Sustainability and Resilience of Tropica

Course Overview

SUSC PS5410 -
Tropical Highland Ecosystems - Vietnam
is an intensive, field-based sustainability course that immerses students in the study of tropical highland ecosystems from within an area that is home to two UNESCO-designated Biosphere Reserves; Núi Chúa (Khánh Hòa Province, with Núi Chúa National Park as the core zone) and Lang Biang (Lâm Đồng Province, with Bidoup–Núi Bà National Park as the core zone). These two regions span an ecological transect from coastal drylands and marine ecosystems to high-elevation montane and cloud forests and is home to multiple indigenous peoples, highlighting their exceptional biodiversity and cultural value. Their recognition under UNESCO’s Man and the Biosphere Program illustrates their international significance as areas for balancing conservation and sustainable development.

The significance of tropical highlands becomes increasingly apparent as the global climate warms and sea level rise forces migration away from deltaic lowlands. Critical ecosystems services provided by these highland environments are threatened not only by a warming climate, but also by changes in land use and increased population. Local indigenous people have survived in these highlands for generations, and are particularly at risk from these changes, comprise one of our main areas of interest. Furthermore, we will be immersed within an area of high biodiversity and endemism, with more than 14 tropical ecosystems that serve as home to numerous endangered species, including the sun bear, the antelope-like saola, giant and Truong Son muntjacs (barking deer), and the gray-shanked douc langur. The region is also rich in endemic plant species, including the enigmatic krempfii pine that is found only in the Central Highlands, and several other rare or endemic conifers. A single highland forest can exhibit exceptional species richness, with studies in the Central Highlands finding up to 70 tree species per hectare.

This course is designed for graduate students in the
Master of Science in Sustainability Science
program at Columbia University who are preparing for careers in environmental science, restoration ecology, climate adaptation, or ecosystem-based management. It is especially suitable for those interested in field-based research, biodiversity monitoring, nature-based solutions, and the integration of science with sustainability pract

• Department: Sustainability Science
• MTWRFSU 9 a.m.-5 p.m.
• Instructor: Brendan Buckley
  h-index: 40 Info
• 3 points

ECONOMETRICS II

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

Printmaking on, through, and below the m

Print on, through, & belo

This course offers to the student who may find an examination of printmaking an asset to their art practice.
The course will cover several printmaking processes like relief, intaglio, silkscreen, and monotype. In addition, we will discuss printmaking concepts such as repetition, matrix, original/translation, reproducibility, and multiple considering the works produced in class.
We will involve a separate in-depth study of each process by alternating studio time, demonstrations, field trips, individual and group critiques.
Through the printmaking processes, students will explore assignments and projects and be encouraged to incorporate them into their own body of work.

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

SYMBOLIC LOGIC

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

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

QUALITATIVE EVALUATION METHODS FOR NARRA

QUALTV EVALUATION METHODS

TBA

• Department: Narrative Medicine
• 3 points

QUALITATIVE EVALUATION METHODS FOR NARRA

QUALTV EVALUATION METHODS

TBA

• Department: Narrative Medicine
• 3 points

PRINTMAKING I: INTAGLIO

• Department: Visual Arts
• MW 1:30 p.m.-4 p.m.
• Instructor: Jennifer Nuss
  Info
• 3 points

PRINTMAKING II: INTAGLIO

• Department: Visual Arts
• MW 1:30 p.m.-4 p.m.
• Instructor: Jennifer Nuss
  Info
• 3 points

LIQUIDITY RISK MANAGEMENT

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

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

• Department: Enterprise Risk Management
• W 8:10 p.m.-10 p.m.
• Instructor: Lindsey de Rechter
  Info
• 3 points

Machine Learning for Finance

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

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

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

• Department: Mathematics
• S 2:40 p.m.-4:30 p.m.
• 3 points

WRITING CREATIVELY: CRAFT LAB & WORKSHOP

• Department: Narrative Medicine
• 3 points

WRITING CREATIVELY: CRAFT LAB & WORKSHOP

• Department: Narrative Medicine
• 3 points

GLOBAL ETHICS

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

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

• Department: Bioethics
• R 4:10 p.m.-6 p.m.
• T 6:10 p.m.-8 p.m.
• Instructor: Robert L Klitzman
  Wikipedia Info
• 3 points

BLOCKCHAIN AND ERM

Using Blockchain, decisions can be made without relying on a single centralized authority, allowing for greater transparency and trust between participants. By using smart contracts and distributed ledgers, users can easily create, modify, and manage agreements between stakeholders, ensuring that all parties have access to the same information and can make informed decisions. As a result, Blockchain technology reduces the risks associated with decision-making, and improves efficiency and accuracy. This course first examines the risks and rewards of implementing Blockchain at large organizations engaging in decentralized decision-making processes. The course then explores the Blockchain as a tool for risk management.

