SOCCER ANALYTICS

This course will examine the data collection process, application, and management practices as it applies to soccer, specifically Major League Soccer and the National Women’s Soccer League. Using soccer as a platform to explore techniques, students will develop a working knowledge of the practical applications of analysis and models used to make management decisions within an organization and a professional league. With growing global connectivity, and access to data across various international leagues, the ability to embrace in-game analytics to improve team's performance, evaluate talent, develop in-game strategies, and more efficiently manage their roster in order to create financial value for their stakeholders has become an invaluable skill.
 
In response to the sports industry turning more towards application of analytics and critical thinking skills, Soccer Analytics aims to develop students into managers who can make decisions, based on provided models, regarding both player and team valuations. Students should be able to demonstrate the capability to apply advanced critical thinking skills to sports business issues and have the ability to integrate objective analysis with subjective judgment in a way that adds value to decision processes.
 
The class will be taught through a combination of lectures, class discussion, group presentations and guest speakers.  Each class will include a review of the reading assignments noted in the syllabus, and students are expected to be fully prepared.  Students are required to read assignments from the texts as well as additional sources provided by the professor. Students must attend class prepared to engage in discussions; have, articulate and defend a point of view; and ask questions and provide comments based on their reading.

• Department: Sports Management
• W 8:10 p.m.-10 p.m.
• Instructor: Caleb K Shreve
  Info
• 3 points

SUSTAINABLE INVESTING & ECONOMIC GROWTH

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

LAW & BIOETHICS

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

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

• Department: Bioethics
• M noon-2 p.m.
• Instructor: Susan Regan
  Info
• 3 points

LAW & BIOETHICS

LAW & BIOETHICS (ONLINE)

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

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

• Department: Bioethics
• T 8 p.m.-10 p.m.
• Instructor: David N Hoffman
  h-index: 2 Info
• 3 points

DIGITAL COMMUNICATION STRATEGY

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

• Department: Strategic Communication
• M 6:10 p.m.-8 p.m.
• Instructor: Lilian Ore
  Info
• 3 points

SPORTS ENTREPRENEURSHIP

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

MACHINE LEARNING: CONCEPTS & APPLICATION

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

DEIA AT WORK: LEADING INCLUSIVE ORGS

Knowledge and experience in the practice of DEIA has become a key requirement for managers and leaders. This course prepares students to manage and lead the practice of DEIA in core business functions, as directors of DEIA offices/initiatives or as DEIA champions within their organizations. It will equip students with an understanding of the advantages and challenges of leading diverse teams and will provide the knowledge, critical analysis, and practical tools required to lead inclusive organizations. It provides a framework and strategic foundation for driving an organization through the stages of gaining awareness about DEIA, practicing DEIA, and amplifying the work of equity and inclusion beyond the workplace. Students will be expected to participate in class discussions and will work on diverse teams to develop a DEIA organizational strategy.

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

DEIA AT WORK: LEADING INCLUSIVE ORGS

Knowledge and experience in the practice of DEIA has become a key requirement for managers and leaders. This course prepares students to manage and lead the practice of DEIA in core business functions, as directors of DEIA offices/initiatives or as DEIA champions within their organizations. It will equip students with an understanding of the advantages and challenges of leading diverse teams and will provide the knowledge, critical analysis, and practical tools required to lead inclusive organizations. It provides a framework and strategic foundation for driving an organization through the stages of gaining awareness about DEIA, practicing DEIA, and amplifying the work of equity and inclusion beyond the workplace. Students will be expected to participate in class discussions and will work on diverse teams to develop a DEIA organizational strategy.

• Department: Auditing
• W 6:10 p.m.-8 p.m.
• Instructor: Erwin Vincent de Leon
  Info
• 0 points

DIGITAL PRODUCT INNOVATION & ENTREPRENEU

DGTL PROD INNOV & ENTRPRN

The exponential growth of information and data—combined with software that can understand and learn from experience—provides entrepreneurs with tremendous opportunities to bring innovative customer-focused solutions to market. While there are no direct paths to bring a new product idea to market, there are easily identifiable milestones that can guide the way from idea generation to product profitability. This course will explore the process of early-stage development of knowledge-driven, data-intensive digital products like Spotify, Netflix, Watson, and TripAdvisor. The goal is to create a hands-on entrepreneurial experience at its most elemental and visceral level—ideation, brainstorming, interacting with customers, building a founding team, developing a business model, managing risk, investigating competitors, pitching the business to potential investors, and creating an interactive mobile app prototype (a design proof of concept for your business idea) through an iterative user-centered design process.

