STORYTELLING WITH DATA AND AI
STORYTELLING WITH DATA 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
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Instructor:
Gert de Geyter
Info -
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
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Instructor:
Bum Chul Kwon
h-index: None Info - 3 points
VISITING ARTIST LECT. I
The component includes scheduled studio critiques with some of New York’s most distinguished art practitioners, and is meant to offer multiple perspectives relevant to the training of contemporary artists. The Visual Arts program invites 20-25 artists and critics a semester, and each student sees at least two Visiting Critics per semester.
- Department: Visual Arts
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Instructor:
Miya Masaoka
Wikipedia Info - 0 points
SPECIAL TOPICS IN WEALTH MANAGEMENT: DIS
DISRUPTIVE TRENDS
Columbia SPS is on the forefront of leading issues in the Wealth Management
profession. This course is designed to explore disruptive trends in the Wealth
Management industry and the opportunities and challenges that may result. As the
profession evolves, our graduates will be prepared to be leaders within all business
models across wealth management. Topics include, but are not limited to,
technology, client psychology, ESG/sustainable investing, financial products,
evolving fee structures, shifting demographics, increased regulatory burdens,
democratization of financial advice, and more.
- Department: Wealth Management
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Instructor:
Matthias Kuhlmey
Info - 3 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.
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
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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
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Instructor:
Regina Dolgoarshinnykh
CULPA: 2 Info - 3 points
Advanced Predictive Modeling Application
ACTUARIAL MODELS II
This course discusses Bayesian methods for estimating linear models. We discuss three methods for estimating the Bayesian posterior: grid approximation, quadratic approximation, and Markov Chain Monte Carlo (MCMC) methods. Bayesian methods are used to estimate linear regression models and generalized linear models. We also use Bayesian methods to estimate multilevel models, also known as linear mixed models. We also estimate linear mixed models using non-Bayesian methods. We learn how to build, estimate, and evaluate these models and how to select the best one.
This class covers most of the material of Exam MAS II of the Casualty Actuarial Society. This is a core class of the Actuarial Science program. Students may take either this class or Actuarial Methods II. Those who have already taken and passed the MAS II exam for CAS are exempted from this class and can substitute an elective.
- Department: Actuarial Science
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Instructor:
Julia Valuyeva
Info - 3 points
CRIT ISSUES IN ART I
N/A
- Department: Visual Arts
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Instructor:
Miles J Scharff
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.
GRADUATE STUDIO I
N/A
- Department: Visual Arts
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Instructor:
Miya Masaoka
Wikipedia Info - 3 points
DATA SCIENCE IN FINANCE AND INSURANCE
DATA SCIENCE IN FIN & INSURANC
The Data Science in Finance and Insurance course explores machine learning models, their theoretical basis, computing implementation and applications in finance and insurance. Topics include 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. Prior exposure to linear algebra, calculus and statistics is helpful. A working knowledge of a spreadsheet program and R is a plus. Students will use spreadsheets and R for validation and prototyping and Python to implement algorithms and apply models to applicable data.
Some topics covered are also 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.
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 object-oriented programming with python, the relational theory and relational database navigation with SQL, deep learning (including traditional machine learning tasks, computer vision, recurrent networks, natural language processing, and large language models), as well as interpretable machine learning.
Some topics covered are relevant to the Advanced Topics in Predictive Analytics (ATPA) exam of the Society of Actuaries. Topics in deep learning are also relevant to the statistical learning portion of the Casualty Actuarial Society (CAS) curriculum, and the quantitative methods section of the Chartered Financial Analyst (CFA) Institute curriculum.
Familiarity with machine learning models covered in the Data Science in Finance and Insurance (ACTU PS5841) course is helpful. Prior exposure to linear algebra, calculus, statistics, and a working knowledge of python and spreadsheets are necessary.
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
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Instructor:
Leland Wei
Info - 3 points
QUANTITATIVE RISK MANAGEMENT
QUANTITATIVE RISK MGMT
Risk Management becomes more and more important in the financial industry especially after the global financial crisis. Large financial institutions are facing high regulatory pressure from the government and public. In response to this pressure, risk management in the financial industry has been transformed dramatically over the past decade. Today, about 50 percent of the function’s staff are dedicated to risk-related operational processes such as credit administration, while 15 percent work in analytics. McKinsey research suggests that by 2025, these numbers will reach 25 and 40 percent, respectively.
