History & Literature Seminar

Art Hist. prisme genre

• Department: French
• Instructor: Keithley Woolward
  Info
• 1-6 points

History & Literature Seminar

Art et Empire

• Department: French
• Instructor: Keithley Woolward
  Info
• 1-6 points

SYSTEMIC RISK

A study of financial, economic, and engineering disasters from a common systems engineering perspective, to better understand and model risk in complex process systems. Course topics will introduce process systems engineering concepts and tools such as digraphs, fault trees, probabilistic risk assessment, HAZOP, FMEA, etc., for modeling enterprise-wide risk. We will develop risk models and analyze them for real-life inspired examples and case studies. Several disaster case studies will also be discussed.

• Department: Auditing
• F 10:10 a.m.-noon
• Instructor: Venkat Venkatasubramanian
  h-index: 58 Info
• 0 points

SYSTEMIC RISK

A study of financial, economic, and engineering disasters from a common systems engineering perspective, to better understand and model risk in complex process systems. Course topics will introduce process systems engineering concepts and tools such as digraphs, fault trees, probabilistic risk assessment, HAZOP, FMEA, etc., for modeling enterprise-wide risk. We will develop risk models and analyze them for real-life inspired examples and case studies. Several disaster case studies will also be discussed.

• Department: Enterprise Risk Management
• F 10:10 a.m.-noon
• Instructor: Venkat Venkatasubramanian
  h-index: 58 Info
• 3 points

INFORMATION TECHNOLOGY RISK MANAGEMENT

IT RISK MANAGEMENT

Students will learn how to better identify and manage a wide range of IT risks as well as better inform IT investment decisions that support the business strategy. Students will develop an instinct for where to look for technological risks, and how IT risks may be contributing factors toward key business risks. This course includes a review of IT risks, including those related to governance, general controls, compliance, cybersecurity, data privacy, and project management. Students will learn how to use a risk-based approach to identify and mitigate cybersecurity and privacy related risks and vulnerabilities. No prior experience or technical skills required to successfully complete this course.

• Department: Enterprise Risk Management
• T 6:10 p.m.-8 p.m.
• M 8:10 p.m.-10 p.m.
• T 8:10 p.m.-10 p.m.
• Instructor: Shahryar Shaghaghi
  Info
• Instructor: Mike Wilkes
  Info
• Instructor: Thomas Kartanowics
  Info
• 3 points

INFORMATION TECHNOLOGY RISK MANAGEMENT

IT RISK MANAGEMENT

Students will learn how to better identify and manage a wide range of IT risks as well as better inform IT investment decisions that support the business strategy. Students will develop an instinct for where to look for technological risks, and how IT risks may be contributing factors toward key business risks. This course includes a review of IT risks, including those related to governance, general controls, compliance, cybersecurity, data privacy, and project management. Students will learn how to use a risk-based approach to identify and mitigate cybersecurity and privacy related risks and vulnerabilities. No prior experience or technical skills required to successfully complete this course.

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

CYBERSECURITY RISK MANAGEMENT

TBA

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

THIRD-PARTY RISK MANAGEMENT

As organizations increasingly rely on external vendors and service providers, managing third-party risks becomes paramount to ensure operational resilience, regulatory compliance, and strategic success. Challenges include:


The evolving nature of technology risks.

The impact of geopolitical tensions.

The lessons learned from disruptive events like pandemics.


By offering a comprehensive curriculum covering everything from the basics of vendor management to advanced predictive TPRM models and emphasizing regulatory requirements specific to the financial services sector, the course equips professionals with the knowledge and tools needed to navigate the intricate web of third-party relationships. 
Students taking this course are prohibited from taking Supply Chain Risk Management for Non-Financials (ERMC PS5585) at any time. Contact your advisor for more information.

• Department: Enterprise Risk Management
• W 6:10 p.m.-8 p.m.
• Instructor: Rod Aday
  Info
• 3 points

DIGITAL SPORTS MEDIA & MARKETING

• Department: Sports Management
• W 4:10 p.m.-6 p.m.
• Instructor: Tom Richardson
  Info
• 3 points

SUPPLY CHAIN RISK MANAGEMENT FOR NON-FIN

SUPPLY CHAIN RM FOR NON-F

The Pandemic made us all aware of the fragility of supply chains and how significant the consequences of failure of our supply chains can be. It is paramount to note that global and local economies can break down, and scarcity of essential resources can foment wars. Risk professionals must know what best practices bring security to supply chains and related companies, governments, and other institutions. 
Students taking this course are prohibited from taking Third-Party Risk Management (ERMC PS5575) at any time. Contact your advisor for more information.