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

PRINTMAKING I: SILKSCREEN

• Department: Visual Arts
• R 10 a.m.-4 p.m.
• Instructor: Alejo Contreras
  Info
• 3 points

PRINTMAKING II: SILKSCREEN

• Department: Visual Arts
• R 10 a.m.-4 p.m.
• Instructor: Alejo Contreras
  Info
• 3 points

IMPACT FINANCE FOR SUSTAINABILITY PRACTI

IMPACT FINANCE FOR SUST PRACT

This survey course examines a range of sustainable and impact investing fixed income and equity products

before transitioning to the asset owner perspective on sustainable and impact investing. Each class session

includes elements of financial analysis, financial structure, social or environmental impact, and policy and

regulatory context. Brief guest lectures, podcasts, and three experiential exercises bring these topics to life.

At the end of the course, each student will be able to (i) construct a diversified portfolio of impact

investments based on the range of products tackled in class, (ii) integrate ESG into debt and equity valuation,

(iii) develop an impact investing product that an asset manager or investment bank could launch, (iv) develop

an impact investing strategy for an asset owner, and (v) lead either side of the investor-corporate dialogue on

sustainability. The lectures are designed to prepare students for both the impact investing product

development exercise and the impact investing asset owner strategy exercise, and these two exercises are

designed to prepare students for impact investing leadership over the course of their careers.

As an early innovator in social finance, dating back 24 years, the instructor provides students with a practical

toolkit, honed by making mainstream financial institutions and products more beneficial to a broader range

of stakeholders and making specialist impact investment firms more relevant to and integrated with

mainstream markets.

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

Sustainability Value Creation in Private

This course provides an overview of the way sustainability (environmental, social and governance) factors are analyzed in private markets. It focuses on preparing students to implement their understanding of the financial and societal risks and opportunities within the investment making process. In private markets, limited partners (pension funds, endowments, high net-worth individuals) have pushed the sustainability imperative and social consciousness of private equity funds and asset managers by seeking greater clarity around how their money is invested in both a responsible and financially meaningful way. Alongside this trend, an evolving regulatory environment globally has propelled the need to systemize evaluation frameworks for stakeholders within investment functions and advisors who support them.Unlike public markets, sustainability information is harder to glean in private markets and requires a skilled extraction and evaluation process. During this course, we examine a traditional ESG due diligence process embedded within the wider investment lifecycle (sourcing, diligence, hold and exit) through the lens of changing geographic regulatory landscape in financial investing and the market leading frameworks that quantify ESG factors for evaluation. The course culminates with a deal due diligence process that mimics an investment committee (IC) comprised of private equity leaders that understand the commercial and purpose-driven viability of an investment.

• Department: Sustainability Management
• M 2:10 p.m.-4 p.m.
• Instructor: Angela Jhanji
  Info
• 3 points

CLOUD COMPUTING

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

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

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

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

• Department: Applied Analytics
• R 8:10 a.m.-10 a.m.
• M 8:10 p.m.-10 p.m.
• Instructor: Mohsen Golalikhani
  Info
• Instructor: Mohamed Mneimneh
  Info
• 3 points

Credit Analytics

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

• Department: Mathematics
• F 1:10 p.m.-3:40 p.m.
• 3 points

HEALTH POLICY & BIOETHICS

This course introduces students to how healthcare policy is created and implemented in the United States and abroad, while also raising critical ethical issues surrounding healthcare policy for the US, and other industrialized as well as poorer nations. Through lectures, discussions, and readings from the current literature, we will explore the political processes and concerns which produce our current policy; examine the major issues being debated surrounding the creation and delivery of healthcare, including ethical issues; explore the process by which we induce biomedical progress and development; explore barriers to sound healthcare production and delivery in various countries, and examine the recent reforms wrought through the Affordable Care Act (Obamacare). In addition, we will spend a few units looking, in detail, at the unusual challenges posed in delivering healthcare to the poor and the elderly.

• Department: Bioethics
• T 2:10 p.m.-4 p.m.
• Instructor: Jonathan Engel
  Info
• 3 points

PRIVACY RISK MANAGEMENT

In today’s digital age, with the collection and usage of personal  information growing at an exponential rate, the study of privacy risk management is crucial. As organizations grapple with the dual challenge of monetizing technological innovation without running afoul of regulatory and legal restrictions, the ERM professional who understands how to identify, assess, and manage privacy risk is in high demand. In this course, students will develop an understanding of the legal frameworks governing data usage, the ethical issues associated with the use of personal information, and how to develop robust privacy frameworks and controls in order to manage privacy risk.