This course is designed to provide students with a high-level overview of modern risk management. This is then followed by an in-depth examination of the techniques and management structures used to assess and control risk, including a detailed discussion on the implementation of Value-at-Risk, which is becoming the de facto standard for measuring risk across all the major classes: market, credit, liquidity and operational.
This course is consistent with and relevant to Financial Risk Manager (FRM) curriculum. It covers majority of FRM learning objectives in the test and it is deeper in the quantitative modelling and analysis.
RISK MANAGEMENT IN P&C INSURANCE
RISK MGMT IN P&C INSURANCE
Insurance company risk management practices and requirements have evolved significantly over the last ten years, with the advances in regulation (e.g., Solvency II, NAIC ORSA) and rating agency oversight. This elective course is designed for individuals interested in moving into risk analysis roles within property and casualty (P&C) insurance, also known as general insurance. It provides a practical review of leading quantitative risk assessment and analysis practices at P&C insurance companies. The course will give you a sound understanding of quantitative risk analysis principles that will help you expand your influence in your organization and improve the way you communicate about risk to regulators, rating agencies, and boards. The course focuses on current industry practices, critical analysis skills of risk, and the development and delivery of professional work products, to influence decision makers.
The course is divided into three parts:
Introduction to P&C Insurance: you will review the unique characteristics of P&C insurers, including underwriting, claims, premiums, policy wordings, insurance law, and regulation;
Risk Analysis: you will gain a deep understanding of the key principles underlying the implementation and application of risk management within an organization, including qualitative aspects such as framework, governance and processes, as well as quantitative methods of risk measurement and modeling; and
Application: through a real life case study, you will work in a group to synthesize the quantitative risk analysis concepts with the realities of P&C insurance company information sources, develop and present a professional consulting work product to a real guest business leader from the insurance risk management community.
- Department: Actuarial Science
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Instructor:
James Maher
Info - 3 points
ORAL COMMUNICATIONS FOR ACTUARIAL PROFES
ORAL COMM FOR ACTUARIAL P
This course is a workshop in communication techniques and professional development. Students make presentations individually and in teams. Actuarial science can be complex and to be successful in the field will require effective communication skills to simplify and explain the complex. The course covers communicating effectively, professional development, structuring presentations, delivery techniques and presentations. The main objective for the course is to help students take the complex including business trends and communicate it in a manner that can be understood by the target audience. We will focus on improving communication skills, networking, interview skills, job opportunities and career development.
- Department: Actuarial Science
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Instructor:
John N Vitucci
Info - 3 points
THESIS DEVELOPMENT SEMINAR
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 student's stay at E3B and will help in their future careers.
- Department: Ecology, Evolution, and Environmental Biology
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Instructor:
Bekka Brodie
Info - 3 points
PUBLIC RELATIONS AND CORPORATE COMMUNICA
PR & CORPORATE COMMUNICATION
This elective is designed for students looking to launch careers in public relations and corporate communications across organizations, from corporate, non-profit, start-up and/or governmental institutions. Course content will provide students with a broad overview of the PR and corporate communications function and foundational communication theory, along with hands-on, tactical training in modern public relations practice. Topics covered include strategic messaging and storytelling, working with the press to generate media coverage, leveraging social media and managing reputations online, crisis communication, public relations ethics and media law, engaging internal and external audiences, and evaluating corporate communications efforts.
- Department: Strategic Communication
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Instructor:
Michael Kaye
Info - 3 points
ARTIST MENTORSHIP / VISITING ARTIST LECT
ARTIST MENTORSHIP/ VALS
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
- 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
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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
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Instructor:
Darryl Wagner
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.
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
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Instructor:
Xue Bai
Info -
Instructor:
Aristargos Christodoulou
Info -
Instructor:
Bruce Fox
Info -
Instructor:
Narae Lee
Info -
Instructor:
Richard R. Ranade
Info -
Instructor:
Yi Zuo
Info -
Instructor:
Benjamin M Perlman
Info -
Instructor:
Rich Lauria
Info -
Instructor:
David P McCarthy
Wikipedia Info - 3 points
INSURANCE RISK MANAGEMENT
- Department: Insurance Management
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Instructor:
Kenneth Radigan
Info - 3 points
Capstone in Political Analytics
The capstone course is the culminating experience for students in the Political Analytics program. Students will have the opportunity to tackle a complex, real-world political analytics challenge for a sponsoring organization. The capstone provides students with analytics experience in a “live” setting and is intended to expose students to the problems, timelines, and communications needs of actual political decision-makers. Working in small teams while being mentored by a program faculty member, students will apply core knowledge, concepts, and frameworks acquired during the program and practice the hands-on skills they have developed in their classes. Throughout the semester, student project teams will interact with the sponsoring organizations as virtual consultants, scoping the problem, acquiring the data, conducting analyses, and ultimately presenting their findings and recommendations to the project sponsor.
