General genetics course focused on basic principles of transmission genetics and the application of genetic approaches to the study of biological function. Principles will be illustrated using classical and contemporary examples from prokaryote and eukaryote organisms, and the experimental discoveries at their foundation will be featured. Applications will include genetic approaches to studying animal development and human diseases.  All students must get permission from the instructor to be added from the waitlist.

• Department: Biological Sciences
• TR 10:10 a.m.-11:25 a.m.
• 3 points

PHYSICAL DIAGNOSIS

• Department: Dental and Oral Surgery
• 0 points

DECISION MODELS & MANAGEMENT

This course provides an introduction to computer-based models for decision-making.  The emphasis is on models that are widely used in diverse industries and functional areas, including finance, accounting, operations, and marketing.  Applications will include advertising planning, revenue management, asset-liability management, environmental policy modeling, portfolio optimization, and corporate risk management, among others. The applicability and usage of computer-based models have increased dramatically in recent years, due to the extraordinary improvements in computer, information and communication technologies, including not just hardware but also model-solution techniques and user interfaces.  Twenty years ago working with a model meant using an expensive mainframe computer, learning a complex programming language, and struggling to compile data by hand; the entire process was clearly marked “experts only.”  The rise of personal computers, friendly interfaces (such as spreadsheets), and large databases has made modeling far more accessible to managers.  Information has come to be recognized as a critical resource, and models play a key role in deploying this resource, in organizing and structuring information so that it can be used productively.

• Department: Sustainability Management
• M 6:10 p.m.-8 p.m.
• Instructor: Lucius J Riccio
  CULPA: 4 Info
• 3 points

DECISION MODELS & MANAGEMENT

This course provides an introduction to computer-based models for decision-making.  The emphasis is on models that are widely used in diverse industries and functional areas, including finance, accounting, operations, and marketing.  Applications will include advertising planning, revenue management, asset-liability management, environmental policy modeling, portfolio optimization, and corporate risk management, among others. The applicability and usage of computer-based models have increased dramatically in recent years, due to the extraordinary improvements in computer, information and communication technologies, including not just hardware but also model-solution techniques and user interfaces.  Twenty years ago working with a model meant using an expensive mainframe computer, learning a complex programming language, and struggling to compile data by hand; the entire process was clearly marked “experts only.”  The rise of personal computers, friendly interfaces (such as spreadsheets), and large databases has made modeling far more accessible to managers.  Information has come to be recognized as a critical resource, and models play a key role in deploying this resource, in organizing and structuring information so that it can be used productively.

• Department: Auditing
• M 6:10 p.m.-8 p.m.
• Instructor: Lucius J Riccio
  CULPA: 4 Info
• 0 points

GHG EMISSIONS: MEASURING AND MINIMIZING

GHG EMISSIONS CARBON FOOT

Global greenhouse gas (GHG) emissions are now at a record high, and the world’s scientific community agrees that continued unabated release of greenhouse gases will have catastrophic consequences. Many efforts to curb greenhouse gas emissions, both public and private, have been underway for decades, yet it is now clear that collectively these efforts are failing, and that far more concerted efforts are necessary. In December 2015, the world’s nations agreed in Paris to take actions to limit the future increase in global temperatures well below to 2°C, while pursuing efforts to limit the temperature increase even further to 1.5°C. Achieving this goal will require mitigation of greenhouse gas emissions from all sectors, both public and private. Critical to any attempt to mitigate greenhouse gas emissions is a clear, accurate understanding of the sources and levels of greenhouse gas emissions. This course will address all facets of greenhouse gas emissions accounting and reporting and will provide students with tangible skills needed to direct such efforts in the future.

Students in this course will gain hands-on experience designing and executing greenhouse gas emissions inventories for companies, financial institutions and governments employing all necessary skills including the identification of analysis boundaries,  data collection, calculation of emissions levels, and reporting of results. In-class workshops and exercises will complement papers and group assignments. A key component of this course will be critical evaluation of both existing accounting and reporting standards as well as GHG emissions reduction target setting practices.