In this course, we use Eric Reis’ startup method from his book, Lean Startup, as a foundation for creating and testing new ideas. Students learn to validate their new product ideas in the market by immediately engaging with customers to gauge whether their idea solves a problem better than alternative solutions. Building on the insight generated by customer interviews, students design a business model using the Lean Canvas approach designed by Ash Maurya and iterate their ideas based on Design Thinking (Tim Brown) principles. Throughout the course, we will shift from learning to the rapid application of new frameworks to speed up product design and development.

Students will be exposed to all the pressures and demands of real-world start-ups by participating in teams tasked with creating weekly deliverables required to launch a new business. The user-experience skills and methods that are taught in this class are in demand by employers and startups across nearly every industry and reflect the latest best practices used to create today’s most widely used and award-winning digital products. The skills developed in this class apply to many real-world business problems that require an agile and iterative approach.

• Department: Auditing
• T 8:10 p.m.-10 p.m.
• Instructor: Ralph Poole
  h-index: 0 Info
• 0 points

DIGITAL PRODUCT INNOVATION & ENTREPRENEU

DGTL PROD INNOV & ENTRPRN

The exponential growth of information and data—combined with software that can understand and learn from experience—provides entrepreneurs with tremendous opportunities to bring innovative customer-focused solutions to market. While there are no direct paths to bring a new product idea to market, there are easily identifiable milestones that can guide the way from idea generation to product profitability. This course will explore the process of early-stage development of knowledge-driven, data-intensive digital products like Spotify, Netflix, Watson, and TripAdvisor. The goal is to create a hands-on entrepreneurial experience at its most elemental and visceral level—ideation, brainstorming, interacting with customers, building a founding team, developing a business model, managing risk, investigating competitors, pitching the business to potential investors, and creating an interactive mobile app prototype (a design proof of concept for your business idea) through an iterative user-centered design process.

In this course, we use Eric Reis’ startup method from his book, Lean Startup, as a foundation for creating and testing new ideas. Students learn to validate their new product ideas in the market by immediately engaging with customers to gauge whether their idea solves a problem better than alternative solutions. Building on the insight generated by customer interviews, students design a business model using the Lean Canvas approach designed by Ash Maurya and iterate their ideas based on Design Thinking (Tim Brown) principles. Throughout the course, we will shift from learning to the rapid application of new frameworks to speed up product design and development.

Students will be exposed to all the pressures and demands of real-world start-ups by participating in teams tasked with creating weekly deliverables required to launch a new business. The user-experience skills and methods that are taught in this class are in demand by employers and startups across nearly every industry and reflect the latest best practices used to create today’s most widely used and award-winning digital products. The skills developed in this class apply to many real-world business problems that require an agile and iterative approach.

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

REPRODUCTIVE ETHICS

• Department: Bioethics
• R 12:30 p.m.-2:30 p.m.
• Instructor: Arthur Kuflik
  Info
• 3 points

OPERATIONAL RISK MANAGEMENT

OPERATIONAL RISK MGMT

Review of the types of operational risks, such as technology risk (e.g., cyber-security), human resources risk, disasters, etc. Includes case studies, risk analysis frameworks and metrics, and common mitigation techniques, such as insurance, IT mitigation, business continuing planning, etc.

• Department: Enterprise Risk Management
• R 6:10 p.m.-8 p.m.
• W 6:10 p.m.-8 p.m.
• M 6:10 p.m.-8 p.m.
• R 8:10 p.m.-10 p.m.
• Instructor: Prasad Kodali
  Info
• Instructor: Rossano Rossi
  Info
• Instructor: Francis Tobin
  Info
• Instructor: Sherry L Stevens
  Info
• 3 points

OPERATIONAL RISK MANAGEMENT

Review of the types of operational risks, such as technology risk (e.g., cyber-security), human resources risk, disasters, etc. Includes case studies, risk analysis frameworks and metrics, and common mitigation techniques, such as insurance, IT mitigation, business continuing planning, etc.

• Department: Auditing
• R 8:10 p.m.-10 p.m.
• Instructor: Saba Zahid
  Info
• 0 points

OPERATIONAL RISK MANAGEMENT

OPERATIONAL RISK MGMT (ONLINE)

Review of the types of operational risks, such as technology risk (e.g., cyber-security), human resources risk, disasters, etc. Includes case studies, risk analysis frameworks and metrics, and common mitigation techniques, such as insurance, IT mitigation, business continuing planning, etc.

• Department: Enterprise Risk Management
• R 8:10 p.m.-10 p.m.
• Instructor: Saba Zahid
  Info
• 3 points

INTRO TO QUANTITATIVE RISK MANAGEMENT

INTRO TO QUANT RISK MGMT

Students without a strong math background will require significant additional time and effort to achieve the learning objectives and work through the course assignments. This course builds a foundation in the mathematics and statistics of risk management. Students are empowered to understand the output of quantitative analysts and to do their own analytics. Concepts are presented in Excel and students will have the opportunity to practice those concepts in Excel, R or Python. This course is a required prerequisite for registering for the following courses: Financial Risk Management, Insurance Risk Management, ERM Modeling.