- Department: Political Analytics
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Instructor:
Sara Yeganeh
Info - 3 points
CAPSTONE
In the fourth semester, students will develop a comprehensive financial plan based
upon a specific client case, taking all elements of a client’s financial profile into
consideration. Students will be expected to demonstrate foundational knowledge
of all aspects of the wealth management curriculum in this course in order to
develop this financial plan. The capstone experience for this program is a dualfocus
on both the written as well as the oral components of the financial plan.
- Department: Wealth Management
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Instructor:
Jason R Papier
Info - 3 points
DATA SCIENCE CONSULTING
- Department: Applied Analytics
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Instructor:
David Shilane
Info - 3 points
APPLIED DEEP LEARNING AND AI
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
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Instructor:
Siddhartha Dalal
Info -
Instructor:
Adrian Heilbut
h-index: 13 Info - 3 points
INDEPENDENT STUDY
N/A
- Department: Visual Arts
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Instructor:
Miya Masaoka
Wikipedia Info - 1-6 points
INDEPENDENT STUDY
- Department: Visual Arts
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Instructor:
Matthew E Buckingham
Wikipedia Info -
Instructor:
David A Cruz
Info -
Instructor:
Delphine A Fawundu
Wikipedia Info -
Instructor:
Jon Kessler
CULPA: 5 Wikipedia Info -
Instructor:
Naeem Mohaiemen
Wikipedia h-index: 8 Info -
Instructor:
Sable Smith
Wikipedia Info -
Instructor:
Tomas Vu Daniel
CULPA: 4
Info
- 1-3 points
BUSINESS ANTHROPOLOGY
OVERVIEW: Business Anthropology explores how awareness and mastery of the concepts and approaches of anthropology can be used to better manage organizations. Students will develop the skills to apply ethnographic methods, cultural analysis, and anthropological frameworks to uncover hidden dynamics within organizations, enhance knowledge sharing, and drive innovation. The course is particularly valuable for any student seeking to strengthen their ability to lead complex, knowledge-driven initiatives with cultural awareness, strategic empathy, and deeper human insight.
CONTENT: Through a combination of hands-on fieldwork, case studies, and strategic analysis, students will learn to identify tacit knowledge, navigate organizational cultures, and design more human-centered, resilient knowledge strategies. Topics include: Foundations of anthropology and its relevance to organizational strategy; ethnographic methods for business insight and knowledge discovery; organizational culture, tacit knowledge, and hidden knowledge flows; power, identity, and hierarchy as factors shaping knowledge practices; bridging qualitative and quantitative intelligence for strategic advantage; applied anthropology in business innovation, design thinking, and change management.
LOGISTICS: This course is delivered in a hybrid format, with some sessions occurring on-campus and some as synchronous online sessions. Sessions meet weekly at the regularly scheduled day and time regardless of modality; the modality of each session will be available on the syllabus prior to the start of the semester. No prerequisites. Open to all graduate students.
- Department: Information & Knowledge Strat
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Instructor:
Jessica L Malloy
Info - 3 points
AI-ENHANCED FINDABILITY & SEMANTIC SYSTE
AI-EnhancedFindabil&Seman
The fusion of traditional information science principles with advanced AI technologies is revolutionizing knowledge management. This course explores how artificial intelligence, particularly Large Language Models (LLMs), is transforming information organization, retrieval, and utilization in digital environments.
Students explore the world of AI-enhanced findability, learning to architect intelligent knowledge platforms that maximize the value of structured and unstructured data. The course covers:
Large Language Models (LLMs) and their game-changing applications in information retrieval
Vector databases and cognitive search capabilities
Advanced Natural Language Processing (NLP) and semantic technologies
Knowledge graphs and how they are being used to add meaning to LLMs
Machine learning for sophisticated classification and categorization
Ethical considerations in AI-powered information systems
Through hands-on projects culminating in the design of real-world applications, students will gain practical experience in architecting AI-enhanced information systems. You'll learn to make informed decisions about integrating AI technologies into information architecture, balancing traditional methods with cutting-edge solutions.