This course will introduce many of the challenges facing carbon accounting practitioners and will require students to recommend solutions to these challenges derived through critical analysis. Classes will examine current examples of greenhouse gas reporting efforts and will allow students the opportunity to recommend improved calculation and reporting methods.

• Department: Sustainability Management
• M 6:10 p.m.-8 p.m.
• W 6:10 p.m.-8 p.m.
• M 6:10 p.m.-8 p.m.
• Instructor: Peter T Clarke
  Info
• 3 points

SECURITY ANALYSIS

Prerequisites: BUSI PS5001 Intro to Finance and BUSI PS5003 Corporate Finance or Professor Approval required. If you have not taken PS5001 or PS5003 at Columbia University, please contact the course instructor for approval. Students will learn about the valuation of publicly traded equity securities. By the end of the semester students will be able to perform fundamental analysis (bottoms-up, firm-level, business and financial analysis), prepare pro forma financial statements, estimate free cash flows and apply valuation models.

• Department: School of Professional Studies (DVSP)
• T 6:10 p.m.-8 p.m.
• Instructor: Panos Mourdoukoutas
  Wikipedia Info
• 3 points

Survey & Polling Methodology

Survey research has played a pivotal role in politics for the better part of the last century, with a wide range of campaign and public policy professionals conducting surveys to gain insight into the thoughts, feelings, and opinions of the electorate and citizenry as a whole. Since the early 2000s, the use of survey experiments has become exponentially more prevalent in the political realm as a way to assess attitudes, anticipate reactions, or measure causal relationships. Recent trends point to the growing importance of the internet and social media to conduct surveys and the linkage of survey data with the wealth of publicly available personal information as well as with information on individuals’ social and economic behavior. In this course, students will learn about the strengths and weaknesses of survey research as well as limitations associated with survey design and various analytical techniques, and they will acquire concrete knowledge of practical tools used in campaigns, advocacy, and election forecasting. Students will be introduced to a set of principles for conducting survey research and analyzing survey data that are the basis for standard practice in the field. Students will be familiarized with terminology and concepts associated with survey questionnaire design, sampling, data collection and aggregation, and survey data analysis to gain insights and to test hypotheses about the nature of human and social behavior and interaction. The course will present a framework that will enable students to evaluate the influence of different sources of error on the quality of data.

• Department: Political Analytics
• T 6:10 p.m.-8 p.m.
• Instructor: Kelly T Rader
  Info
• 2 points

ESG-ALIGNED CORPORATE GOVERNANCE

ESG-ALIGNED CORP GOVER

Environmental, social and governance issues (‘ESG’) are moving to center stage for corporate boards and executive teams.  This elective course complements management and operations courses by focusing on the perspective and roles of the board and C-suite of corporations, financial institutions and professional firms in addressing ESG risks as well as promoting and overseeing governance aligned with ESG principles. The course focuses on the interchange between the external legal, competitive, societal, environmental and policy ‘ecosystems’ corporations face (which vary around the world) and a company’s internal structure, operations and pressures. We will use the United Nations Guiding Principles on Business and Human Rights and the UN Global Compact Principles (which incorporate all aspects of ESG) as the central frameworks to explore the concept of a corporation’s responsibility to respect and remedy human rights and environmental harms.  We will also examine the Equator Principles and other frameworks that spell out good practices for project finance and other investment decisions, and reference a wide range of the myriad indices, supplier disclosure portals and benchmarks that exist in this inter-disciplinary field.  Relevant regulations, corporate law regimes and court cases will be discussed from the point of view of what business managers need to know. While most of the course will deal with companies and firms serving global, regional or national markets, several examples will deal with the question of how the ESG ecosystem affects or offers opportunities to start-ups.