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

STRATEGY AND ANALYTICS

n/a

• Department: Applied Analytics
• F 2:10 p.m.-4 p.m.
• T 8:10 p.m.-10 p.m.
• F 2:10 p.m.-4 p.m.
• F 10:10 a.m.-noon
• R 8:10 p.m.-10 p.m.
• M 6:10 p.m.-8 p.m.
• T 6:10 p.m.-8 p.m.
• W 6:10 p.m.-8 p.m.
• Instructor: Arunava Bhattacharyya
  Info
• Instructor: Ranjit Kumble
  Info
• Instructor: Peter Went
  Info
• Instructor: Lisa Godek
  Info
• Instructor: Jisang Pack
  Info
• Instructor: Panagiotis Tarhanidis
  Info
• Instructor: Sandy Balkin
  Info
• Instructor: Ashoke S Bhattacharjya
  Info
• Instructor: David Kreutter
  Info
• 3 points

STRATEGY AND ANALYTICS

STRATEGY AND ANALYTICS ONLINE

n/a

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

Intro Darkroom Photography

Introductory course to analog photographic tools, techniques, and photo criticism. This class explores black & white, analog camera photography and darkroom processing and printing.  Areascovered include camera operations, black and white darkroom work, 8x10 print production, and critique. With an emphasis on the student’s own creative practice, this course will explore the basics of photography and its history through regular shooting assignments, demonstrations, critique, lectures, and readings. No prior photography experience is required.

• Department: Visual Arts
• MW 9:30 a.m.-noon
• Instructor: Elisheva Gavra
  Info
• 3 points

PROPERTY/CASUALTY

PROPERTY & CASUALTY

• Department: Actuarial Science
• W 6:10 p.m.-8:55 p.m.
• 3 points

SOLAR PROJECT DEVELOPMENT

TBA

• Department: Sustainability Management
• T 6:10 p.m.-8 p.m.
• Instructor: Daniel J Giuffrida
  Info
• 3 points

Indigenous Oral Traditions and Anti-Colo

Through weekly readings, seminar discussions, and independent research, students will be immersed in the discourse, theoretical approaches, methods, and applications of Indigenous oral traditions and oral histories. Students will learn about the nature of oral traditions from multiple Indigenous perspectives; studying them as deeply grounded knowledge systems and world views connected to places and nations. The course will examine how colonialism has acted a great interrupter to the collective memory which is foundational to Indigenous oral traditions and nationhood. Finally, we will consider how contemporary anti-colonial Indigenous narratives are ‘remembering back’ by drawing upon and building from the stories that have (and have not) been passed down through the generations.

• Department: Oral History
• F 10:10 a.m.-1 p.m.
• 2 points

ANALYTICS & LEADING CHANGE

ANALYTICS & LEADING CHNG

• Department: Applied Analytics
• M 6:10 p.m.-8 p.m.
• Instructor: Ron Papka
  Info
• 3 points

ANALYTICS & LEADING CHANGE

ANALYTICS & LEADNG CHNG ONLINE

• Department: Applied Analytics
• M 8:10 p.m.-10 p.m.
• Instructor: Zachary Kornhauser
  Info
• 3 points

Statistics - Graduate Recitation

Statistics - Grad Recitat

This course is an introduction to probability and statistics for data science. Topics
include probability theory, probability distributions, simulations, parameters estima-
tion, hypothesis testing, simple regression. Python examples will be used throughout
the course for illustrations.

• Department: Statistics
• M 1:10 p.m.-2 p.m.
• T 12:10 p.m.-1 p.m.
• W 5:10 p.m.-6 p.m.
• 0 points

Intro to Digital Photography

Since Walter Benjamin’s concept of “work of art in the age of mechanical reproduction” (1935), photography has been continuously changed by mechanical, and then digital, means of image capture and processing. This class explores the history of the image, as a global phenomenon that accompanied industrialization, conflict, racial reckonings, and decolonization. Students will study case studies, read critical essays, and get hands-on training in capture, workflow, editing, output, and display formats using digital equipment (e.g., DSLR camera) and software (e.g., Lightroom, Photoshop, Scanning Software). Students will complete weekly assignments, a midterm project, and a final project based on research and shooting assignments. No Prerequisites and no equipment needed. All enrolled students will be able to check out Canon EOS 5D DSLR Camera; receive an Adobe Creative Cloud license; and get access to Large Format Print service.

• Department: Visual Arts
• TR 1 p.m.-3:30 p.m.
• Instructor: Paula L Lycan
  Info
• 3 points

STAT INFERENCE & MODELING

Prerequisites: (STAT GR5701) working knowledge of calculus and linear algebra (vectors and matrices), STAT GR5701 or equivalent, and familiarity with a programming language (e.g. R, Python) for statistical data analysis. In this course, we will systematically cover fundamentals of statistical inference and modeling, with special attention to models and methods that address practical data issues. The course will be focused on inference and modeling approaches such as the EM algorithm, MCMC methods and Bayesian modeling, linear regression models, generalized linear regression models, nonparametric regressions, and statistical computing. In addition, the course will provide introduction to statistical methods and modeling that addresses various practical issues such as design of experiments, analysis of time-dependent data, missing values, etc. Throughpout the course, real-data examples will be used in lecture discussion and homework problems. This course lays the statistical foundation for inference and modeling using data, preparing the MS in Data Science students, for other courses in machine learning, data mining and visualization.