• Department: Enterprise Risk Management
• R 6:10 p.m.-8 p.m.
• Instructor: David Weltz
  Info
• 3 points

INTRO TO QUANTITATIVE RISK MANAGEMENT

Students without a strong math background will require significant additional time and effort to achieve the learning objectives and work through the course assignments. This course builds a foundation in the mathematics and statistics of risk management. Students are empowered to understand the output of quantitative analysts and to do their own analytics. Concepts are presented in Excel and students will have the opportunity to practice those concepts in Excel, R or Python. This course is a required prerequisite for registering for the following courses: Financial Risk Management, Insurance Risk Management, ERM Modeling.

• Department: Auditing
• R 6:10 p.m.-8 p.m.
• Instructor: David Weltz
  Info
• 0 points

INTRO TO QUANTITATIVE RISK MANAGEMENT

INTRO TO QRM (ONLINE)

Students without a strong math background will require significant additional time and effort to achieve the learning objectives and work through the course assignments. This course builds a foundation in the mathematics and statistics of risk management. Students are empowered to understand the output of quantitative analysts and to do their own analytics. Concepts are presented in Excel and students will have the opportunity to practice those concepts in Excel, R or Python. This course is a required prerequisite for registering for the following courses: Financial Risk Management, Insurance Risk Management, ERM Modeling.

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

FUNDAMENTALS OF SPORTS ANALYTICS

• Department: Sports Management
• M 6:10 p.m.-8 p.m.
• Instructor: Joanna Levy
  Info
• 3 points

DISABILITY & BIOETHICS

This course offers students a context from which to examine "disability" and "disability studies" from the perspectives of bioethics.  What can we learn when we put these two ever-broadening disciplines into conversation?   Throughout the course, we will endeavor to connect academic texts and theories to real-world dilemmas, with a focus on lived experience and the social contexts of disability. Our aims are not only to read, analyze, and communicate in academic styles but also to identify, understand, and communicate the relevance of both bioethics and disability studies as they apply to broader societal structures, including medicine, public health, law, politics, and beyond.

• Department: Bioethics
• M 4 p.m.-6 p.m.
• Instructor: Sara M Bergstresser
  h-index: 5 Info
• 3 points

CODING FOR RISK MANAGEMENT

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

• Department: Enterprise Risk Management
• W 6:10 p.m.-8 p.m.
• T 6:10 p.m.-8 p.m.
• Instructor: Marcus Eich
  Info
• 3 points

FINANCIAL RISK MANAGEMENT

FINANCIAL RISK MGMT

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

• Department: Enterprise Risk Management
• R 8:10 p.m.-10 p.m.
• T 8:10 p.m.-10 p.m.
• R 6:10 p.m.-8 p.m.
• Instructor: Zava Aydemir
  Info
• Instructor: Phillip E Toth
  Info
• Instructor: Igor Axenov
  Info
• 3 points

FINANCIAL RISK MANAGEMENT

FINANCIAL RISK MGMT (ONLINE)

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

• Department: Enterprise Risk Management
• W 6:10 p.m.-8 p.m.
• W 8:10 p.m.-10 p.m.
• Instructor: David J Romoff
  Info
• Instructor: Justin Hon
  Info
• 3 points

MATH MTHDS-FIN PRICE ANALYSIS

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

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

EMBODIED BORDERLANDS

• Department: Narrative Medicine
• W 12:10 p.m.-2 p.m.
• 3 points

SPORT ACCOUNTING & FINANCE

• Department: Sports Management
• T 6:10 p.m.-8 p.m.
• Instructor: Michael Parker
  Info
• 3 points

HOPE, MEANING AND ETHICS IN CLINICAL CAR

HOPE, MEANING & ETHICS CLIN CR

• Department: Bioethics
• W 6 p.m.-7:50 p.m.
• Instructor: Linda S Golding
  Info
• 3 points

FUNDRAISING FUNDAMENTALS FOR NONPROFITS

FUNDRAISING FUND FOR NP

This course provides a comprehensive overview of fundraising and development in the nonprofit sector and introduces students to basic terminology and concepts in the field. The various fundraising vehicles are surveyed and participants learn to apply fundraising strategies as they balance individual donor and institutional needs. Relationship building, the solicitation process, the psychological dynamics and the realities of asking for money are examined as students refine their skills through analysis of case studies and participation in role playing exercises. A full array of written formats used by fundraising professionals including mission statements, grant proposals, acknowledgment letters, and campaign appeal materials are introduced. While students develop an understanding of the essentials of fundraising operations, they also examine the larger issues confronting today’s fundraising managers as well as explore the relationships between fundraisers and a nonprofit organization’s management structure and other stakeholders.