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

SPORTS LAW AND ETHICS

• Department: Sports Management
• W 6:10 p.m.-8 p.m.
• M 4:10 p.m.-6 p.m.
• Instructor: Carla Varriale
  Info
• Instructor: Jill Kelley
  Info
• 3 points

AI and the Future of Strategic Communica

AI & the Future of Strat

The field of Artificial Intelligence (AI) has rapidly evolved to become a transformative global force across various industries, with particular significance for strategic communication. This elective course provides a comprehensive exploration of AI’s foundations, its current landscape, and its profound impact on media, journalism, public relations, and marketing communications. The course also addresses critical issues surrounding AI such as ethics, policy, and risk management associated with adoption, while offering practical insights into implementing common AI tools and developing essential AI skills for communication professionals.

• Department: Strategic Communication
• M 4:10 p.m.-6 p.m.
• Instructor: Cecilia Dones
  Info
• 3 points

CIRCULAR ECONOMY FOR SUSTAINABILITY PROF

CIRC ECON FOR SUST PROFS

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

structures, systems and processes.

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

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

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

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

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

AI INFUSION

Artificial intelligence (AI) is swiftly infusing the communication discipline with immediate implications for students and practitioners alike. To stay current with rapidly unfolding developments and create new ties with industry, this 0-credit course presents a biweekly series of speakers and panels comprised of alumni, Advisory Board members, and professionals. Speakers discuss their own AI use in the workplace. Students have the opportunity to interact with communication leaders on the forefront of AI implementation.
 
Each session aligns with a different Strategic Communication course topic. Among the areas to be explored are synthetic data and synthetic audience testing, event simulation, retrieval augmented generation (RAG), agentic AI, content production, and personalization at scale. Along with current use cases, a core focus of discussion will be AI governance, leadership strategy and decision-making, workforce training, and the development of principles and policies to guide human-centric and ethical AI implementation.

• Department: Strategic Communication
• T 6 p.m.-7:20 p.m.
• Instructor: Brandy N Dawson
  Info
• 0 points

MARKET RESEARCH

Market research is the way that companies identify, understand and develop the target market for their products.  It is an important component of business strategy, and it draws on the research and analytics skills you have learned thus far in the program. Often market research consists of generating your own data, through quantitative and qualitative methodologies, in pursuit of the market research question.

This course is an elective that will expand on quantitative and qualitative methodologies that have been introduced previously, provide an introduction to other methodologies that are more specific to market research, and provide hands-on practice in defining a market research plan from start to finish. Students will also learn about particular types of market research studies and when and how they should be deployed. Students will generate and test their own research instruments. Through the use of case studies and simulations, students will learn how market research fits into an overarching marketing plan for a company.

This course is designed for students who have completed the Research Design and Strategy and Analytics core courses, and who are exploring how research fits into product marketing. You will leave this class understanding the essential aspects of market research, when and how they should be deployed, and the role you could play in small and large companies directing and executing on market research opportunities.

• Department: Applied Analytics
• R 8:10 p.m.-10 p.m.
• Instructor: Diahanna L Post
  Info
• 3 points

GENDER AND COMMUNICATION IN THE WORKPLAC

GENDER & COMM IN THE WORKPLACE

Gender and Communication in the Workplace offers professionals across sectors and industries the knowledge and skills needed to identify the social and linguistic practices enacted at work, and the opportunity to advance the interests of those who run up against barriers to advancement as a result of prejudice and stereotyping.

• Department: Strategic Communication
• M 2:10 p.m.-4 p.m.
• Instructor: Jane M McManus
  Info
• 3 points

ORGAN TRANSPLANT ETHICS

• Department: Bioethics
• M 6:10 p.m.-8 p.m.
• Instructor: David N Hoffman
  h-index: 2 Info
• 3 points

AI USER INTERFACES FOR ANALYTICS

AI UI FOR ANALYTICS

In recent years, data analytics and artificial intelligence (AI) have become essential to business intelligence and informed decision making. But to realize the impact of analytics and AI, effective visual communication of data insights via user interfaces (UI), such as web pages and app dashboards, is equally critical. Building effective UIs requires mastering the user experience (UX) design principles and certain front-end development technologies. Furthermore, the recent rise of multimodal Generative AI offers unprecedented opportunities for simplifying, automating, and scaling UX/UI development.

This course provides a comprehensive understanding of UX design principles and best practices for developing UIs while emphasizing ethical considerations and inclusivity. Students will learn to create intuitive and visually engaging websites and dashboards that leverage AI-generated insights, also considering data privacy, diversity, and accessibility. Key topics include the design, implementation, and evaluation of UIs, with hands-on experience in web development technologies like HTML, CSS, and JavaScript, as well as related cloud services. Students will apply state-of-the-art AI technologies to create intelligent and interactive UIs, all while critically assessing data sources and AI models for potential biases.