• Department: Statistics
• TR 5:40 p.m.-6:55 p.m.
• Instructor: Dobrin Marchev
  Info
• 3 points

Advanced Darkroom Photography

Advanced analog photography & darkroom printing. Students will work with analog cameras and learn how to refine black-and-white printing techniques, produce larger prints, etc. Emphasis will be placed on the editing, sequencing, and display of images while cultivating a theoretical and historical context to situate the work. Students will engage with an array of photographic practices through presentations, critiques, guest artist lectures and printing assignments. This course will explore critical issues in contemporary photography and advanced camera and production techniques through regular shooting assignments, demonstrations, critique, lectures, readings, and field trips. Prerequisites:
Intro Darkroom Photography
(Columbia) or equivalent experience

• Department: Visual Arts
• TR 9:30 a.m.-noon
• Instructor: Dana N Buhl
  Info
• 3 points

PRO-SEMINAR IN FILM THEORY

• Department: Film
• F 2 p.m.-5 p.m.
• Instructor: Jason R Lariviere
  Info
• 3 points

Electrification and Decarbonization

Electricity is the lifeblood of human society. Decarbonization of global economies through electrification is seen as the most viable path for reducing GHG emissions and addressing the worst effects of climate change. Though generally accepted as the best path forward, an understanding of the operational parameters of the electric system is essential to understanding both the benefits and limitations of current and future actions. This includes the highly visible investments in renewable energy generation, less visible but equally important investments in transmission and distribution infrastructure, and the largely personal, private choices of individual households and businesses.

The course will examine pathways for the transition from fossil fuel-based electricity generation to one dominated by electricity generated by renewable energy. Students will examine the drivers of past energy transitions and various factors influencing current energy systems. At the conclusion of the course, students will be able understand the drivers of past energy transitions, the impact of those drivers on the overall energy supply chain, and how new technologies (e.g. distributed energy resources, smart meters, internet of things (IOT), etc.), consumer adoption of mass market products (e.g. Electric Vehicles, battery backup, etc,) and evolving consumer expectations (e.g. fast charging) are altering long held assumptions about energy production and use. Through this work, students will be able to infer practical steps to support current efforts to decarbonize and the potential impacts of those actions on the modern energy supply chain.

• Department: Sustainability Management
• M 4:10 p.m.-6 p.m.
• Instructor: Rory Christian
  Info
• 3 points

FINANCIAL ECONOMICS

• Department: Economics
• R 2:10 p.m.-4 p.m.
• Instructor: Pedro Tremacoldi Rossi
  Info
• 3 points

Media Archeology

“It could have been otherwise.” -Noël Burch
With this brief yet generative statement from a foundational film theorist we are introduced to a major theme of this course, a graduate level seminar concerning the still-in-formation field of media archeology. Pursuing the material traces left by false starts, wrong moves, misbegotten speculation, and dead formats, this course will dig into the historical past in order to better understand our current media ecology, prepare for the computational future, and imagine how things could be otherwise. Archeology in this sense refers to the study of a technical object through investigating its origins (its arché), as a means of breaking down traditional linear accounts of history and reconstructing them along new, more lacunary, less teleological lines. This will be our goal. We will be introduced to media archeology as both a method and an aesthetics. Our approach will look for the old in the new and the new in the old, while locating recurring topoi, ruptures, and discontinuities. Marking a departure from more hermeneutical, text-based film and media studies models, we will instead focus on questions of hardware, materiality, and physical inscription—technological research that sticks close to the signal of mediatic events, close to the metal, close to the silicon. We will perform close reading and thick description, as in established humanities disciplines like literary studies and anthropology, but with radically different, non-phenomenological, non-discursive object formations. Topics we will consider include, for example, analog waveforms and digital pulses, mathematical versus narrative modes of epistemology, and what Thomas Elsaesser calls a “poetics of obsolescence.” Our readings will draw from the corpus of media archeology studies as well as consonant fields such as material culture studies, computer engineering, and the history of science.

• Department: Film
• M 2 p.m.-5 p.m.
• Instructor: Wanda Strauven
  Info
• 3 points

POLICY AND LEGAL CONTEXT FOR SUSTAINABIL

POLICY & LEGAL CNTXT FOR

• Department: Sustainability Management
• M 6:10 p.m.-8 p.m.
• Instructor: Charlie Cibrario Assereto
  Info
• 3 points

Business and Climate Change: Law, Policy

This course will provide students with an understanding of the ways and extent to which climate change law and policy is relevant to businesses, as well as the role of sustainability professionals in practical implementation. The course is divided into several core topics, including: (i) an overview of international and U.S. climate change policy and law, including the Paris Agreement, the Inflation Reduction Act and energy transition policy support, and human rights/environmental justice; (ii) market-led, voluntary initiatives such as the Task Force on Climate-related Financial Disclosures (TCFD), and related developments including the mainstreaming of ESG investing, sustainable finance, and the proliferation of corporate net zero goals; (iii) corporate governance, shareholder activism, and the emergence of mandatory regulation on climate disclosures, such as the E.U.’s Taxonomy Regulation and the U.S. Securities & Exchange Commission’s proposed climate disclosure rule; (iv) carbon pricing, carbon markets, and “offsets”; (v) greenhouse gas emissions accounting and data challenges; and (vi) climate-related litigation and enforcement actions against corporations and financial institutions in the U.S. and other key markets, including “greenwashing” litigation and “anti- energy company boycott” investigations by several U.S. states.

• Department: Sustainability Management
• W 4:10 p.m.-6 p.m.
• 3 points

Minstrelsy and Popular Culture

Minstrelsy is one of America’s original forms of popular entertainment, and its formal, thematic, and narrative elements continue to reverberate throughout popular culture to this day. Indeed, given the close relationship between stage performance and the development of screen cultures, it should come as little surprise that many of the tropes and representational strategies that film and media adopted to portray blackness bore, and continue to bear, close relation to minstrelsy and blackface. This seminar will examine the ways that minstrelsy has played a crucial role in the evolution of American popular culture, especially in film and media. The course will focus on the complex function and legacy of minstrelsy, whether from the perspective of Jewish artists trying to establish their racial identities in early Hollywood, or African American artists attempting to subvert dominant representational modes.