• Department: Sustainability Management
• M 6:10 p.m.-8 p.m.
• R 6:10 p.m.-8 p.m.
• M 6:10 p.m.-8 p.m.
• Instructor: Jessica M Wasser
  Info
• Instructor: Adam R Gordon
  Info
• Instructor: Jessica M Wasser
  Info
• 3 points

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 Science
• R 6:10 p.m.-8 p.m.
• 3 points

GENRE STUDY: Blockbuster

• Department: Film
• R 2:10 p.m.-3:25 p.m.
• Instructor: Ronald Gregg
  CULPA: 2 Info
• 3 points

DESCRIPTING AFRICAN AMERICAN BODIES

DESCRIPTING AFR-AMRCN BODIES

This course explores representations of the impact of structural racism on health and health outcomes. In this endeavor, this course examines historical issues and theories, emphasizes critical analysis and the application of knowledge, and asks critical questions about authors’ decisions to depict illness and health in specific ways. Scholarly readings in the areas of narrative and critical race theory will not only illuminate the relationship between social conditions and health outcomes but also provide the necessary insights and concepts to articulate how authors and directors represent health risks and outcomes in cultural contexts. Written and visual texts will provide a context for reflecting on specific personal and cultural experiences with structural racism and the narrative strategies that authors employ to depict the effects of structural racism on African American bodies.

• Department: Narrative Medicine
• M 3:10 p.m.-5 p.m.
• Instructor: Aaron Oforlea
  Info
• 3 points

Listening and Seeing with the Body in Mi

Listening & Seeing w/ Bod

Long-time colleagues and friends, Mary Marshall Clark and Ann Cvetkovich will model collaborative and interdisciplinary approaches to oral history that draw on their overlapping and shared interests in oral testimony as a genre of public feeling, witness, testimony and psychoanalysis. They have both, for example, contributed to Columbia’s September 11, 2001 Oral History and Narrative and Memory project and the Covid-19 Oral History Narrative and Memory Archive project. Ann Cvetkovich, a professor of gender and sexuality studies with training in literature, brings to the mutual conversation interests in queer theory, trauma, affect, archives, and creative approaches to method, as well as experience with interviewing artists and HIV/AIDS activists. Mary Marshall, director of the Columbia Center for Oral History, brings 21 years of building oral history projects on everyday life, politics, trauma, activism and the arts. As a psychoanalyst in training, she also brings the lens of psychosocial analysis to questions of suffering, of social difference and intersectionality. 

 

In addition to readings in theory and method, the course will focus on listening to oral histories with a sample interview for shared discussion each week.  The final project for the class will provide students with an opportunity to work intensively with an interview of their choosing, and there will be brief creative exercises along the way that will allow students to workshop and share their process as listeners and visual observers to the world of memory and affect.

• Department: Oral History
• M 2:10 p.m.-5 p.m.
• 2 points

THESIS RESEARCH

This course is designed to help students select, contextualize and narrow a research topic; generate research questions and arguments; and think critically about the approaches employed in the research and writing process. This course also focuses on the vital role of citation in academic research. You will survey different citation styles, and apply appropriate citation in an annotated bibliography that relates to your research topic. Pedagogically diverse, the course involves one-to-one tutorials and workshops throughout the term. The goal of the course is to provide students with a roadmap and tools needed to produce a high quality MA thesis. Students will engage with key readings that demonstrate the epistemological, ontological and methodological debates that underpin your research areas, and discuss key theories that your thesis intends to address. We will explore frameworks for analysis and search out examples of their application in scholarship that pertains to Islamic Studies and Muslim societies. Students will develop a MA thesis proposal and annotated bibliography that will be further developed and realized during your time at the Aga Khan University. Students are asked to make a schedule of one-to-one meetings with faculty members and to provide peer feedback at points during the term. You are asked to come to the workshops and meetings prepared and ready to engage in a discussion about the key components of your research design process.

• Department: Graduate School of Arts and Sciences
• M 4:10 p.m.-6 p.m.
• Instructor: Kathryn Spellman Poots
  Info
• 4 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.
• 3 points

Program Evaluation

Political campaign managers, policymakers, lobbying firms, advocacy organizations, and other professionals operating in the political arena need to be able to distinguish effective programs from ineffectual ones. Electoral campaigns, policy-making initiatives, advocacy efforts, lobbying operations, social movement activities, and media investigations can all be assessed through a program evaluation lens, enabling improved data-based decision-making regarding whether an existing program should be continued, expanded, enhanced, or discontinued. Program evaluation techniques can also be used to assess the potential impact of new programs and to improve the effectiveness of program administration. This course focuses on methods for evaluating program designs, evidence collection, analysis, and interpretation, frameworks for decision-making, and reporting and communicating findings. Students will build upon the foundational knowledge that was established during the Strategic Thinking course and develop practical skills related to various types of program evaluation.