The course content comprises a blend of conceptual learning and practice assignments. Weekly lectures and reading materials will cover the fundamentals of data visualization and user experience designs. Students will put the gained knowledge into practice through individual design and coding assignments and a group term project.

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

PEDIATRICS & ETHICS

• Department: Bioethics
• W 4:10 p.m.-6 p.m.
• Instructor: George Hardart
  Info
• 3 points

Supervised Research

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

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

Supervised Research

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

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

GLOBAL LEGAL & REGULATORY ECOSYSTEM

• Department: Insurance Management
• Instructor: Sandra Bograd
  Info
• 3 points

PEDAGOGY: GOALS, METHODS, CONTEXTS (CER

• Department: Narrative Medicine
• 3 points

PEDAGOGY: GOALS, METHODS, CONTEXTS (CER

• Department: Narrative Medicine
• 3 points

Intro to Moving Image: Video, Film & Art

Intro Moving Image:Video,

Intro to Moving Image: Video, Film & Art is an introductory class on the production and editing of digital video. Designed as an intensive hands-on production/post-production workshop, the apprehension of technical and aesthetic skills in shooting, sound and editing will be emphasized. Assignments are developed to allow students to deepen their familiarity with the language of the moving image medium. Over the course of the term, the class will explore the language and syntax of the moving image, including fiction, documentary and experimental approaches. Importance will be placed on the decision making behind the production of a work; why it was conceived of, shot, and edited in a certain way. Class time will be divided between technical workshops, viewing and discussing films and videos by independent producers/artists and discussing and critiquing students projects. Readings will be assigned on technical, aesthetic and theoretical issues. Only one section offered per semester. If the class is full, please visit http://arts.columbia.edu/undergraduate-visual-arts-program.

• Department: Visual Arts
• W 10 a.m.-4 p.m.
• Instructor: Shelly Silver
  CULPA: 1 Info
• 3 points

Supervised Independent Research

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

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

Supervised Independent Research

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

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

GENETICS & ETHICS

• Department: Bioethics
• W 8:10 p.m.-10 p.m.
• 3 points

COMPANY FAILURES

Examination of areas critical to an organization’s success from strategic, operational, financial, and insurance perspectives, and examines why many companies fail in spite of the vast knowledge of factors driving success. Several case studies examined in depth.

• Department: Enterprise Risk Management
• M 6:10 p.m.-8 p.m.
• T 8:10 p.m.-10 p.m.
• M 8:10 p.m.-10 p.m.
• Instructor: Francis Tobin
  Info
• 3 points

MATHEMATICS FOR AI

This course equips students with essential mathematical foundations for understanding and working with artificial intelligence (AI) algorithms. After a brief introduction to the historical and social context that numbers arise in, students will learn about:
- Linear Algebra: Matrices, matrix-vector multiplication, linear models, change of basis, dimensionality, spectral decomposition, and principal component analysis (PCA).
- Calculus: Rates of change, derivatives, optimization techniques like gradient descent, with a brief touch upon linear approximation.
- Probability and Statistics: Mathematically deriving complex probability distributions out of simpler ones, mathematically deriving statistical testing methods
- Graph Theory: How graphs are used to find relationships between data as well as being a setting for AI-driven problem solving.
- Problem Solving and Algorithms: Applying mathematical concepts to find problem solutions.
Students will learn about search methods like uninformed search, informed search with the A* algorithm, and greedy algorithms.
- Computational Theory and Automata: Answering questions about what is computable, what is needed in order to compute something, and using this framework to state how much “information” is contained in a mathematical object.
By the end of this course, students will possess a strong mathematical toolkit to confidently tackle the complexities of modern AI algorithms.

• Department: Applied Analytics
• T 8:10 a.m.-10 a.m.
• M 6:10 p.m.-8 p.m.
• Instructor: Robert Simione
  Info
• Instructor: Thilan Arachchi Appuhamillage
  Info
• 3 points

RISK REGULATIONS IN FINANCE

This course examines post-financial crisis regulations including Basel III, Fundamental Review of the Trading Book (FRTB), Dodd-Frank Act, Supervision and Regulation Letter 11-7 (SR 11-7), and others.  Case studies will explore the technical details of these new rules; and guest lectures from industry experts will bring the material to life.  Areas of focus include: model risk management, stress testing, derivatives, and insurance.  By the end of this course students will be able to:


Evaluate the purpose and limitations of risk regulations in finance.

Identify and communicate weaknesses in a financial firm.

Communicate with regulators.

Understand Recovery and Resolution Plans or “Living Wills” for a financial firm.