• Department: Film
• T 10:10 a.m.-12:40 p.m.
• Instructor: Racquel Gates
  Info
• 3 points

STORYTELLING WITH DATA AND AI

Data does not have meaning without context and interpretation. Being able to effectively present data analytics in a compelling narrative to a particular audience will differentiate you from others in your field. This course takes students through the lifecycle of an analytical project from a communication perspective. Students develop written, verbal, and visual deliverables for three major audiences: data experts (e.g., head of analytics); consumer and presentation experts (e.g., chief marketing officer); and executive leadership (e.g., chief executive officer).

Students get ample practice in strategic interactions in relevant social and professional contexts (e.g., business meetings, team projects, and one-on-one interactions); active listening; strategic storytelling; and creating persuasive professional spoken and written messages, reports, and presentations. Throughout the course, students create and receive feedback on data storytelling while sharpening their ability to communicate complex analytics to technical and nontechnical audiences with clarity, precision, and influence.

• Department: Applied Analytics
• W 6:10 p.m.-8 p.m.
• Instructor: Scott A Spencer
  Info
• 3 points

STORYTELLING WITH DATA AND AI

STORYTELLING WITH DATA ONLINE

Data does not have meaning without context and interpretation. Being able to effectively present data analytics in a compelling narrative to a particular audience will differentiate you from others in your field. This course takes students through the lifecycle of an analytical project from a communication perspective. Students develop written, verbal, and visual deliverables for three major audiences: data experts (e.g., head of analytics); consumer and presentation experts (e.g., chief marketing officer); and executive leadership (e.g., chief executive officer).

Students get ample practice in strategic interactions in relevant social and professional contexts (e.g., business meetings, team projects, and one-on-one interactions); active listening; strategic storytelling; and creating persuasive professional spoken and written messages, reports, and presentations. Throughout the course, students create and receive feedback on data storytelling while sharpening their ability to communicate complex analytics to technical and nontechnical audiences with clarity, precision, and influence.

• Department: Applied Analytics
• W 8:10 p.m.-10 p.m.
• Instructor: Bum Chul Kwon
  h-index: None Info
• 3 points

INTERNSHIP

• Department: Film
• Instructor: Hanna Seifu
  Info
• Instructor: Maureen A Ryan
  Info
• Instructor: Jack Lechner
  Info
• Instructor: Mynette Louie
  Wikipedia Info
• 1-3 points

Topics in Nursing Practice

TOPICS IN NURSING PRACTIC

This course is designed to introduce pre-licensure students to relevant and emergent topics which affect the practice of nursing in the national and international healthcare system. The focus will be on issues confronting professional nurses including global health, cultural awareness, gender identity, and evidence-based wellness. State mandated topics for licensure will be covered.

• Department: Nursing
• 0-1 points

VISITING ARTIST LECT. II

Visiting artists and critics are invited over the course of the academic year to give a one-hour lecture followed by discussion, and conduct 3 40-minute studio visits. These lecturers will join the previously listed Visiting Critics and will be available as one of your allotted studio visits each semester.

• Department: Visual Arts
• Instructor: Miya Masaoka
  Wikipedia Info
• 0 points

ACTUARIAL METHODS

The Actuarial Methods course explores models for evaluating and managing risks of life contingent contracts, their theoretical basis and applications. Topics include survival models, life insurance and annuity benefits, premium and reserve calculations related to policies on a single life, as well as option pricing. This course also covers materials relevant to the long-term section of the Fundamentals of Actuarial Mathematics (FAM) exam of the Society of Actuaries. This is a core course of the M.S. in Actuarial Science program.

• Department: Actuarial Science
• TR 8:40 a.m.-9:55 a.m.
• Instructor: Yubo Wang
  Info
• 3 points

ADVANCED ACTUARIAL METHODS

The purpose this class is to develop the student’s knowledge of the theoretical basis of certain actuarial models and the application of those models to insurance and other financial risks. A thorough knowledge of calculus, probability, and interest theory is assumed. Knowledge of risk management at the level of Exam P is also assumed.

The combination of these two classes covers the material for the FAM-L and ALTAM examinations of the Society of Actuaries. This is a core class of the Actuarial Science program. Students who have already taken and passed the MLC or LTAM exam for SOA are exempted from this class and can substitute an elective.

• Department: Actuarial Science
• MW 10:10 a.m.-11:25 a.m.
• Instructor: Abraham Weishaus
  Info
• 3 points

ACTUARIAL MODELS

This course provides an introduction to the tools for pricing and reserving for short term insurance. We will discuss methods for calculating IBNR reserves, ratemaking, frequency and severity models used for modeling coverage modifications, statistical methods for fitting, evaluating, and selecting parametric models for frequency and severity, and three credibility methods.

This class covers the short-term material of Exam FAM and also covers the material of Exam ASTAM of the Society of Actuaries, and some of the material on Exams MAS I, MAS II, and 5 of the Casualty Actuarial Society. This is a core class of the Actuarial Science program. Students who have already taken and passed the FAM exam (or its short term portion) and the ASTAM exam administered by the SOA are exempted from this class and can substitute an elective.