• Department: Political Analytics
• W 6:10 p.m.-8 p.m.
• Instructor: Sara Yeganeh
  Info
• 2 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 Science
• T 4:10 p.m.-6 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
• R 4:10 p.m.-6 p.m.
• Instructor: Nicole C Dicrecchio
  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
• W 4:10 p.m.-6 p.m.
• Instructor: Ryan 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
• R 4:10 p.m.-6 p.m.
• Instructor: Nicole C Dicrecchio
  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: Charles R 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: Charles R Riemann
  Info
• 3 points

Leadership

Successful leaders in politics, campaign management, and related professions must be able to lead change in their organizations, not only motivate and manage their teams toward a common goal. The aims that leaders seek to achieve are determined by their ability to create value, collaborate, influence, navigate uncertainty, and advance ideas, programs, and movements. In this course, students will learn about how the development of personal attributes and abilities lays the groundwork for building the core leadership competencies that are essential for high-impact management as well as changing the behavior and the culture of organizations with particular emphasis on how to successfully introduce the methods and results of analytics. Students will explore the motivations, obstacles, and interventions of change, and learn to build alliances, facilitate difficult meetings and develop a transformation plan. They will also review some of the most important academic research and business publications on change management and the implementation of analytics. The course is intended to enhance practical skills through dynamic interactions with the instructor, role-playing with classmates, and other real-world experiences.

• Department: Political Analytics
• M 6:10 p.m.-8 p.m.
• Instructor: David Wolfson
  Info
• 2 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

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: Auditing
• T 6:10 p.m.-8 p.m.
• Instructor: Ammar Belal
  Info
• 0 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 Science
• W 4:10 p.m.-6 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
• F 2:10 p.m.-4 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
• R 6:10 p.m.-8 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
• M 6:10 p.m.-8 p.m.
• Instructor: Patrick Houlihan
  Info
• 3 points

THESIS SEMINAR II

• Department: Sociology
• R 2:10 p.m.-4 p.m.
• Instructor: Denise Milstein
  CULPA: 9 h-index: 5 Info
• 3 points

APPLIED DATA SCI FOR SOC SCIENTISTS

• Department: Quantitative Methods/Social Sciences
• T 6:10 p.m.-8 p.m.
• 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
• W 6:10 p.m.-8 p.m.
• Instructor: Nicholas L Anderson
  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: Mazen Asaad
  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
• T 6:10 p.m.-8 p.m.
• Instructor: Alexander Peterhansl
  Info
• 3 points

ORAL HISTORY INTERNSHIP

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

INTRO SOCIAL DATA ANLYS II LAB

• Department: Sociology
• W 10:10 a.m.-noon
• Instructor: Mireia Triguero Roura
  Info
• 0 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
• M 7:10 p.m.-9 p.m.
• Instructor: Kevin Visconti
  Info
• 3 points

MULTIMEDIA STORYTELLING

MULTIMEDIA PRACTICE

This course is a survey of the documentary craft and industry through the lens of the documentary relationship. We will define the documentary relationship as those relations organic to the process of crafting documentary. Those can be between narrator and producer, between collaborators, and between material and meaning. We will ask questions about craft, ethics, and power within documentary work and workshop short documentary works of our own

• Department: Oral History
• W 2:10 p.m.-5 p.m.
• Instructor: Sayre Quevedo
  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 Science
• W 6:10 p.m.-8 p.m.
• Instructor: Braddock Linsley
  h-index: 42 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.
• Instructor: Lilian Ore
  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: Negotiation & Conflict Resolution
• F noon-2 p.m.
• Instructor: Susan Levin
  Info
• 3 points

APPLIED ANALYTICS IN ORGANIZATIONAL CONT

APP AN IN ORG CONTEXT

• Department: Applied Analytics
• T 6:10 p.m.-8 p.m.
• Instructor: Mani Vannan
  Info
• 3 points

VALUE-BASED ENTERPRISE RISK MANAGEMENT

VALUE-BASED ERM

Foundational ERM course. Addresses all major ERM activities: risk framework; risk governance; risk identification; risk quantification; risk decision making; and risk messaging. Introduces an advanced yet practical ERM approach based on the integration of ERM and value-based management that supports integration of ERM into decision making. Provides a context to understand the differences between (a) value-based ERM; (b) traditional ERM; and (c) traditional "silo" risk management.