This course is ideal for future knowledge strategists, information architects, and AI enthusiasts who want to lead the next generation of intelligent information systems. Join us to explore the intersection of AI and information science and prepare to shape the future of knowledge work.
No programming experience is required—just your curiosity and readiness to engage with the forefront of information technology.
- Department: Information & Knowledge Strat
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Instructor:
Ralph Poole
h-index: 0 Info - 3 points
APPLIED WRITING
- Department: Narrative Medicine
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Instructor:
Jenessa R Abrams
Info - 4 points
SUPERVISED PROJECT IN SPORTS MANAGEMENT
FC BAYERN MUNCH
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
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Instructor:
Grant J Son
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
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Instructor:
Dana Rosenberg
Info - 3 points
MASTER THESIS WORKSHOP
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
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Instructor:
Arthur Kuflik
Info - 1 points
LEADING LARGE COMPLEX PROJECTS
Project management has been important to many types of missions, projects, and activities for many years; however, it has been especially critical to the success of large complex projects across decades and centuries. Large complex projects span the globe across all industries and sectors. They also span concepts, product design, development, manufacturing, operations, and logistics, etc. Products may include hardware, software, services, product support, systems, and systems of systems, etc.
The primary focus of this course will be around project leadership as projects are planned and executed (project management). The course will start by recognizing the need and benefits of project management for large complex global projects, explore characteristics of project managers, and study the commonality and differences in types of projects. The course will continue with understanding the essential capabilities of project management, and analyze the variations in project lifecycles. The course will address managing risk throughout the project lifecycle, controls, and performance measurement, and maximizing the use of knowledge. Lastly, the course will visualize the future of projects and project management structure and core capabilities.
Our fundamental goal is to better prepare leaders for large complex global projects. This will be gained via readings; real-world case studies; and study, research, analysis, and exploration by the students. Therefore, the course will require students to engage in reflection, discussion, activities, and assignments aimed at personal unlearning and learning. The assignment and class discussions will be quite provocative to drive maximum learning.
- Department: Information & Knowledge Strat
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Instructor:
Gregory Robinson
Info - 3 points
MASTER THESIS (2 CREDIT)
Thesis requirement for Bioethics program. Taken with the Thesis Workshop (BIET K5991).
- Department: Bioethics
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Instructor:
Arthur Kuflik
Info - 2 points
AI AND THE KNOWLEDGE-DRIVEN ORGANIZAT
AI & THE KNOWLEDGE-DRIVEN
OVERVIEW: Artificial Intelligence is one of the most important technological developments in decades and has already begun to demonstrate significant improvements in healthcare, military, finance, retail, and the arts. In this class we will cover an intro to artificial intelligence with a specific lens on how knowledge driven organizations can benefit from AI. This course is not a coding or a computer science course, but does touch on high level concepts in statistics, data science, and software engineering, though no experience is necessary in these fields.
CONTENT & OBJECTIVES: You will learn how AI works, what are the best and worst use cases for AI, and the implications of implementing AI. As exciting as this space can be, there are real risks, ethical considerations, and new challenges that we will cover and discuss. By the end of the course, you will have a clear understanding of the possibilities with AI, how to implement AI in a knowledge driven organization, and the global nature of this technology. You will build on previous coursework of knowledge strategy and learn how AI accelerates knowledge management including search ranking, content recommendations, and people analytics.
LOGISTICS
:
Class meets once a week.
- Department: Information & Knowledge Strat
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Instructor:
Nitesh Goyal
Info -
Instructor:
Nicole Alexander
Info - 3 points
Perspectives on International and World
Persptvs on Int'l & World
This course gives students the opportunity to design their own curriculum: To attend lectures, conferences and workshops on historical topics related to their individual interests throughout Columbia University. Students may attend events of their choice, and are especially encouraged to attend those sponsored by the History Department (www.history.columbia.edu). (The Center for International History - cih.columbia.edu - and the Heyman Center for the Humanities - heymancenter.org/events/ - also have impressive calendars of events, often featuring historians.) The goal of this mini-course is to encourage students to take advantage of the many intellectual opportunities throughout the University, to gain exposure to a variety of approaches to history, and at the same time assist them in focusing on a particular area for their thesis topic.