• Department: Actuarial Science
• MW 1:10 p.m.-2:25 p.m.
• Instructor: Abraham Weishaus
  Info
• 3 points

Building a Scalable Business

• Department: Business
• MTWRF 9 a.m.-5 p.m.
• Instructor: Faculty
  h-index: 37 Info
• 3 points

CRITICAL ISSUES IN ART II

• Department: Visual Arts
• T 3 p.m.-5 p.m.
• Instructor: Ivana Dama
  Info
• 3 points

PREDICTIVE MODELING IN FINANCE & INSURAN

PREDICT MODLNG IN FIN & INSRNC

This course introduces to the students, generalized linear models (GLM), time series models, and some popular statistical learning models such as decision trees models as well as random forests and boosting trees.  The aim for GLM is to provide a flexible framework for the analysis and model building using the likelihood techniques for almost any data type. The aim for the statistical learning models is to build and predict or understand data structure (if unsupervised) using statistical learning methods such as tree-based for supervised learning and the Principle Component Analysis and Clustering for unsupervised learning.  It develops a student’s knowledge of the theoretical basis in predictive modeling, computational implementation of the models and their application in finance and insurance. Tools such as cross-validation and techniques such as regularization and dimension reduction for fitting and selecting models are explored.  We also implement these models using a combination of Excel and R.

The class covers the material of Exams, Statistics for Risk Modeling (SRM) and Predictive Analytics (PA) of Society of Actuaries, and some material of Exams, Modern Actuarial Statistics I (MAS-I) and MAS II by the Casualty Actuarial Society. This is a core course for the Actuarial Science students. Students who have already taken and passed the SRM and PA exams administered by the SOA are exempted from this class and can substitute an elective.

• Department: Actuarial Science
• TR 2:40 p.m.-3:55 p.m.
• Instructor: Lina Xu
  Info
• 3 points

DATA SCIENCE IN FINANCE AND INSURANCE

DATA SCIENCE IN FIN & INSURANC

This course explores machine learning models, their theoretical basis, computing implementation and applications in finance and insurance.  It discusses machine learning models for regression, classification and unsupervised learning;  tools such as cross validation and  techniques such as regularization, dimension reduction and ensemble learning;  and select algorithms for fitting machine learning models.  This course offers students an intensive hands-on experience where they combine theoretical understanding, domain knowledge and coding skills to better inform data-driven decision making.

Some topics covered are relevant to the statistical learning portion of the Society of Actuaries (SOA) and the Casualty Actuarial Society (CAS) curricula, and the quantitative methods section of the Chartered Financial Analyst (CFA) Institute curriculum.  This is a core course of the Actuarial Science program.

• Department: Actuarial Science
• TR 10:10 a.m.-11:25 a.m.
• Instructor: Yubo Wang
  Info
• 3 points

GRADUATE STUDIO II

• Department: Visual Arts
• R noon-4 p.m.
• Instructor: Miya Masaoka
  Wikipedia Info
• 3 points

GRADUATE STUDIO II

• Department: Visual Arts
• M 4 p.m.-10 p.m.
• Instructor: Miya Masaoka
  Wikipedia Info
• 3 points

Advanced Data Science Applications in Fi

Adv Data Sci App in Fin a

The Advanced Data Science Applications in Finance and Insurance course covers topics in database navigation, select advanced predictive analytics models and model interpretability. Topics include relational databases, generalized additive models, deep learning models, linear mixed models, Bayesian approaches, and interpretable machine learning.

Course discussions help students develop an understanding of the models and methodologies, as well as the ability to implement these models in R or python using opensource packages. Course assignments help students practice applying these models to financial, insurance and other data, as well as gain additional insights through validating aspects of the models. After taking this course, students will be able to apply these advanced predictive analytics models to financial and insurance data to better inform data-driven decision making by combining their theoretical understanding, domain knowledge and coding skills.

Some topics covered are relevant to the Advanced Topics in Predictive Analytics (ATPA) exam of the Society of Actuaries, and (with a more analytical emphasis) to the quantitative methods section of the CFA Program Level II exam by the CFA Institute.

Familiarity with machine learning models covered in the Data Science in Finance and Insurance course is helpful. Prior exposure to linear algebra, calculus, statistics, and a working knowledge of python, R and spreadsheets are necessary.

• Department: Actuarial Science
• TR 2:40 p.m.-3:55 p.m.
• Instructor: Yubo Wang
  Info
• 3 points

GLOBAL CAPITAL MARKET & INVESTMENT

GLOBAL CAPITAL MRKT & INVSTMNT

This course will introduce students to major issues currently of concern to all investors. It can give you the skills to conduct a sophisticated assessment of current issues and debates covered by the popular media as well as more-specialized finance journals. These skills are essential for people who pursues a financial service career, especially in today’s rapidly evolving environment. The material presented in this course are both practical important and intellectually interesting.

This course is consistent with and relevant to Chartered Financial Analyst (CFA) curriculum. It covers all subjects in CFA test and most of problems are in the same format as the CFA examination questions. This course will also provide a foundation for further study in Financial Risk Management and Financial market related courses.

