As digital media increasingly drives the field of strategic communication, leading successful communication efforts also require a platform specific, evidence-based strategic approach. Leaders must know how to use a broad and rapidly changing mix of digital media platforms and tools to connect their message with the right audience. To that end, this course covers major topics in digital media and communication, such as content strategy, digital experience, channel planning, online reputation management, programmatic marketing, audience targeting, artificial intelligence and more. Through in-class lectures, discussion, case studies, guest speakers, group projects and individual writing assignments, students in this course will be introduced to strategic decision-making and communications planning for social media, mobile, digital advertising, search, email, digital out-of-home and interactive media (video, radio, podcasts). Students will also gain an in-depth understanding of how to integrate digital strategies and tactics with traditional communication efforts.
Review of the types of operational risks, such as technology risk (e.g., cyber-security), human resources risk, disasters, etc. Includes case studies, risk analysis frameworks and metrics, and common mitigation techniques, such as insurance, IT mitigation, business continuing planning, etc.
This course seeks to introduce students to the latest theory, research and practice of “Inclusive Leadership,” an evolving framework, for understanding the role of people leaders, teams, and individual contributors in cultivating diverse, equitable, and inclusion environments in companies and organizations. This interactive, intensive course will leverage insights, research, and experiences of leading scholars and practitioners in the fields of leadership, diversity, and inclusion. The content covered is grounded in inclusive leadership development, diversity management, team effectiveness, organization development, and intergroup relations. Students will learn hands-on strategies for fostering inclusion at every level of the organization, and how and why it matters on the overall culture and climate of the organization in a systematic way. Class discussions, assignments, and readings will pose questions such as: How to foster a culture of inclusion? How do we know when inclusion is actually taking place?
Students without a strong math background and experience with Excel will require significant additional time and effort to achieve the learning objectives and work through the course assignments.
This course builds a foundation in the mathematics and statistics of risk management. Students are empowered to understand the output of quantitative analysts and to do their own analytics. Concepts are presented in Excel and students will have the opportunity to practice those concepts in Excel, R or Python.
This course is a required prerequisite for registering for the following courses: Coding for Risk Management, Financial Risk Management, Quantitative Risk Management, Credit Risk Management, Market Risk Management, Credit Risk Analytics, Applied Coding for Risk Management, Derivatives Risk Management, Model Risk Management, ERM Modeling, and Machine Learning for Risk Management.
In an era defined by unprecedented global challenges and opportunities, nonprofit advocacy serves as a powerful force for systemic reform and public innovation. This course immerses students in the intersection of theory and practice through an
advocacy practicum
approach—designed to equip future nonprofit leaders with the skills to influence policy, mobilize communities, and drive systemic change.
In the context of the ever evolving policy landscape of New York City and providing a global lens, this course offers an in-depth exploration of advocacy fundamentals within the nonprofit sector. Through real-world case studies, hands-on projects, and interactive fieldwork, students have the opportunity to examine how advocacy efforts in New York City—a hub of civic engagement—can expand broader policy frameworks and cross into international contexts.
Over the term, students will explore the theoretical foundations of advocacy, including social movement theory, policy influence, and public opinion formation. They will engage in stakeholder analysis, coalition-building, and the creation of advocacy strategies tailored to shifting political, economic, and social dynamics. Central to this course will be discussions on how traditional advocacy approaches are being redefined in response to growing inequalities and systemic challenges, emphasizing the need for adaptable, intersectional strategies to confront global disparities.
The framework emphasizes practical application: students will have the opportunity to develop and implement real advocacy plans, leveraging digital tools, media, and virtual organizing strategies to enhance their impact. Fieldwork, simulations, and collaborative projects will allow students to apply theoretical knowledge to tangible issues, empowering them to lead efforts that address pressing social challenges, whether locally in New York City or globally in areas such as international development and human rights.
Key topics include:
Crafting advocacy strategies that influence public policy in divided political environments;
Building and managing coalitions across stakeholders;
Engaging marginalized communities to ensure inclusive and equitable advocacy efforts;
Navigating the digital advocacy landscape to design impactful campaigns.