• Department: Enterprise Risk Management
• T 8:10 p.m.-10 p.m.
• M 6:10 p.m.-8 p.m.
• M 8:10 p.m.-10 p.m.
• R 8:10 p.m.-10 p.m.
• T 6:10 p.m.-8 p.m.
• R 6:10 p.m.-8 p.m.
• W 6:10 p.m.-8 p.m.
• W 8:10 p.m.-10 p.m.
• T 8:10 p.m.-10 p.m.
• R 2:10 p.m.-4 p.m.
• R 8:10 p.m.-10 p.m.
• W 2:10 p.m.-4 p.m.
• Instructor: Rich Lauria
  Info
• Instructor: Duncan Campbell
  Info
• 3 points

SELF & OTHER IN CLIN ENCOUNTER

TBD

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

NONPROFIT DEVELOPMENT, FUNDRAISING, AND

NP DEVELOPMENT & FUNDRAIS

This course provides a comprehensive overview of the design, implementation and management of the components of a philanthropic program and its relationship to the financial sustainability of the nonprofit organization. It introduces the philosophical, ethical and historical underpinnings of fundraising practice, also providing the nomenclature, characteristics, and methods of gift generation and their sources, and the management and stewardship of those sources. Additionally, it examines the relationship of the organization’s mission to its strategic vision and the planning, management and impact of fundraising to the organization’s advancement and sustainability.

• Department: Non Profit Management
• R 6:10 p.m.-8 p.m.
• M 6:30 p.m.-8 p.m.
• Instructor: John Hicks
  Info
• Instructor: Ramone Segree
  CULPA: 1 Info
• 3 points

PAINTING I

• Department: Visual Arts
• F 10 a.m.-4 p.m.
• Instructor: Annette Hur
  Info
• 3 points

FICTION WORKSHOP

• Department: Writing
• W 2 p.m.-5 p.m.
• R 10 a.m.-1 p.m.
• W 4:15 p.m.-7:15 p.m.
• R 1:10 p.m.-4:10 p.m.
• Instructor: James Canon
  Wikipedia Info
• Instructor: Frances H Cha
  Info
• Instructor: Dennard T Dayle
  Info
• Instructor: Joshua Furst
  Wikipedia Info
• Instructor: Hilary J Leichter
  Info
• Instructor: Matthew Salesses
  Wikipedia 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: Charles R Guetta
  Info
• 1.5 points

Business Analytics

• Department: Decision, Risk and Operations
• Instructor: Charles R Guetta
  Info
• Instructor: Benjamin J Tubiana
  Info
• Instructor: Thomas Vladeck
  Info
• 1.5 points

UNDERSTAND CONFLICT & COOPERATION

UNDERSTAND CONFL & COOPER

• Department: Negotiation & Conflict Resolution
• T 10 a.m.-1 p.m.
• 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

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

Operations Management

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

Operations Management

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

Operations Management

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

PAINTING III

• Department: Visual Arts
• T 10 a.m.-4 p.m.
• Instructor: Kenny Rivero
  Info
• 3 points

LEGAL ISSUES IN BUILDING CONSTRUCTION

LEGAL ISSUES-BLDG CONSTR

• Department: Construction Administration
• W 6:10 p.m.-8 p.m.
• Instructor: Matthew Neuringer
  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
• R 6:10 p.m.-8 p.m.
• Instructor: Mark W Hildreth
  Info
• 1.5 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

FOUNDATIONS OF CLINICAL MED II

• Department: Medicine
• 0 points

Organizational Conflict and Mediation

Org. Conflict & Meditatio

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
• S 9 a.m.-5 p.m.
• Instructor: Michele Riley
  Info
• 3 points