• Department: Actuarial Science
• W 2:40 p.m.-5:25 p.m.
• 3 points

THESIS DEVELOPMENT SEMINAR

Prerequisites: EEEB G4850. Incoming M.A. students aiming for the thesis-based program are guided through the process of defining a research question, finding an advisor, and preparing a research proposal. By the end of the semester the students will have a written research proposal to submit to potential advisors for revision. Subject to a positive review of the research proposal, students are allowed to continue with the thesis-based program and will start working with their advisor. The course will also provide an opportunity to develop basic skills that will facilitate the reminder of the students stay at E3B and will help in their future careers.

• Department: Ecology, Evolution, and Environmental Biology
• R 10:10 a.m.-noon
• Instructor: Bekka Brodie
  Info
• 3 points

Grad Sem II in Sound Art & Related Media

The Graduate Seminar in Sound Art and Related Media is designed to create a space that is inclusive yet focused on sound as an art form and a medium. Class time is structured to support, reflect, and challenge students as individual artists and as a community. The course examines the medium and subject of sound in an expanded field, investigating its constitutive materials, exhibition and installation practices, and its ethics in the 21st century. The seminar will focus on the specific relations between tools, ideas, and meanings and the specific histories and theories that have arisen when artists engage with sound as a medium and subject in art. The seminar combines discussions of readings and artworks with presentations of students' work and research, as well as site visits and guest lectures.

 

While the Columbia Visual Arts Program is dedicated to maintaining an interdisciplinary learning environment where students are free to use and explore different mediums while also learning to look at, and critically discuss, artwork in any medium, we are equally committed to providing in-depth knowledge concerning the theories, histories, practices, tools and materials underlying these different disciplines. We offer Graduate Seminars in different disciplines, or combinations of disciplines, including moving image, new genres, painting, photography, printmaking, sculpture, as well as in Sound Art in collaboration with the Columbia Music Department through their Computer Music Center. These Discipline Seminars are taught by full-time and adjunct faculty, eminent critics, historians, curators, theorists, writers, and artists.

• Department: Visual Arts
• R 10 a.m.-noon
• Instructor: Miya Masaoka
  Wikipedia Info
• 3 points

GROUP CRITIQUE II

• Department: Visual Arts
• W 5:30 p.m.-9:30 p.m.
• 3 points

ARTIST MENTORSHIP / VALS II

This required Visual Arts core MFA curriculum course, comprising two parts, allows MFA students to deeply engage with and learn directly from a wide variety of working artists who visit the program each year.

Lecture Series
The lecture component, taught by an adjunct faculty member with a background in art history and/or curatorial studies, consists of lectures and individual studio visits by visiting artists and critics over the course of the academic year. The series is programmed by a panel of graduate Visual Arts students under the professor's close guidance. Invitations are extended to artists whose practice reflects the interests, mediums, and working methods of MFA students and the program. Weekly readings assigned by the professor provide context for upcoming visitors. Other course assignments include researching and preparing introductions and discussion questions for each of the visitors. Undergraduate students enrolled in Visual Arts courses are encouraged to attend and graduate students in Columbia's Department of Art History are also invited. Following each class-period the conversation continues informally at a reception for the visitor. Studio visits with Visual Arts MFA students take place on or around the week of the artist or critic's lecture and are coordinated and assigned by lottery by the professor.

Artist Mentorship
The Artist-Mentor component allows a close and focused relationship to form between a core group of ten to fifteen students and their mentor. Students are assigned two mentors who they meet with each semester in two separate one-week workshops. The content of each workshop varies according to the Mentors’ areas of expertise and the needs of the students. Mentor weeks can include individual critiques, group critiques, studio visits, visits to galleries, other artist's studios, museums, special site visits, readings, and writing workshops. Here are a few descriptions from recent mentors:
• During Mentor Week we will individually and collectively examine our assumptions and notions about art. What shapes our needs and expectations as artists and the impact of what we do?
• Our week will include visits to exhibition spaces to observe how the public engages the art. Throughout, we will consider art's ability to have real life consequences and the public's desire to personally engage with and experience art without mediation.
• The week will be conducted in two parts, f

• Department: Visual Arts
• T 6 p.m.-9 p.m.
• Instructor: Miya Masaoka
  Wikipedia Info
• 3 points

Geographies of Environmental Justice and

The origin of the American Environmental Justice Movement can be traced back to the emergence of the American
Civil Rights Movement of the 1960s, and more specifically to the U.S. Civil Rights Act of 1964. These historical
moments set the stage for a movement that continues to grow with present challenges and widening of economic,
health and environmental disparities between racial groups and socioeconomic groups. The environmental justice
movement builds upon the philosophy and work of environmentalism, which focuses on humanity’s adverse impact
upon the environment, entailing both human and non-human existence. However, environmental justice stresses the
manner in which adversely impacting the environment in turn adversely impacts the population of that environment.

At the heart of the environmental justice movement are the issues of racism and socioeconomic injustice.
This course will examine the intersections of race, equity, and the environment – focusing on history and the
growing role and impact of the environmental justice movement in shaping new sustainability discourses, ethics,
policies, and plans for the twenty-first century. Environmental Justice embeds various disciplines into its analytical
framework ranging from human geography and history to urban studies, economics, sociology, environmental
science, public policy, community organizing, and more. Drawing from these disciplines, as well as from recent
policies, advocacy, and regulations, students will develop a deeper understanding of equity, sustainability, social
impact, and environmental justice in places and spaces across the nation.