• Department: Non Profit Management
• T 6:10 p.m.-8 p.m.
• Instructor: John Hicks
  Info
• 3 points

FUNDRAISING FUNDAMENTALS FOR NONPROFITS

This course provides a comprehensive overview of fundraising and development in the nonprofit sector and introduces students to basic terminology and concepts in the field. The various fundraising vehicles are surveyed and participants learn to apply fundraising strategies as they balance individual donor and institutional needs. Relationship building, the solicitation process, the psychological dynamics and the realities of asking for money are examined as students refine their skills through analysis of case studies and participation in role playing exercises. A full array of written formats used by fundraising professionals including mission statements, grant proposals, acknowledgment letters, and campaign appeal materials are introduced. While students develop an understanding of the essentials of fundraising operations, they also examine the larger issues confronting today’s fundraising managers as well as explore the relationships between fundraisers and a nonprofit organization’s management structure and other stakeholders.

• Department: Auditing
• M 6:30 p.m.-8 p.m.
• T 6:10 p.m.-8 p.m.
• Instructor: Ramone Segree
  CULPA: 1 Info
• Instructor: John Hicks
  Info
• 0 points

FUNDRAISING FUNDAMENTALS FOR NONPROFITS

FUNDRAISING FUND FOR NP

This course provides a comprehensive overview of fundraising and development in the nonprofit sector and introduces students to basic terminology and concepts in the field. The various fundraising vehicles are surveyed and participants learn to apply fundraising strategies as they balance individual donor and institutional needs. Relationship building, the solicitation process, the psychological dynamics and the realities of asking for money are examined as students refine their skills through analysis of case studies and participation in role playing exercises. A full array of written formats used by fundraising professionals including mission statements, grant proposals, acknowledgment letters, and campaign appeal materials are introduced. While students develop an understanding of the essentials of fundraising operations, they also examine the larger issues confronting today’s fundraising managers as well as explore the relationships between fundraisers and a nonprofit organization’s management structure and other stakeholders.

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

INSURANCE RISK MANAGEMENT

INSURANCE RISK MGMT

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

• Department: Enterprise Risk Management
• M 8:10 p.m.-10 p.m.
• Instructor: Melissa Miller
  Info
• 3 points

MULTI-ASSET PORTFOLIO MGMT

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

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

CREDIT RISK MANAGEMENT

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

• Department: Enterprise Risk Management
• R 8:10 p.m.-10 p.m.
• M 6:10 p.m.-8 p.m.
• Instructor: Rahmi E Aktug
  Info
• Instructor: Weijun Weng
  Info
• 3 points

CREDIT RISK MANAGEMENT

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

• Department: Enterprise Risk Management
• M 6:10 p.m.-8 p.m.
• Instructor: Weijun Weng
  Info
• 3 points

CAPSTONE

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

• Department: Non Profit Management
• T 6:10 p.m.-8 p.m.
• Instructor: Thomas W Watson
  Info
• 3 points

MA Mentored Research

MA MENTORED RESEARCH

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

• Department: Statistics
• Instructor: Demissie Alemayehu
  h-index: 14 Info
• 0-1 points

Statistical Fieldwork

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

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

MANAGING DATA

• Department: Applied Analytics
• M 8:10 p.m.-10 p.m.
• T 8:10 p.m.-10 p.m.
• S 10:10 a.m.-noon
• R 8:10 p.m.-10 p.m.
• R 6:10 p.m.-8 p.m.
• T 6:10 p.m.-8 p.m.
• S 12:10 p.m.-2 p.m.
• F 10:10 a.m.-noon
• R 8:10 p.m.-10 p.m.
• Instructor: Javid B Huseynov
  Info
• Instructor: Constantine Christakos
  Info
• Instructor: Darshan Desai
  Info
• Instructor: Michael A Silas
  Info
• Instructor: Gert de Geyter
  Info
• Instructor: Nitinchandra Nayak
  Info
• Instructor: Sridhar Ravula
  Info
• Instructor: Devarshi Ghoshal
  Info
• Instructor: Arash Khatibi
  Info
• 3 points

MANAGING DATA

MANAGING DATA ONLINE

• Department: Applied Analytics
• W 8:10 p.m.-10 p.m.
• R 6:10 p.m.-8 p.m.
• Instructor: Mohamed Mneimneh
  Info
• Instructor: Juan Melo
  Info
• 3 points

CLINICAL ETHICS

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

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

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

• Department: Bioethics
• W 2 p.m.-4 p.m.
• Instructor: Barbra Rothschild
  Info
• 3 points