• Department: Enterprise Risk Management
• R 6:10 p.m.-8 p.m.
• W 8:10 p.m.-10 p.m.
• Instructor: Jean Michel Ngalikpima
  Info
• Instructor: Sudeep Lahiri
  Info
• 3 points

Career Development for Quantitative Fina

Career Develop for Quant

This course helps the students understand the job search process and develop the professional skills necessary for career advancement. The students will not only learn the best practices in all aspects of job-seeking but will also have a chance to practice their skills. Each class will be divided into two parts: a lecture and a workshop.

In addition, the students will get support from Teaching Assistants who will be available to guide and prepare the students for technical interviews.

• Department: Mathematics
• TR 11:40 a.m.-12:55 p.m.
• Instructor: Jaehyuk Choi
  Info
• 0 points

ESG AND ERM

ESG will be a driving force in risk management in upcoming years. ERM / Risk professionals need a solid understanding of emerging ESG trends and regulations and how they apply to day-to-day job responsibilities. The ESG and ERM course begins with an overview of the ESG landscape and framework. After a foundational understanding is established, the course focuses on incorporating ESG into enterprise risk management, including identification, quantification, decision making, and reporting of ESG-related risks.

• Department: Enterprise Risk Management
• M 6:10 p.m.-8 p.m.
• R 6:10 p.m.-8 p.m.
• Instructor: Helda Rock
  Info
• Instructor: Tahmina Day
  Info
• 3 points

CONSUMERISM AND SUSTAINABILITY

TBA

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

ANALYTICS FOR BUSINESS OPERATIONS MANAGE

Operations Management (OM) is responsible for the efficient production and delivery of goods and services, serving as a cornerstone of successful organizations. This course emphasizes how analytical techniques, such as forecasting, queuing theory, and linear programming, provide critical tools for optimizing operational decision-making, improving efficiency, and addressing real-world challenges in operations management. In this course, you will gain essential skills to optimize processes, manage resources, and enhance productivity across various industries. The course will be delivered through a combination of interactive lectures, case studies, and hands-on coding exercises to ensure a balance between conceptual learning and practical application.

Through lectures, you will gain a solid foundation in OM principles and analytical techniques. Case studies will help illustrate real-world applications of OM in industries such as manufacturing, healthcare, retail, and logistics, allowing you to see how the concepts are applied in diverse contexts. This course will integrate the principles of OM with hands-on analytical techniques using Python, allowing you to model and solve real-world OM problems. You will learn to run simulations, perform optimizations, and analyze data to make data-driven decisions that enhance efficiency and overall performance.

OM practices are tailored to meet the specific needs of various sectors. In manufacturing, OM helps streamline production lines and minimize waste; in healthcare, it enhances patient flow and optimizes resource allocation; in retail, it improves inventory management and supply chain operations; and in logistics, it ensures timely deliveries while reducing transportation costs. This course will equip you with the skills to apply OM practices effectively in different industries.

Analytics for Business Operations Management is an elective that is intended for students who are interested in pursuing a career using analytics and operational insights to drive organizational success in a competitive global marketplace across various industries.

• Department: Applied Analytics
• R 6:10 p.m.-8 p.m.
• F 10:10 a.m.-noon
• M 6:10 p.m.-8 p.m.
• Instructor: Arash Khatibi
  Info
• Instructor: Janice Winch
  Info
• Instructor: Andy W Chen
  Info
• 3 points

DERIVATIVES RISK MANAGEMENT

This course explores financial derivatives across different asset classes with in-depth analysis of several popular trades including block trades, program trades, vanilla options, digital options, and variance swaps. Their dynamics and risks are explored through Monte Carlo simulation using Excel and Python. The daily decisions and tasks of a frontline risk manager are recreated and students have the opportunity to see which trades they would approve or reject. Students will gain a working knowledge of financial derivatives and acquire technical skills to answer complex questions on the trading floor.

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

MANAGING STAKEHOLDER RISK IN THE ORGANIZ

In this course, students study major concepts of management and organization theory to understand human behavior in an organizational context, and then learn how to apply this to better manage interactions with key ERM stakeholders. Students will learn how to accomplish key ERM activities effectively while preserving and enhancing key internal relationships.

The course provides a deep dive into how enterprise risk functions operate within organizations, blending theoretical frameworks with practical, real-world applications. Topics include individual and organizational psychology, risk culture, organizational structure and governance, and the dynamics of managing risk in complex institutions. Through case studies and class discussions, students explore the behavioral and structural dimensions that shape ERM practices.


This elective is open only to students within the ERM program. This course (MSRO) is analogous to Managing Human Behavior in the Organization (MHBO), but customized for an ERM role. As a result, ERM students may not register for MHBO and those that have already taken MHBO may not register for MSRO.