Building on the broadness of environmental justice and sustainability, this course will use the geography lens and
frameworks, building on the concept that geography brings together the physical and human dimensions of the
world in the study of people, places, and environments. Geography will set the stage for us to explore a variety of
environmental justice topics and issues in different regions across the nation, from the Black Belt South to the Rust
Belt to Cancer Alley, New Orleans, and Atlanta; then back to New York City and the metropolitan area, introducing
students to initiatives, policies, stakeholders, research, community groups, and advocacy involved in the
development and implementation of environmental laws, policies, practices, equity-based solutions, and sustainable
infrastructure.

• Department: Sustainability Management
• T 6:10 p.m.-8 p.m.
• Instructor: John E Williams
  Info
• 3 points

PROSEMINAR IN ACTUARIAL SCIENCE

Industry representatives conduct a series of noncredit seminar sessions designed to expose students to the actuarial profession as well as to address a range of topics in actuarial science.

• Department: Actuarial Science
• TR 4:10 p.m.-6 p.m.
• Instructor: Lina Xu
  Info
• 2 points

ERM CAPSTONE

Teams will work through a case assignment, demonstrating mastery of key learnings gained throughout the program on an integrated basis. A simulated case study is used: this is a combination of publicly-available information of an actual company and simulated ERM program details, based on a blend of current ERM programs and practices in the marketplace. Each team will assess the case study and recommend enhancements.

• Department: Enterprise Risk Management
• M 6:10 p.m.-8 p.m.
• W 8:10 p.m.-10 p.m.
• Instructor: Xue Bai
  Info
• Instructor: David P McCarthy
  Wikipedia Info
• 3 points

CAPSTONE PROJECT

TBA

• Department: Narrative Medicine
• Instructor: Catherine G Rogers
  Info
• Instructor: Alexis Almeida
  Info
• Instructor: Michael E Davidovits
  Info
• Instructor: Stephanie J Adler Yuan
  Info
• 2-4 points

SOUTH ASIA RESEARCH SEMINAR

• Department: Graduate School of Arts and Sciences
• M 10:10 a.m.-noon
• Instructor: Syantani Chatterjee
  Info
• 2-4 points

DIRECTED READINGS

Directed Readings in Ancient Studies.

• Department: Classics @Barnard
• Instructor: Ellen Morris
  CULPA: 10 Info
• 3 points

Equity Investment Management

• Department: Finance
• Instructor: Faculty
  h-index: 37 Info
• 3 points

APPLIED DEEP LEARNING AND AI

TOPIC: APPLD DEEP LEARN A

Deep Learning has become a cornerstone of Artificial Intelligence (AI), with applications in finance, healthcare, sports, autonomous vehicles, chatbots, national security, and artistic creations using elements of Natural Language Processing, Computer Vision, and Speech Recognition. Students will gain a solid foundation in Deep learning and its applications, starting with a compressed review of some Statistical Learning models followed by much deeper dive into Deep Neural Networks. Topics covered include Neural Networks, Convolutional Neural Networks (CNN), word embeddings, attention mechanisms, transformers, encoder-decoder architectures and Generative Adversarial Networks (GAN). Students will also learn training of agents to make optimal decisions in complex environments using Reinforcement Learning. Practical applications will demonstrate how to prepare, train, test, and validate these models.

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

INTERNATIONAL ECONOMICS

• Department: Economics
• T 6:10 p.m.-8 p.m.
• Instructor: Sebastian Heise
  Info
• 3 points

INDEPENDENT STUDY

• Department: Visual Arts
• Instructor: Seth Cluett
  h-index: 4 Info
• Instructor: Miya Masaoka
  Wikipedia Info
• 1-6 points

INDEPENDENT STUDY

• Department: Visual Arts
• Instructor: Daphne Arthur
  Info
• Instructor: Matthew E Buckingham
  Wikipedia Info
• Instructor: David A Cruz
  Info
• Instructor: Jon Kessler
  CULPA: 5 Wikipedia Info
• Instructor: Naeem Mohaiemen
  Wikipedia h-index: 8 Info
• Instructor: Kenny Rivero
  Info
• Instructor: Shelly Silver
  CULPA: 1 Info
• Instructor: Sable Smith
  Wikipedia Info
• Instructor: Miya Masaoka
  Wikipedia Info
• 1-3 points

Nursing Leadership and Management

NURSE LEADERSHIP & MANAGM

This course is designed to introduce concepts of leadership and management for entry-level professional nursing practice. The course addresses building cultures of quality and safety in complex health care delivery systems and introduces management theories and concepts including interprofessional communication, teamwork, delegation, and supervision.