- Department: History
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Instructor:
Line Lillevik
Info - 1-3 points
Internship in Industry - ACTU
Internship In ACTU
This asynchronous, 3-credit elective provides an immersive, supervised professional internship experience paired with structured reflection and applied academic work. Students integrate theory with practice while assessing organizational culture, ethical decision-making, feedback practices, and professional competencies. Through guided analysis and reflective assignments, students deepen self-awareness, strengthen career readiness, and clarify how their internship experience shapes future professional goals.
- Department: Actuarial Science
- 3 points
Internship in Industry - APAN
This asynchronous, 3-credit elective provides an immersive, supervised professional internship experience paired with structured reflection and applied academic work. Students integrate theory with practice while assessing organizational culture, ethical decision-making, feedback practices, and professional competencies. Through guided analysis and reflective assignments, students deepen self-awareness, strengthen career readiness, and clarify how their internship experience shapes future professional goals.
- Department: Applied Analytics
- 3 points
Internship in Industry - BIET
Internship in BIET
This asynchronous, 3-credit elective provides an immersive, supervised professional internship experience paired with structured reflection and applied academic work. Students integrate theory with practice while assessing organizational culture, ethical decision-making, feedback practices, and professional competencies. Through guided analysis and reflective assignments, students deepen self-awareness, strengthen career readiness, and clarify how their internship experience shapes future professional goals.
- Department: Bioethics
- 3 points
Internship in Industry - CNAD
Internship In CNAD
This asynchronous, 3-credit elective provides an immersive, supervised professional internship experience paired with structured reflection and applied academic work. Students integrate theory with practice while assessing organizational culture, ethical decision-making, feedback practices, and professional competencies. Through guided analysis and reflective assignments, students deepen self-awareness, strengthen career readiness, and clarify how their internship experience shapes future professional goals.
- Department: Construction Administration
- 3 points
Internship in Industry - ERM
Internship In ERM
This asynchronous, 3-credit elective provides an immersive, supervised professional internship experience paired with structured reflection and applied academic work. Students integrate theory with practice while assessing organizational culture, ethical decision-making, feedback practices, and professional competencies. Through guided analysis and reflective assignments, students deepen self-awareness, strengthen career readiness, and clarify how their internship experience shapes future professional goals.
- Department: Enterprise Risk Management
- 3 points
Internship in Industry - HCM
Internship In HCM
This asynchronous, 3-credit elective provides an immersive, supervised professional internship experience paired with structured reflection and applied academic work. Students integrate theory with practice while assessing organizational culture, ethical decision-making, feedback practices, and professional competencies. Through guided analysis and reflective assignments, students deepen self-awareness, strengthen career readiness, and clarify how their internship experience shapes future professional goals.
- Department: Human Capital Management
- 3 points
Internship in Industry - IKNS
Internship In IKNS
This asynchronous, 3-credit elective provides an immersive, supervised professional internship experience paired with structured reflection and applied academic work. Students integrate theory with practice while assessing organizational culture, ethical decision-making, feedback practices, and professional competencies. Through guided analysis and reflective assignments, students deepen self-awareness, strengthen career readiness, and clarify how their internship experience shapes future professional goals.
- Department: Information & Knowledge Strat
- 3 points
Internship in Industry - NECR
This asynchronous, 3-credit elective provides an immersive, supervised professional internship experience paired with structured reflection and applied academic work. Students integrate theory with practice while assessing organizational culture, ethical decision-making, feedback practices, and professional competencies. Through guided analysis and reflective assignments, students deepen self-awareness, strengthen career readiness, and clarify how their internship experience shapes future professional goals.
- Department: Negotiation & Conflict Resolution
- 3 points
Internship in Industry - NMED
Internship in NMED
This asynchronous, 3-credit elective provides an immersive, supervised professional internship experience paired with structured reflection and applied academic work. Students integrate theory with practice while assessing organizational culture, ethical decision-making, feedback practices, and professional competencies. Through guided analysis and reflective assignments, students deepen self-awareness, strengthen career readiness, and clarify how their internship experience shapes future professional goals.
- Department: Narrative Medicine
- 3 points
Internship in Industry - NOPM
Internship In NOPM
This asynchronous, 3-credit elective provides an immersive, supervised professional internship experience paired with structured reflection and applied academic work. Students integrate theory with practice while assessing organizational culture, ethical decision-making, feedback practices, and professional competencies. Through guided analysis and reflective assignments, students deepen self-awareness, strengthen career readiness, and clarify how their internship experience shapes future professional goals.