CLINICAL ETHICS

INTRO CLINICAL ETHICS (ONLINE)

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

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

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

• Department: Bioethics
• R 9:30 a.m.-11:30 a.m.
• Instructor: Barbra Rothschild
  Info
• 3 points

RESEARCH SEMINAR IN HIST

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

• Department: French
• Instructor: Malgorzata Mazurek
  CULPA: 2 Info
• 3 points

OPERATIONS: BACKBONE OF THE COMPANY

OPERATIONS: BACKBONE OF C

• Department: Insurance Management
• Instructor: Marguerite Demartino
  Info
• 3 points

TAX PLANNING

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

• Department: Wealth Management
• Instructor: Jordan A Sprechman
  Info
• 3 points

MARKET RISK MANAGEMENT

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

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

• Department: Enterprise Risk Management
• W 8:10 p.m.-10 p.m.
• Instructor: Michael Zwecher
  Info
• 3 points

PRACTICAL PRODUCTION II

• Department: Film
• F 9 a.m.-11 a.m.
• F 11 a.m.-1 p.m.
• F 1 p.m.-3 p.m.
• Instructor: Shrihari C Sathe
  Info
• 1.5 points

LEADERSHIP IN SPORTS MANAGEMENT

LDRSHP & PERS MGMT IN SPR

TBA

• Department: Sports Management
• R 2:10 p.m.-4 p.m.
• R 6:10 p.m.-8 p.m.
• Instructor: Neal Pilson
  Wikipedia Info
• Instructor: Pamela Wheeler
  Info
• 3 points

LEADERSHIP IN SPORTS MANAGEMENT

TBA

• Department: Sports Management
• M 2:10 p.m.-4 p.m.
• M 4:10 p.m.-6 p.m.
• Instructor: Mary Wittenberg
  Info
• Instructor: Leonard Elmore
  Info
• 3 points

ECONOMETRICS II

• Department: Economics
• MW 1:10 p.m.-2:25 p.m.
• 3 points

PRINTMAKING:DRAWING INTO PRINT

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

SYMBOLIC LOGIC

Advanced introduction to classical sentential and predicate logic. No previous acquaintance with logic is required; nonetheless a willingness to master technicalities and to work at a certain level of abstraction is desirable. Note: Due to significant overlap, students may receive credit for only one of the following three courses: PHIL UN3411, UN3415, GR5415.

• Department: Philosophy
• TR 2:40 p.m.-3:55 p.m.
• Instructor: Achille Varzi
  CULPA: 30 Wikipedia h-index: 40 Info
• 4 points

ANOMALY DETECTION

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

CREDIT RISK ANALYTICS

The field of credit risk management is undergoing a quiet revolution as subjective and manually-intensive methods give way to digitization, algorithmic management, and decision-making. This course provides a practical overview and hands-on experience with different methods, and it also provides a view of future technologies and discussions of potential future directions. Participants in this course should be well-positioned to take entry-level analytic positions and help drive strategic decisions.

The first half of the course explores analytics used today for credit risk management. You will learn to create rating and scoring models and a macro scenario-based stress testing model. In the second half of the course, we explore more advanced tools used by the more prominent organizations and fintech firms, including neural net and XGBoost decision tree models.

• Department: Enterprise Risk Management
• M 6:10 p.m.-8 p.m.
• Instructor: Christopher Mann
  Info
• 3 points

PRINTMAKING I: INTAGLIO

• Department: Visual Arts
• MW 2:30 p.m.-5 p.m.
• Instructor: Jennifer Nuss
  Info
• 3 points

PRINTMAKING II: INTAGLIO

• Department: Visual Arts
• MW 2:30 p.m.-5 p.m.
• Instructor: Jennifer Nuss
  Info
• 3 points

Tech Arts: Post Production II

Tech Arts: Post Production II continues teaching the core techniques for picture and sound editing and the post production workflow process for Columbia Film MFA students. We will cover preparing for a long-form edit, digital script integration, color management and continuity, advanced trimming, and advanced finishing. The hands-on lessons and exercises will be conducted using the industry-standard Non-Linear Editing Systems, Avid Media Composer, and Davinci Resolve. Each week’s class will consist of hands-on demonstrations and self-paced practice using content created by the students and provided by the program.

• Department: Film
• R 10 a.m.-1 p.m.
• Instructor: Michael J Cacioppo Belantara
  Info
• 1.5 points

APPLIED TEXT AND NATURAL LANGUAGE ANALYT

APPLIED TXT & NAT LANG AN

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

APPLIED TEXT AND NATURAL LANGUAGE ANALYT

APPLD TXT & NAT LANG AN ONLINE

• Department: Applied Analytics
• M 6:10 p.m.-8 p.m.
• Instructor: John Ortega
  h-index: None Info
• 3 points

LIQUIDITY RISK MANAGEMENT

Indicators of companies running into hard times typically include revenue volatility, loss of key personnel, reputational damage, and increased litigation. However, company failures are frequently marked by insufficient liquidity, or the lack of cash to meet obligations. Liquidity risk is the unexpected change in a company’s cash resources or demands on such resources that results in the untimely sale of assets, and/or an inability to meet contractual demands and/or default. In extreme cases, the lack of sufficient cash creates severe losses and results in company bankruptcy.