• Department: Nursing
• T 11 a.m.-1 p.m.
• Instructor: Ana Kelly
  Info
• 2 points

Banking & Monetary Policy in the Global

• Department: Business Economics
• Instructor: Faculty
  h-index: 37 Info
• 3 points

SUPERVISED INTERSHIP IN SPORTS MANAGEMEN

• Department: Sports Management
• Instructor: Kelly Carroll
  Info
• 3 points

Human-Centered Design for Data-Driven St

HumCenDesignForDDStrat+De

Within this course, students will explore how practices from human-centered design (HCD) can be applied to the end-to-end data science workflow—problem (use case) definition, data collection & preparation, data exploration, data modeling, and communicating and visualizing the results— in order to build trust in data that is used to drive strategy and decision making and impact organizational change. Students will learn about fundamental human values and how methods from the behavioral sciences and HCD can inspire ethical use of data to drive strategy and change in the modern, data-driven workplace. Students will understand how keeping “humans in the loop” is beneficial, and they will develop a critical eye for assessing whether the data they rely on to make decisions at work is human-centric, particularly as we become more reliant on data science and artificial intelligence (AI) technologies to inform our insights, strategies, and decision making at work.

Content & Goals: Through hands-on, project-based work, students will work individually and in project teams to practice designing human-centric information and communication experiences, leveraging audience-focused data visualizations and storytelling techniques to drive a strategic workplace objective, motivating leaders and employees into action to create traceable organizational impact that benefits people. Students will have an opportunity to practice their writing and presentation skills through practical course assignments.

Logistics: This graduate-level elective course is designed for students in Information & Knowledge Strategy but is open to other students at Columbia University. This course would be relevant to students studying management and technology more broadly. The course will be delivered in person on Columbia’s campus during the spring semester.

No prerequisites.

• Department: Information & Knowledge Strat
• R 6:10 p.m.-8 p.m.
• Instructor: Blake Dicosola
  Info
• 3 points

NAVIGATING THE FUTURE OF WORK

This course is designed to provide an understanding of the critical capabilities necessary for individual, team, and organizational success in the new world of work. Based upon current economic models, students will recognize the intangible factors within teams and organizations that drive decision making, knowledge, and culture as value and valuation of the work of organizations.

Our core question is, how to start, build, and sustain leadership and organization capabilities for successfully navigating the future of work? The course will answer this question by looking at successful case examples who are demonstrably leading the way. We will bring actual leaders and entrepreneurs to the class for exchange with our class. The course will require students to work individually and in teams to build their own future of work models through unlearning and learning.

Students will study modern exemplar organizations and leaders to harness their lessons for staying competitive and successful. We will explore the changing nature of work, provide the means for better understanding what is occurring, and develop strategies for successfully navigating this new world. This course will start by analyzing how platforms, robotics, AI, automation, data, digitization, and the speed of technology has changed work. The capabilities necessary for success require both technological expertise, as well as, human skill centered around leadership, knowledge, and cultures of trust, respect and intentional inclusion. Students will participate in an “intangibles” assessment survey that will measure behaviors associated with leadership, culture, and knowledge for driving performance. This approach allows for exploring how the intangible factors behind each of these change factors impact the world of work, workforces, and workplaces.

Assignments will include determining individual work interests, skills and connecting them to organizational objectives and key results (OKR). Students will work in teams to design a future of work map and negotiate practices for their current organizations and clients.

• Department: Information & Knowledge Strat
• MTWRF 9 a.m.-5 p.m.
• 3 points

APPLIED WRITING

• Department: Narrative Medicine
• R 6:10 p.m.-9 p.m.
• 4 points

SUPERVISED PROJECT IN SPORTS MANAGEMENT

SUPERVISED PROJ IN SPORTS

Projects are research intensive and vary according to partners and specialty.

 

Advanced standing in the Sports Management program, with at least 12 points/credits (4 courses) completed is required. A student may not exceed 6 points/credits (2 courses) of Supervised Projects, or take more than 3 points/credits (1 course) per semester.

• Department: Sports Management
• T 2:10 p.m.-4 p.m.
• Instructor: Grant J Son
  Info
• 3 points

SUPERVISED PROJECT IN SPORTS MANAGEMENT

NFL SOCL JUSTC IMPACT PRACTICE

Projects are research intensive and vary according to partners and specialty.

 

Advanced standing in the Sports Management program, with at least 12 points/credits (4 courses) completed is required. A student may not exceed 6 points/credits (2 courses) of Supervised Projects, or take more than 3 points/credits (1 course) per semester.

• Department: Sports Management
• W 12:10 p.m.-2 p.m.
• Instructor: Leonard Elmore
  Info
• 3 points

SUPERVISED PROJECT IN SPORTS MANAGEMENT

SUPERVISED PROJ IN SPORTS

Projects are research intensive and vary according to partners and specialty.

 

Advanced standing in the Sports Management program, with at least 12 points/credits (4 courses) completed is required. A student may not exceed 6 points/credits (2 courses) of Supervised Projects, or take more than 3 points/credits (1 course) per semester.

• Department: Sports Management
• W 4:10 p.m.-6 p.m.
• Instructor: Leonard Elmore
  Info
• 3 points

MASTER THESIS WORKSHOP

MASTER THESIS WKSHP (1 CREDIT)

TAKEN WITH BIET 5992 Master Thesis (2-credit). 

The Workshop meets six times over four months. These sessions will assist students in starting to focus more fully on a topic and approach. During the Thesis Workshop, students will first speak informally for five minutes about a possible topic, followed by a more formal five-minute presentation and a draft of a one-page outline or abstract, proceeding to a more finalized outline or abstract. At each of these stages, students will receive feedback from the course director as well as fellow students.

• Department: Bioethics
• F 11:30 a.m.-1:30 p.m.
• Instructor: Arthur Kuflik
  Info
• 1 points