By the end of the course, students should be prepared to plan critically and act decisively in the fast-changing world of advocacy, with the tools, s
Students will utilize the knowledge and skills learned to perform a comprehensive or focused health assessment including history and physical examination in a supervised laboratory. Students will record findings in an approved manner and demonstrate utilization of holistic, region-cultural, and ethical approaches to individuals and families.
Equips students with the ability to adopt the programming culture typically present in the ERM/risk areas of most financial organizations. By studying Python, SQL, R, git, and AWS, students gain exposure to different syntaxes. Students apply these skills by coding up market risk and credit risk models. Students also gain familiarity with working in the cloud.
The environment affects human health and well-being, and current health-care technology can impact the environment. Thus, questions about how humans ought to relate both to their own environment and to other living beings on this planet fall squarely within the field of bioethics. While some observers may see bioethics as concerning only the health of human beings defined narrowly, bioethics in fact has many implications for the larger biosphere and vice versa.
This course discusses important issues at the nexus of bioethics and the environment, including climate change, ozone shield depletion, soil erosion, ocean pollution, diminishing biodiversity-all among the environmental factors with adverse consequences for the health of both human and non-human beings. Even the technologies employed in health-
care
have environmental impact harmful
to
health.
Among the challenges to be addressed: How can healthcare be made “green”? What do present generations “owe” to future generations? What is environmental justice in the relations between developed and developing societies? How should humans relate to the other inhabitants of this planet?
A survey of market, credit, liquidity, and systemic risk. Includes case studies, risk quantification methods, and common mitigation techniques using portfolio management, hedging, and derivatives. Also addresses traditional risk management practices at banking institutions.
This course provides a comprehensive overview of the grants process, with specific reference to the research, writing, and managing of a range of grant types. The grants process is considered within the context of an institution’s total fundraising strategy as well as its overall mission-based goals. The course covers the range of possible grant-giving institutions, including government, corporate, and foundation, as well as the various types of grants, such as challenge, and their respective considerations for the fundraiser and nonprofit institution. Emphasis is placed on developing competitive proposals, accurate budgets, and appropriate systems of administration.
Prerequisite: Fundraising Fundamentals: NOPM PS5370
This course examines questions such as: What does the telling and reading of narratives do for the ill or disabled individual? How can clinicians effectively elicit, interpret, and act upon such narratives? Who owns a story, and what is the role of co-authorship, power and witnessing in story-telling and story-listening? Whose voice do we hear? What are the roles of power and hierarchy in story-telling and listening? What is the impact of familial, cultural, social, institutional, political contexts on the individual story? And finally, how can personal stories be translated to political advocacy and action? Texts assigned weekly will be broadly interdisciplinary – drawing from memoir, poetry, essays, fiction, feature and documentary films, narrative theory, and disability studies, exploring the relationship between disability/illness experience and narrative. This elective course is open to all students in the Narrative Medicine CPA program. Students should be prepared to engage with each other and with the instructor and to offer their questions, comments, insights, and analysis.
This is an essential, practically applied element of narrative medicine study and it is exemplary as a way to illustrate the impact of narrative study in shaping experience, opening awareness, and highlighting the need for change and new stories. A narrative medicine course focused on disability and illness narratives is an important aspect of narrative medicine study. Exploring narratives presented in a variety of formats by using narrative medicine methods can encourage deeper perspective-taking and promote activism for underrepresented voices.