An institution’s cash resources and obligations can and must be managed. Indeed, the field of liquidity risk management is an established part of treasury departments at sizable institutions. The regularity of cash flows and the turbulence of business and markets must be assessed and quantified. This course provides students the tools and techniques to manage all types of liquidity challenges including the need to sell assets unexpectedly in the market, or work through ‘‘run‐on-the‐bank’’ situations for financial services companies.

• Department: Enterprise Risk Management
• T 8:10 p.m.-10 p.m.
• Instructor: Joseph Dziwura
  Info
• 3 points

Machine Learning for Finance

The application of Machine Learning (ML) algorithms in the Financial industry is now commonplace, but still nascent in its potential.  This course provides an overview of ML applications for finance use cases including trading, investment management, and consumer banking. 

Students will learn how to work with financial data and how to apply ML algorithms using the data.  In addition to providing an overview of the most commonly used ML models, we will detail the regression, KNN, NLP, and time series deep learning ML models using desktop and cloud technologies. 

The course is taught in Python using Numpy, Pandas, scikit-learn and other libraries.  Basic programming knowledge in any language is required.

• Department: Mathematics
• S 2:40 p.m.-4:30 p.m.
• Instructor: Renzo Silva
  Info
• 3 points

GLOBAL ETHICS

Increasingly, issues of medical research and clinical care are posing complex ethical issues not only in the United States, but in other countries in both the industrialized and the developing world. Yet varying economic, political, social, cultural, and historical contexts shape these issues. In diverse contexts in Asia, Africa, Europe and North and South America, practices and policies, along with cultures and moral values, differ enormously. Yet ethical issues are arising not in isolation, but as part of global communities and discourses. In research, multinational pharmaceutical companies are increasingly conducting studies in both industrialized countries and the developing world, posing numerous ethical tensions. In clinical care, uses of reproductive technologies differ across national borders, leading to “reproductive tourism”. End of life care varies widely, reflecting in part differing attitudes toward death and dying. This course examines the political, economic, social, cultural, philosophical, medical, and historical roots and implications of these issues.

The course meets once a week online for an hour and a half, and offers extensive live-session interaction and post-session discussion forums to explore the various bioethical issues contemplated throughout the semester.

• Department: Bioethics
• R 4:10 p.m.-6 p.m.
• T 6 p.m.-7:45 p.m.
• Instructor: Robert L Klitzman
  Wikipedia Info
• 3 points

Price Impact Models and Applications to

Price Impact Models & App

At the end of the course, students are expected to understand how to design live trading experiments, fit price impact models and apply price impact models to a broad set of quantitative strategies. Special emphasis is placed on acquiring the ability to communicate precise assumptions and actionable results to a general audience within the finance community. The class is divided into three modules: (a) a quick primer on trading, the role of price impact in quantitative finance and the database language kdb+ (b) real-life applications of price impact models within trading teams, including optimal execution, statistical arbitrage, and liquidity risk management (c) the design and study of live trading experiments using causal inference with applications to Transaction Cost Analysis (TCA) and high frequency trading.

• Department: Mathematics
• F 10:10 a.m.-12:40 p.m.
• Instructor: Kevin Webster
  Info
• 3 points

PRINTMAKING I: SILKSCREEN

• Department: Visual Arts
• R 10 a.m.-4 p.m.
• Instructor: Emma F Hammond-Thomas
  Info
• 3 points

IMPACT FINANCE FOR SUSTAINABILITY PRACTI

IMPACT FINANCE FOR STNBLT

Impact Finance for Sustainability Practitioners

• Department: Sustainability Management
• R 6:10 p.m.-8 p.m.
• Instructor: Bhakti Mirchandani
  Info
• 3 points

CLOUD COMPUTING

Data analytics have become an essential component of business intelligence and informed decision making. Sophisticated statistical and algorithmic methodologies, generally known as data science, are now of predominant interest and focus. Yet, the underlying cloud computing platform is fundamental to the enablement of data management and analytics.