• Department: Enterprise Risk Management
• T 6:10 p.m.-8 p.m.
• W 8:10 p.m.-10 p.m.
• Instructor: Kristen Walters
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• Instructor: Ann Breslawski
  Info
• 3 points

Special Topics Class - Sustainable Produ

Sustainable Products

Every minute of every day all around the world, people purchase and interact with all types of products as part of their daily lives and routines. Although products have many different forms and serve various functions, virtually all have direct connections and potential impact opportunities for Sustainability. In this course, we will explore the complexities of defining, designing, producing, marketing and using Sustainable Products that deliver tangible commercial market benefits, while balancing inevitable trade-offs to drive net-positive sustainability impacts. By connecting insights from multiple disciplines, we will study how sustainable products can meet consumer needs, differentiate from competitors, gain potential scalability, and drive meaningful change in the marketplace. The course aims to provide sustainable business professionals with a sampling of approaches and practical tools needed to design, produce, and market products that are both impactful and commercially successful.

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

FINANCIAL SEC ANALYSIS AND PORTFOLIO MGT

FIN SEC ANALYSIS AND PORT

Financial securities analysis and portfolio management is the study of analyzing information to evaluate financial securities and design investment strategies. Studying the subject can provide a foundation for students entering the fields of investment analysis or portfolio management. This course provides an intensive introduction to major topics in investments. Part I of the course lays the theoretical foundation by introducing the Portfolio Theory and Equilibrium Asset Pricing models. Part II covers the valuation models and analysis of major asset classes: equity, fixed-income, and derivatives. Topics include bond valuation and interest rate models, equity valuation and financial statement analysis, options valuation, other derivatives, and risk management. Part III of the course focuses on the practice of active portfolio management.

• Department: Applied Analytics
• W 8:10 p.m.-10 p.m.
• R 6:10 p.m.-8 p.m.
• Instructor: Lei Yu
  Info
• 3 points

TOOLS FOR RISK MANAGEMENT

Tools for Risk Management examines how risk technology platforms assess risks. These platforms gather, store, and analyze data; and transform that data to actionable information. This course explores how the platforms are implemented, customized, and evaluated. Topics include business requirements specification, data modeling, risk analytics and reporting, systems integration, regulatory issues, visualization, and change processes. Hands-on exercises using selected vendor tools will give students the opportunity to see what these tools can offer.

• Department: Enterprise Risk Management
• M 8:10 p.m.-10 p.m.
• R 6:10 p.m.-8 p.m.
• Instructor: Viktor Ziskin
  Info
• Instructor: Barney Baldwin
  Info
• 3 points

MODEL RISK MANAGEMENT

Given the ever growing reliance on models, Model risk affects financial institutions at almost every level of their organization including pricing, risk, finance, and marketing. Model risk management (MRM) is now one of the primary focuses of operational risk management at modern financial institutions. In this class, the ERM skill sets of risk identification, risk quantification, and risk decision making are applied to the kinds of models seen in large, complex financial institutions. Through readings, lecture, assignments, and in-class discussions, students learn the principles and concepts that a robust MRM function uses to manage model risk.

• Department: Enterprise Risk Management
• R 8:10 p.m.-10 p.m.
• Instructor: Peter L Russo
  Info
• 3 points

ERM MODELING

Equips students with the basics of risk measurement and simulation using a hands-on approach to ERM modeling. Using industry-standard simulation software, students build systems of risk drivers for finance and insurance companies. Topics include risk correlations, VaR and TVaR, capital modeling, capital allocation, and parameter, process, and model Risk. Students acquire both quantitative experience building models and qualitative appreciation for model weaknesses.

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

SPORTS SPONSORSHIP & SALES

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

From Ruins to Remains: Palestine & Archa

This new course aims to provide advanced undergraduate and graduate students with a critical history of Palestine-related archaeology from the mid-19th century to the present, and (b) an examination of how archaeological narratives relating to Palestine have been impacted by state nationalism, colonialism and conflicting local, regional and global religious interests from the "Classical World" to the 21st century.

• Department: Anthropology
• W 12:10 p.m.-2 p.m.
• Instructor: Brian Boyd
  CULPA: 6 Info
• 4 points

MACHINE LEARNING FOR RISK MANAGEMENT

The exponentially increasing availability of data and the rapid development of information technology and computing power have inevitably made Machine Learning part of the risk manager’s toolkit. But, what are these tools? This class provides the driving intuitions for machine learning. Students will see how many of the algorithms are extensions of what we already do with our human minds. These algorithms include regularized regression, cluster analysis, naive bayes, apriori algorithm, decision trees, random forests, and boosted ensembles.

Through practical and real-life applications of ML to Risk Management, students will learn to identify the best technique to apply to a particular risk management problem, from credit risk measurement, fraud detection, portfolio selection to climate change, and ESG applications.