Disability and Illness Narratives: Storytelling For Awareness and Activism
is an elective course in the Narrative Medicine CPA program. In addition, this course is open to cross-registrants in other programs who demonstrate some understanding of narrative medicine and/or participate in the online asynchronous narrative medicine orientation course before the semester begins. Narrative Medicine CPA students are required to have completed, or be simultaneously enrolled in the course,
Narrative Medicine Methods: Close Reading and Writing
, course number K5120, and have completed the required program online asynchronous orientation course. CPA courses are all 10 weeks/modules long, and they are online and asynchronous, which means there are no meeting times. Each module represents one week of the course. All modules begin on a Tuesday and end on Monday of th
This is an introductory pharmacology course, and, since pharmacology is an applied science, it builds on several foundational concepts of biology, chemistry, microbiology, anatomy, and physiology in the context of nursing practice. Principles of pharmacology will be discussed, including pharmacokinetics, pharmacodynamics, and toxicities. Major pharmacologic agents used in treating more common disease states will be discussed with emphasis on relating the mechanism of action to the therapeutic use.
Credit Risk Management requires business acumen, the monitoring of internal and external data, disciplined execution, and organizational intelligence. A solid understanding of this enables a credit risk manager to help organizations achieve their objectives. Through readings, case studies, and modeling projects, students learn how risk managers decide on credit risk management strategy applied throughout the client lifecycle.
Capstone projects afford a group of students the opportunity to undertake complex, real-world, client-based projects for nonprofit organizations, supervised by a Nonprofit Management program faculty member. Through the semester-long capstone project, students will experience the process of organizational assimilation and integration as they tackle a discrete management project of long or short-term benefit to the client organization. The larger theoretical issues that affect nonprofit managers and their relationships with other stakeholders, both internal and external, will also be discussed within the context of this project-based course.
Digital, social, and mobile media continue to heavily impact every aspect of sports business, often in profound and unanticipated ways, particularly in managing and optimizing revenue streams. All revenue line items are fully intertwined and integrated with each other, media, sponsorship, ticketing, hospitality, concessions and licensing, etc. Students of this course will learn to analyze and optimize the ecosystem of sports business including content rights, ticketing, sponsorship, merchandising, marketing, etc., as well as make business analytics decisions by leveraging business analytics software to run scenario analysis.
This course is intended to provide a mechanism to MA students in Statistics who undertake on-campus project work or research. The course may be signed up with a faculty member from the Department of Statistics for academic credit. Students seeking to enroll in the course should identify an on-campus project and a congenial faculty member whose research is appealing to them, and who are able to serve as their mentor. Students should then submit an application to enroll in this course, which will be reviewed and approved by the Faculty Director of the MA in Statistics program.
Prerequisites: GR5203; GR5204 &GR5205 and at least 4 approved electives This course is an elective course for students in the M.A. in Statistics program that counts towards the degree requirements. To receive a grade and academic credits for this course, students are expected to engage in approved off-campus internships that can be counted as an elective. Statistical Fieldwork should provide students an opportunity to apply their statistical skills and gain practical knowledge on how statistics can be applied to solve real-world challenges.
FUNDAMENTALS OF DATA ENGINEERING
This fundamental course introduces students to core concepts of nursing science including taxonomy, philosophies of caring, nursing process, and evidence-based care. Concepts from the biological, physical, epidemiological, and behavioral sciences will be utilized as students begin the study of adults experiencing major biophysical health problems. The course is an introduction to the role of the professional nurse in medical/surgical nursing care of the adult client in context of populations.
COURSE OVERVIEW
The proposed graduate-level fieldwork course, Sustainability and Resilience of Tropical Coastal Ecosystems, is designed for students interested in learning more about the interconnections between tropical coastal ecosystems, focusing on the nexus between coral reef, seagrass, and mangrove systems. This course will discuss the importance and value of these vital tropical coastal ecosystems. We will specifically concentrate on the stewardship, conservation, and restoration of these systems in light of the multiple assaults associated with global climate change that impact these systems and put them at risk of complete collapse. This includes reviewing the most critical issues in tropical marine biodiversity, resource sustainability, ecosystem resilience, and global change biology. Three (3) Lecture
ACADEMIC GOALS
This course offers students a hands-on understanding of tropical coastal ecosystem management and sustainability challenges. Participants will engage with local experts and communities, fostering skills in field research and sustainability practices.