This course introduces students to cloud computing concepts and practices ranging from infrastructure and administration to services and applications. The course is primarily focused on the development of practical skills in utilizing cloud services to build distributed and scalable analytics applications. Students will have hands-on exposure to VMs (Virtual Machines), databases, storage, microservices, and AI/ML (Artificial Intelligence and Machine Learning) services through Google Cloud Platform, et al.  Cost and performance characteristics of alternative approaches will also be studied. Topics include: overview of cloud computing, cloud systems, parallel processing in the cloud, distributed storage systems, virtualization, security in the cloud, and multicore operating systems. Throughout, students will study state-of-the-art solutions for cloud computing developed by Google, Amazon, Microsoft, and IBM.

The course modules provide a blend of lecture and reading materials along with class exercises and programming assignments. While extensive programming experience is not required, students taking the course are expected to possess basic Python 3 programming skills.

The desired outcome of the course is the student’s ability to put conceptual knowledge to practical use. Whether you are taking this course for future academic research, for work in industry, or for an innovative startup idea, this course should help you master the fundamentals of cloud computing.

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

Credit Analytics

This course uses a combination of lectures and case studies to introduce students to the modern credit analytics. The objective for the course is to cover major analytic concepts, ideas with a focus on the underlying mathematics used in both credit risk management and credit valuation.  We will start from an empirical analysis of default probabilities (or PD), recovery rates and rating transitions. Then we will introduce the essential concepts of survival analysis as a scientific way to study default.  For credit portfolio we will study and compare different approaches such as CreditPortfolio View, CreditRisk+ as well as copula function approach. For valuation we will cover both single name and portfolio models.

• Department: Mathematics
• W 1:10 p.m.-3:40 p.m.
• Instructor: David X Li
  Info
• 3 points

Healthcare Analytics

Data and analytics have always been central to understanding diseases, delivering healthcare and improving patient outcomes. As far back as the 1800’s, Florence Nightingale used data and analytics to reduce the number of deaths of British soldiers in the Crimean War by two-thirds, and John Snow used data and analytics to contain the outbreak of cholera in London. Both used data visualization to communicate their findings and drive change. Today, we have a much deeper understanding of diseases and many more treatment options available. However, the adoption of advanced analytics in healthcare has not kept pace with adoption in other industry sectors, such as financial services and retail. One thing that has not changed since the days of Florence Nightingale and John Snow is the importance of clearly communicating data-driven insights for maximum impact. These lessons are evident in our current challenges with COVID, especially relating to testing, vaccination and individual behaviors. The barriers in the contemporary healthcare environment are high because the outcomes are critical, there are multiple stakeholders, and the system is siloed with discrete, and sometimes competing, needs and expectations. Healthcare is inherently human-centered. Therapeutic interventions cannot improve lives unless healthcare providers and patients adopt them. As with all applications of analytics, providing insights that are understandable and actionable is critical.

In Healthcare Analytics, students will gain a strategic understanding of the healthcare industry, knowledge of how different stakeholder groups use data and analytics to inform scientific, clinical and operational decisions, and how state of the art analytics are transforming every aspect of healthcare from how drugs are discovered and developed to how population and individual health outcomes are optimized. Students will learn how to communicate healthcare data and analyses to drive the adoption of insights by healthcare providers and patients.

Healthcare Analytics is an elective that is intended for students who are interested in learning about healthcare and analytics and students who are interested in pursuing a career using analytics in the healthcare industry sector or in healthcare consulting. This full semester course will be offered online, and is open to APAN students who have successfully completed Applied Analytics in an Organizational Context (APAN PS5100), Storytelling with Data (APAN PS5800), Strategy and Analytics (APAN

• Department: Auditing
• W 6:10 p.m.-8 p.m.
• Instructor: David Kreutter
  Info
• 0 points

Healthcare Analytics

Data and analytics have always been central to understanding diseases, delivering healthcare and improving patient outcomes. As far back as the 1800’s, Florence Nightingale used data and analytics to reduce the number of deaths of British soldiers in the Crimean War by two-thirds, and John Snow used data and analytics to contain the outbreak of cholera in London. Both used data visualization to communicate their findings and drive change. Today, we have a much deeper understanding of diseases and many more treatment options available. However, the adoption of advanced analytics in healthcare has not kept pace with adoption in other industry sectors, such as financial services and retail. One thing that has not changed since the days of Florence Nightingale and John Snow is the importance of clearly communicating data-driven insights for maximum impact. These lessons are evident in our current challenges with COVID, especially relating to testing, vaccination and individual behaviors. The barriers in the contemporary healthcare environment are high because the outcomes are critical, there are multiple stakeholders, and the system is siloed with discrete, and sometimes competing, needs and expectations. Healthcare is inherently human-centered. Therapeutic interventions cannot improve lives unless healthcare providers and patients adopt them. As with all applications of analytics, providing insights that are understandable and actionable is critical.