- Department: Non Profit Management
- 3 points
Internship in Industry - PMGT
This asynchronous, 3-credit elective provides an immersive, supervised professional internship experience paired with structured reflection and applied academic work. Students integrate theory with practice while assessing organizational culture, ethical decision-making, feedback practices, and professional competencies. Through guided analysis and reflective assignments, students deepen self-awareness, strengthen career readiness, and clarify how their internship experience shapes future professional goals.
- Department: Project Management
- 1.5 points
Internship in Industry - POAN
Internship In POAN
This asynchronous, 3-credit elective provides an immersive, supervised professional internship experience paired with structured reflection and applied academic work. Students integrate theory with practice while assessing organizational culture, ethical decision-making, feedback practices, and professional competencies. Through guided analysis and reflective assignments, students deepen self-awareness, strengthen career readiness, and clarify how their internship experience shapes future professional goals.
- Department: Political Analytics
- 3 points
Internship in Industry - SPRT
Internship in SPRT
This asynchronous, 3-credit elective provides an immersive, supervised professional internship experience paired with structured reflection and applied academic work. Students integrate theory with practice while assessing organizational culture, ethical decision-making, feedback practices, and professional competencies. Through guided analysis and reflective assignments, students deepen self-awareness, strengthen career readiness, and clarify how their internship experience shapes future professional goals.
- Department: Sports Management
- 3 points
Internship in Industry - SUMA
Internship In SUMA
This asynchronous, 3-credit elective provides an immersive, supervised professional internship experience paired with structured reflection and applied academic work. Students integrate theory with practice while assessing organizational culture, ethical decision-making, feedback practices, and professional competencies. Through guided analysis and reflective assignments, students deepen self-awareness, strengthen career readiness, and clarify how their internship experience shapes future professional goals.
- Department: Sustainability Management
- 3 points
Internship in Industry - SUSC
Internship In SUSC
This asynchronous, 3-credit elective provides an immersive, supervised professional internship experience paired with structured reflection and applied academic work. Students integrate theory with practice while assessing organizational culture, ethical decision-making, feedback practices, and professional competencies. Through guided analysis and reflective assignments, students deepen self-awareness, strengthen career readiness, and clarify how their internship experience shapes future professional goals.
- Department: Sustainability Science
- 3 points
Internship in Industry - TMGT
This asynchronous, 3-credit elective provides an immersive, supervised professional internship experience paired with structured reflection and applied academic work. Students integrate theory with practice while assessing organizational culture, ethical decision-making, feedback practices, and professional competencies. Through guided analysis and reflective assignments, students deepen self-awareness, strengthen career readiness, and clarify how their internship experience shapes future professional goals.
- Department: Technology Management
- 3 points
INDEPENDENT STUDY
This course offers students an opportunity to expand their curriculum beyond the established course offerings. Interested parties must consult with the QMSS Program Director before adding the class. This course may be taken for 2-4 points.
- Department: Quantitative Methods/Social Sciences
-
Instructor:
Gregory M Eirich
CULPA: 1 Info - 1-4 points
INDEPENDENT STUDY
Independent Study is a one- or three-credit course that can count toward the curriculum area requirement in Integrative Sustainability Management, Economics and Quantitative Analysis, Physical Dimensions, Public Policy, General and Financial Management, or Elective, with the approval of the faculty advisor. A final deliverable relating to the Sustainability Management curriculum is required at the end of the semester, and will be evaluated for a letter grade by the faculty advisor and reported to the SUMA program office.
- Department: Sustainability Management
-
Instructor:
Maria L Gray
Info - 1-3 points
INDEPENDENT STUDY
- Department: Sustainability Science
-
Instructor:
Maria L Gray
Info - 3 points
IKNS INDEPENDENT STUDY
Overview
: This 1 semester course (elective, IKNS students only, hybrid) provides an opportunity for a student to extend or supplement their educational experience via a deep-dive into an established or novel area of research of their choice (the topic), under the guidance & supervision of a faculty member (the supervisor). An independent study course allows a student to work one-on-one with a faculty member to gain & contribute new insight into the discipline of Knowledge Management.