Technology’s complexity becomes intricately detailed and beautiful when viewed as a system —its components, though diverse, work in symbiosis underpinned by shared communication protocols and governance structures. This system enables machines to operate with increasingly minimal human intervention.
This survey course offers a broad and holistic exploration of technology as an integrated system, emphasizing the seamless integration that characterizes modern technological frameworks. Students will delve into the core components that constitute digital environments—such as the Internet, networks, hardware, and software—and understand how these elements collectively drive and shape today’s IT infrastructure.
This course provides the tools to measure and manage market risk in the context of large financial institutions. The volume and complexity of the data itself, at large institutions, makes it a challenge to generate actionable information. We will take on this challenge to master the path from data to decisions.
We cover the essential inputs to the engines of financial risk management: VaR, Expected Exposure, Potential Exposure, Expected Shortfall, backtesting, and stress testing as they apply to asset management and trading. We explore the strengths and weaknesses of these different metrics and the tradeoffs between them. We also cover how regulatory frameworks impact both the details and the strategy of building these engines. Lastly, we cover counterparty-credit methodologies, mainly as they apply to Trading Book risk.
TBA
TBA
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.
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.
This fundamental course provides the student with clinical experience to implement patient-centered care that reflects an understanding of the concepts of human growth and development, health promotion, nursing management of illness, and patient safety. Philosophies and scientific theories of nursing will serve as a foundation for the development of critical thinking and skill acquisition. Key elements of culture, spirituality, heredity, and ethics will be integrated into the planning and provision of nursing care to individuals and populations.
Students will gain competency by practicing skills in a supportive and supervised environment in the simulation laboratory. This fundamental course provides the student with practical application of nursing skills and the scientific rationale for performing procedures correctly in order to provide patient-centered care that reflects an understanding of the concepts of human growth and development, health promotion, nursing management of illness, and patient safety. Philosophies and scientific theories of nursing will serve as a foundation for the development of critical thinking and skill acquisition. Key elements of culture, spirituality, heredity, and ethics will be integrated into the planning and provision of nursing care to simulated patients.
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.
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
In this course, students will comprehend the fundamental principles of these new technologies and how to strategically apply them to drive innovation, create efficiencies, and generate new opportunities in a rapidly evolving digital landscape. It offers students the opportunity to understand the factors fueling the adoption of these technologies including the exponential growth of data, the decline in trust post-financial crisis, the desire for data ownership, growing regulatory transparency requirements, the need for greater efficiencies, and the required protection of sensitive data. The evolution goes beyond the implementation of new processes, decentralized business models and technologies. The convergence of new technologies and interdisciplinary innovation drive the requirement for changes in regulatory processes, governance, and ethics.
This course is designed for graduate students who aspire to lead in the era of digital transformation. It is ideal for those who seek to understand the strategic applications of blockchain, AI, and Web 3.0 technologies to drive innovation within their organizations. Whether planning to advance in a career in technology management or a professional in data and knowledge-driven industries, this course will enable the acquisition of knowledge and skills necessary to navigate and leverage the opportunities presented by the Fourth Industrial Revolution.
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.
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.
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.
Artificial intelligence has become widely available. In some cases, regulations apply already. In other cases, those working in law, public policy, and ethics continue to debate whether and how to regulate use, and which products should require pre-market vetting by regulators. Many principles and guidelines govern the AI space, providing a strong “soft law” framework for state and institutional governance. Some focus on consumer privacy, fairness, protecting workers, and human rights. Students will develop a core competency in AI and ethics with an emphasis on problem-solving, critical thinking, and analysis of AI tools and products related to health, health care, and the social determinants of health.
Computer scientists, coders, and engineers best understand the development and use of machine learning, but often lack training in ethics, law, and public policy. Ethicists with an understanding of AI and machine learning can help steer AI use in safe and productive ways.
The course is primarily designed for bioethics master’s students; no formal background in artificial intelligence or machine learning is assumed. Some knowledge of ethics, ethical principles, and foundational philosophy will be presumed, yet students can request additional resources if they have not had the requisite coursework.