In Healthcare Analytics, students will gain a strategic understanding of the healthcare industry, knowledge of how different stakeholder groups use data and analytics to inform scientific, clinical and operational decisions, and how state of the art analytics are transforming every aspect of healthcare from how drugs are discovered and developed to how population and individual health outcomes are optimized. Students will learn how to communicate healthcare data and analyses to drive the adoption of insights by healthcare providers and patients.

Healthcare Analytics is an elective that is intended for students who are interested in learning about healthcare and analytics and students who are interested in pursuing a career using analytics in the healthcare industry sector or in healthcare consulting. This full semester course will be offered online, and is open to APAN students who have successfully completed Applied Analytics in an Organizational Context (APAN PS5100), Storytelling with Data (APAN PS5800), Strategy and Analytics (APAN

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

SPORTS LAW AND ETHICS

• Department: Sports Management
• W 6:10 p.m.-8 p.m.
• Instructor: Carla Varriale
  Info
• 3 points

INTRO TO BLOCKCHAIN, CRYPTO$ & ANALYTICS

BLOCKCHAINCRYPTOCURRENCY &ANL

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

CLINICAL ETHICS: END OF LIFE CARE

• Department: Bioethics
• F 9 a.m.-11 a.m.
• Instructor: David N Hoffman
  h-index: 2 Info
• 3 points

CIRCULAR ECONOMY FOR SUSTAINABILITY PROF

Throughout history, societies have discovered resources, designed and developed them into textiles,

tools and structures, and bartered and exchanged these goods based on their respective values.

Economies emerged, driven by each society’s needs and limited by the resources and technology

available to them. Over the last two centuries, global development accelerated due in large part to the

overextraction and use of finite resources, whether for energy or materials, and supported by vast

technological advancements. However, this economic model did not account for the long-term impacts of

the disposal or depletion of these finite resources and instead, carried on unreservedly in a “take-make’-

waste” manner, otherwise known as a linear economy. Despite a more profound understanding of our

planet’s available resources, the environmental impact of disposal and depletion, and the technological

advancements of the last several decades, the economic heritage of the last two centuries persists today;

which begs the question: what alternatives are there to a linear economy?

The premise of this course is that through systems-thinking, interdisciplinary solutions for an alternative

economic future are available to us. By looking at resources’ potential, we can shape alternative methods

of procurement, design, application, and create new market demands that aim to keep materials,

products and components in rotation at their highest utility and value. This elective course will delve into

both the theory of a circular economy - which would be a state of complete systemic regeneration and

restoration as well as an optimized use of resources and zero waste - and the practical applications

required in order to achieve this economic model. Achieving perfect circularity represents potentially

transformative systemic change and requires a fundamental re-think of many of our current economic

structures, systems and processes.

This is a full-semester elective course which is designed to create awareness among sustainability

leaders that those structures, systems and processes which exist today are not those which will carry us

(as rapidly as we need) into a more sustaining future. The class will be comprised of a series of lectures,

supported by readings and case-studies on business models, design thinking and materi

• Department: Sustainability Management
• M 6:10 p.m.-8 p.m.
• M 4:10 p.m.-6 p.m.
• M 6:10 p.m.-8 p.m.
• Instructor: Danielle Azoulay
  Info
• Instructor: Diana A Trushell
  Info
• Instructor: Danielle Azoulay
  Info
• 3 points

Supervised Research

Students conduct research related to biotechnology under the sponsorship of a mentor within the University. The student and the mentor determine the nature and extent of this independent study. In some laboratories, the student may be assigned to work with a postdoctoral fellow, graduate student or a senior member of the laboratory, who is in turn supervised by the mentor. The mentor is responsible for mentoring and evaluating the students progress and performance. Credits received from this course may be used to fulfill the laboratory requirement for the degree. Instructor permission required. Web site: http://www.columbia.edu/cu/biology/courses/g4500-g4503/index.html

• Department: Biological Sciences
• Instructor: Lili Yamasaki
  CULPA: 5 Info
• 3-6 points

Supervised Research

Students conduct research related to biotechnology under the sponsorship of a mentor within the University. The student and the mentor determine the nature and extent of this independent study. In some laboratories, the student may be assigned to work with a postdoctoral fellow, graduate student or a senior member of the laboratory, who is in turn supervised by the mentor. The mentor is responsible for mentoring and evaluating the students progress and performance. Credits received from this course may be used to fulfill the laboratory requirement for the degree. Instructor permission required. Web site: http://www.columbia.edu/cu/biology/courses/g4500-g4503/index.html

• Department: Biological Sciences
• Instructor: Lili Yamasaki
  CULPA: 5 Info
• 3-6 points

CAPSTONE PROJECT

CONSTRUCTION CAPSTONE PROJECT

• Department: Construction Administration
• R 6:10 p.m.-8 p.m.
• 3 points