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

Vegetalities

This seminar examines the "vegetal turn" in the humanities through the lens of Black studies, Indigenous studies, and  feminist/queer studies approaches to science and technology. Beginning with Suzanne Césaire's 1942 definition of Caribbean being as fundamentally vegetal, the course reads across plant science, multispecies ethnography, critical race theory, queer ecologies, and plantation studies to ask what plants know, who knows them, and what vegetality offers as an analytic for thinking about racialized and gendered life in the Anthropocene. Students produce an annotated bibliography, a vegetal fieldwork exercise, and a seminar paper suitable for development toward publication. They also maintain a living plant throughout the semester.

• Department: Anthropology
• W 10:10 a.m.-noon
• Instructor: Vanessa L Agard-Jones
  CULPA: 3 Info
• 4 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
• 3 points

ARTIFICIAL INTELLIGENCE OF THINGS

AI OF THINGS

• Department: Applied Analytics
• R 6:10 p.m.-8 p.m.
• W 8:10 p.m.-10 p.m.
• Instructor: Petros Zerfos
  Info
• Instructor: Javid B Huseynov
  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
• R 6:10 p.m.-8 p.m.
• M 8:10 p.m.-10 p.m.
• T 8:10 p.m.-10 p.m.
• Instructor: Leslie Weinstein
  Info
• Instructor: Terry Cottrell
  Info
• Instructor: Thomas Kartanowics
  Info
• 3 points

CYBERSECURITY RISK MANAGEMENT

Cyber losses, reflected in daily headlines on data breaches, state-sponsored attacks on critical infrastructure, and ransomware incidents, have grown to exceed other major categories of operating risk in terms of total cost, driving increased regulatory activity in response.

This means risk management professionals need a solid understanding of cyber-risk management programs, techniques, mitigation strategies, architectures, frameworks, and procedures, which this course provides.  Some frameworks covered include ISO27001, NIST CSF, CIS 18 Critical Security Controls, etc.  Effective management of cyber-risks is an Enterprise-wide activity addressing immediate risks requiring attention while building a mature foundation for a resilient and proactive cybersecurity risk management program; a Technology Risk Management foundation is therefore a prerequisite for enrollment; however, IT expertise is not.

The course provides practical, hands-on, cases and exercises for the application of cyber-risk management principles, equipping course graduates to help lower the probability of a risk event in their organization, and to enhance organizational resilience for effective incident response and recovery.

• Department: Enterprise Risk Management
• W 6:10 p.m.-8 p.m.
• None None-None
• Instructor: Ian Clark
  Info
• 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.
• R 8:10 p.m.-10 p.m.
• Instructor: Rod Aday
  Info
• Instructor: Rimla Khawaja
  Info
• 3 points

ANALYTICS FOR CYBERSECURITY MANAGEMENT

ANALYTICS FR CYBERSECURIT

This course is designed to immerse students in the intersection of cybersecurity and data analytics. The course explores how modern data-driven approaches are revolutionizing the way organizations detect and manage cyber threats. Students will engage deeply with core cybersecurity concepts, such as network security, vulnerability management, and threat intelligence, while also learning to leverage cutting-edge data analytics and artificial intelligence to solve real-world security problems. Through hands-on exercises, coding assignments, and case studies, students will gain practical skills in analyzing logs and telemetries, building detection systems, and applying machine learning to security operations.

• Department: Applied Analytics
• M 8:10 p.m.-10 p.m.
• Instructor: Muhammed Bulut
  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
• M 6:10 p.m.-8 p.m.
• M 8:10 p.m.-10 p.m.
• Instructor: Dan Cahill
  Info
• Instructor: Bryce Wolf
  Info
• 3 points

APPLIED AGENTIC AI

Artificial intelligence (AI) has entered a new era defined not just by what models can generate, but by what AI systems can autonomously do. Agentic AI, systems built on large language models (LLMs) that can reason, plan, use tools, access data, and act on behalf of users, is rapidly reshaping how organizations approach analytics, decision-making, and workflow automation. From AI agents that autonomously query databases and build dashboards, to multi-agent systems that coordinate complex analytical pipelines, agentic AI represents a significant shift in how analytics professionals design, build, and deliver insights.

This course provides a comprehensive, hands-on introduction to the design, development, and deployment of agentic AI systems for analytics use cases. Students will explore the foundational concepts behind LLM-based agents, including reasoning patterns (ReAct, Chain-of-Thought, Plan-and-Execute), tool use and function calling, memory architectures, and retrieval-augmented generation (RAG). The curriculum emphasizes practical agent development using modern frameworks such as LangGraph, LlamaIndex, CrewAI, and the OpenAI and Anthropic SDKs, and it addresses the ethical, governance, and safety considerations essential to responsible deployment.