Topic/objective
: The topic is chosen by the student as long as it falls within the general realm of Knowledge Management or its specific content areas in the IKNS curriculum, such as IT systems, knowledge organizing systems, data repositories, business data analytics including machine learning & AI, learning processes, collaboration, dialogue, team & project management, transformational leadership, change management, digital transformation, or digital product innovation. The course will therefore serve the dual purpose of allowing a student to pursue their own intellectual curiosity & to make a contribution to the wider discipline of Knowledge Management. In addition, students will deepen their understanding of the content they acquired in other courses, by applying this content to the specific topic chosen for the Independent Study.
Logistics
: Ahead of registration, the student meets with the supervisor to discuss & agree on (i) the topic & the relevant IKNS curriculum area(s); (ii) the timeline of deliverables, milestones, & contact hours for the semester; & (iii) the number of credits. The student summarizes these points in a ~1 pg
Independent Study Proposal
. The student can register for the course only once the supervisor & the Academic Director agree to & sign the
Independent Study Proposal
(which includes the topic, the IKNS curriculum area, the number of credits, & the assigned supervisor). The number of credits (1-3) will be commensurate with the scope of the Independent Study. The scope can range from a summary of existing sources (typically 1 credit. 5-10 pg report), to a synthesis or meta-analysis of existing & new sources, e.g., interviews withSMEs (typically 2 credits, 10-15 pg report), to a comprehensive study which adds the student’s own critical discussion & suggestions to the topic (typically 3 credits; 15-20 pg report).
- Department: Information & Knowledge Strat
- 1-3 points
IKNS INDEPENDENT STUDY
Overview
: This 1 semester course (elective, IKNS students only, hybrid) provides an opportunity for a student to extend or supplement their educational experience via a deep-dive into an established or novel area of research of their choice (the topic), under the guidance & supervision of a faculty member (the supervisor). An independent study course allows a student to work one-on-one with a faculty member to gain & contribute new insight into the discipline of Knowledge Management.
Topic/objective
: The topic is chosen by the student as long as it falls within the general realm of Knowledge Management or its specific content areas in the IKNS curriculum, such as IT systems, knowledge organizing systems, data repositories, business data analytics including machine learning & AI, learning processes, collaboration, dialogue, team & project management, transformational leadership, change management, digital transformation, or digital product innovation. The course will therefore serve the dual purpose of allowing a student to pursue their own intellectual curiosity & to make a contribution to the wider discipline of Knowledge Management. In addition, students will deepen their understanding of the content they acquired in other courses, by applying this content to the specific topic chosen for the Independent Study.
Logistics
: Ahead of registration, the student meets with the supervisor to discuss & agree on (i) the topic & the relevant IKNS curriculum area(s); (ii) the timeline of deliverables, milestones, & contact hours for the semester; & (iii) the number of credits. The student summarizes these points in a ~1 pg
Independent Study Proposal
. The student can register for the course only once the supervisor & the Academic Director agree to & sign the
Independent Study Proposal
(which includes the topic, the IKNS curriculum area, the number of credits, & the assigned supervisor). The number of credits (1-3) will be commensurate with the scope of the Independent Study. The scope can range from a summary of existing sources (typically 1 credit. 5-10 pg report), to a synthesis or meta-analysis of existing & new sources, e.g., interviews withSMEs (typically 2 credits, 10-15 pg report), to a comprehensive study which adds the student’s own critical discussion & suggestions to the topic (typically 3 credits; 15-20 pg report).
- Department: Information & Knowledge Strat
- 1-3 points
MASTER'S THESIS
This course fulfills the Masters Thesis requirement of the QMSS MA Program. It is designed to help you make consistent progress on your master’s thesis throughout the semester, as well as to provide structure during the writing process. The master’s thesis, upon completion, should answer a fundamental research question in the subject matter of your choice. It should be an academic paper based on data that you can acquire, clean, and analyze within a single semester, with an emphasis on clarity and policy relevance.
- Department: Quantitative Methods/Social Sciences
-
Instructor:
Elena B Krumova
Info -
Instructor:
Hadi Katesari
Info -
Instructor:
Maiko Yomogida
Info - 3-4 points
MA Research Specialization in Statistics
Research Specialization/S
Each year, approximately 10–15% of MA in Statistics students participate in on-campus academic research, contributing to advances in statistical methodology and applied areas. Some projects demonstrate exceptional promise and benefit from additional time and support for further development. The MA Research Specialization in Statistics allows qualified students to extend their MA program to a fourth semester to continue their research under the supervision of a faculty mentor. This competitive, merit-based program requires demonstrated research progress, a nomination from a faculty mentor, and an outstanding academic record. STAT GR5999 serves as the course through which students admitted to the MA Research Specialization fulfill their research requirements.