• Department: Applied Analytics
• M 8:10 p.m.-10 p.m.
• Instructor: Javid B Huseynov
  Info
• 3 points

STRATEGY AND ANALYTICS

n/a

• Department: Applied Analytics
• F 12:10 p.m.-2 p.m.
• F 2:10 p.m.-4 p.m.
• M 8:10 p.m.-10 p.m.
• R 6:10 p.m.-8 p.m.
• F 10:10 a.m.-noon
• W 6:10 p.m.-8 p.m.
• R 8:10 p.m.-10 p.m.
• M 6:10 p.m.-8 p.m.
• Instructor: Joseph R Schlosser
  Info
• Instructor: Arunava Bhattacharyya
  Info
• Instructor: Ranjit Kumble
  Info
• Instructor: Peter Went
  Info
• Instructor: Lisa Godek
  Info
• Instructor: Ashoke S Bhattacharjya
  Info
• Instructor: Huan Liu
  Info
• Instructor: Sandy Balkin
  Info
• 3 points

STRATEGY AND ANALYTICS

STRATEGY AND ANALYTICS ONLINE

n/a

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

CANCER BIOETHICS

Cancer is the second leading cause of death in the US and most affluent countries. It represents a complex group of
diseases with heterogeneity in biology, incidence, prevalence, and outcomes. And unlike other complex and
potentially life-threatening maladies, a cancer diagnosis is regularly received by patients as a death sentence. It
elicits dread, despair, hopelessness, and sometimes stigma in patients and their families. The emotional toll of a
cancer diagnosis and vulnerability that ensues, can profoundly impact patients’ approaches to research and
treatment.
The Cancer Bioethics course offers a comprehensive exploration of the diverse ethical issues that arise in the context
of cancer care and research, providing students with an analytic framework for complex moral dilemmas faced by
patients, clinicians, researchers, and policymakers. Through case studies, theoretical discussions, and critical
analysis, students will employ key bioethical principles and their application to cancer care - from diagnosis to
survivorship or decisions about end-of-life care. Topics will include unique ethical challenges in oncology such as
the “right not to know” and other challenges associated with disclosures of genomic testing of cancer; the moral
uncertainty of conducting research in minors diagnosed with cancer and the downstream use of their oncologic data;
the unbridled optimism and therapeutic illusion among a number of cancer specialists; therapeutic misconception
among participants in oncologic clinical trials; and the increasing integration of artificial intelligence into new
models of cancer care and prognostication. The course will also examine the intersection of social determinants of
health, cultural beliefs and value systems, and healthcare access, addressing the ethical concerns of disparities in
cancer care.
The course incorporates curricular elements of clinical ethics, law and bioethics, research ethics, reproductive ethics,
pediatric ethics, global ethics, environmental ethics, race and bioethics, organ transplant ethics, health policy and
bioethics, etc. This is an elective course open to cross-registrants from other fields and/or Columbia University
programs. Students do not need to have medical background to take this course. Students pursuing a degree in
medicine or pre-medicine, nursing, behavioral sciences, biotechnology, genetics, data science, public policy,
journalism, law, and governme

• Department: Bioethics
• W 6:10 p.m.-8 p.m.
• 3 points

CAPSTONE

The Capstone Project is an opportunity for students to synthesize and apply learnings from throughout the Strategic Communication program. Under the guidance of expert advisers, you’ll investigate a real-world communication issue, devising solutions and strategies that bridge the gap between theory and practice.

• Department: Strategic Communication
• R 6:10 p.m.-9 p.m.
• Instructor: Mark Truss
  Info
• Instructor: Lilian Ore
  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
• TR 10:10 a.m.-12:40 p.m.
• Instructor: Paula L Lycan
  Info
• 3 points

AI & PHOTOGRAPHY

As far back as Walter Benjamin’s “work of art in the age of mechanical reproduction” (1935), photography has always been challenged by
mechanical means
of image processing. Photographers and Institutions have first resisted and then (mostly) embraced each of these changes. This class explores Artificial Intelligence Photography as the latest in a series of earthquakes in the history of the photographic image, accompanying the desires of business, globalization, and science. This class seeks an ethically guided, globally representative model for photography and artificial intelligence. Debates around authorship and creativity (e.g., Supreme Court case with Andy Warhol) now face a radically new context of an “authorless” photograph. As crowdsourced imagemaking begins, the bias of massive datasets have taken techno-utopians by surprise, underlining that the task of building an equitable image-bank of the world cannot be left to algorithms and entrepreneurs. This class will explore the ethics and aesthetics of Artificial Intelligence and Imagery. There will be equal emphasis on reading and writing papers, as there will be on learning new software and tools.

• Department: Visual Arts
• MW 1:10 p.m.-3:40 p.m.
• Instructor: Alexey Yurenev
  Info
• 3 points