- Department: Statistics
-
Instructor:
Demissie Alemayehu
h-index: 14 Info - 6 points
Workshops in Sustainability Career Paths
Workshops in Sust Careers
The M.S. in Sustainability Management program is offering a panel workshop series, featuring SUMA alumni who will share firsthand insights into the courses that shaped their professional journeys. The workshops will offer a unique opportunity to hear how alumni applied their classroom learning in real-world sustainability careers across sectors, including corporate sustainability, sustainability finance, policy, consulting, environmental justice, and more.
This is a 0 credit ungraded course open to all students in the MS in Sustainability Management, MS in Sustainability Science, MPA in Environmental Science and Policy, MS in Climate, MS in Climate Finance, and MA in Climate and Society programs. Students can attend as many or as few workshops as they'd like, in person or virtually. The Zoom link and classroom location will be confirmed in the coming weeks.
Workshop dates and topics:
September 9 - Governmental Sustainability, Decarbonization, and Environmental Protection
September 16 - Corporate Sustainability
September 21 - Sustainability Finance
October 7 - Environmental Justice
October 14 - The Built Environment
October 21 - International Careers
November 11 - Energy Consulting
November 18 - Sustainability Analytics
December 2 - Nonprofit and Advocacy
CAPSTONE WORKSHOP IN SUSTAINABLE SCIENCE
Students study the sustainability science behind a particular sustainability problem, collect and analyze data using scientific tools, and make recommendations for solving the problem. The capstone course is a client-based workshop that will integrate each element of the curriculum into an applied project, giving students hands-on experience.
- Department: Sustainability Science
- 3 points
GRADUATE SPECIAL TOPIC
Signal Proc Med Devices
Current topics in biomedical engineering. Subject matter will vary by year.
- Department: Biomedical Engineering
-
Instructor:
Megan Heenan
Info - 3 points
APPLIED RESEARCH
- Department: Insurance Management
-
Instructor:
Teresa W Chan
Info - 3 points
WORKSHOP (CERT)
This workshop provides an intense immersion in the methods and skills of narrative medicine. Lectures will open up themes of how stories work, creativity, ethics, bearing witness, and empathy, while the small groups practice rigorous skills in close reading, creative writing, and responding to the writings of others. The learning objectives of the workshops are to 1) provide personal contact to introduce and solidify intersubjective relationships among participants; 2) to ignite use of methods that have been and will be utilized in the on-line component, e.g., writing to prompts from literary texts and responding to both form and content of colleagues’ writing; 3) plenary lectures from the architects of the discipline of Narrative Medicine in the foundational theories to be studied; 4) scheduled cultural learning opportunities of New York City (music, museums, literary readings) for shared creative experiences; 5) contact with Master of Science in Narrative Medicine graduate program for certification participants toward their understanding of the breadth of the field and the potential for their continuing to study NM after the CPA; 6) introduction to the national and international reach of Columbia Narrative Medicine so that participants grasp the value and magnitude of the community they have entered as certification program students. Participants will be given the chance to present their own works-in-progress to assembled participants and faculty as a jump-start to collaborative projects during and after the participation in the certification program.
- Department: Narrative Medicine
- 0 points
Intro Social Data Analysis I
Basic techniques for analyzing quantitative social science data. Emphasis on conceptual understanding as well as practical mastery of probability and probability distributions, inference, hypotheses testing, analysis of variance, simple regression, and multiple regression.
- Department: Sociology
-
Instructor:
Yao Lu
h-index: 25 Info - 4 points
PROJECTS-BIOMEDICAL INFORMATCS
Research in medical informatics under the direction of a faculty adviser.
- Department: Biomedical Informatics
-
Instructor:
Noemie Elhadad
Wikipedia h-index: 46 Info -
Instructor:
Chunhua Weng
h-index: 37 Info -
Instructor:
Mohammed Alquraishi
Info -
Instructor:
Andrea Califano
h-index: 77 Info -
Instructor:
Dennis Vitkup
Info -
Instructor:
Raul Rabadan
Wikipedia h-index: 72 Info - 1-12 points