The first part of the course (the first 6 modules) explores the core insurance products one needs to understand within the Wealth Management and Family Office ecosystem. Students will analyze and evaluate risk exposure types for which a client might want insurance, including liability, automobile, homeowners, health, disability, long-term care, and life risks. Students will also learn how to conduct insurance needs analysis and select appropriate insurance policies and companies for their clients.
In the second part of the course, students will focus on mastery of Client Communications. In the wealth management industry, where technical expertise is increasingly commoditized, effective communication is the key differentiator for building trust and sustaining a successful practice. This intensive segment positions communication not as a mere soft skill, but as the central strategic imperative for building a thriving advisory practice. Students will master the science and art of communication in their dual roles: as advisors to clients and as operators of a practice. The modules consider the full spectrum of strategic communication: from building and maintaining robust client relationships and navigating challenging conversations, to architecting a powerful personal brand and digital presence, to designing tech-enabled, scalable outreach systems.
Students enrolled in the MA in Biotechnology Program have the opportunity to receive academic credit while conducting Supervised Research under the guidance of a faculty mentor within the University (S5502) or a biotech business-specific Supervised Internship outside the University (S5503) within the New York City Metropolitan Area unless otherwise approved by the Program. Credits received from this course are used to fulfill the Practical Training requirement for the MA degree.
Students enrolled in the MA in Biotechnology Program have the opportunity to receive academic credit while conducting Supervised Research under the guidance of a faculty mentor within the University (S5502) or a biotech business-specific Supervised Internship outside the University (S5503) within the New York City Metropolitan Area unless otherwise approved by the Program. Credits received from this course are used to fulfill the Practical Training requirement for the MA degree.
Students enrolled in the MA in Biotechnology Program have the opportunity to receive academic credit while conducting Supervised Research under the guidance of a faculty mentor within the University (S5502) or a biotech business-specific Supervised Internship outside the University (S5503) within the New York City Metropolitan Area unless otherwise approved by the Program. Credits received from this course are used to fulfill the Practical Training requirement for the MA degree.
Students enrolled in the MA in Biotechnology Program have the opportunity to receive academic credit while conducting Supervised Research under the guidance of a faculty mentor within the University (S5502) or a biotech business-specific Supervised Internship outside the University (S5503) within the New York City Metropolitan Area unless otherwise approved by the Program. Credits received from this course are used to fulfill the Practical Training requirement for the MA degree.
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.
Prerequisites: all 6 MAFN core courses, at least 6 credits of approved electives, and the instructors permission. See the MAFN website for details. This course provides an opportunity for MAFN students to engage in off-campus internships for academic credit that counts towards the degree. Graded by letter grade. Students need to secure an internship and get it approved by the instructor.
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.
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.
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.
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.
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.
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.
This asynchronous, 1.5-credit elective integrates a supervised professional internship with structured reflection and applied coursework to help students connect academic learning to real-world practice. Through career design, goal setting, and reflective exercises, students clarify professional interests, build adaptability, and articulate the impact of their internship on future career pathways.
This asynchronous, 1.5-credit elective integrates a supervised professional internship with structured reflection and applied coursework to help students connect academic learning to real-world practice. Through career design, goal setting, and reflective exercises, students clarify professional interests, build adaptability, and articulate the impact of their internship on future career pathways.
This asynchronous, 1.5-credit elective integrates a supervised professional internship with structured reflection and applied coursework to help students connect academic learning to real-world practice. Through career design, goal setting, and reflective exercises, students clarify professional interests, build adaptability, and articulate the impact of their internship on future career pathways.
This asynchronous, 1.5-credit elective integrates a supervised professional internship with structured reflection and applied coursework to help students connect academic learning to real-world practice. Through career design, goal setting, and reflective exercises, students clarify professional interests, build adaptability, and articulate the impact of their internship on future career pathways.
This asynchronous, 1.5-credit elective integrates a supervised professional internship with structured reflection and applied coursework to help students connect academic learning to real-world practice. Through career design, goal setting, and reflective exercises, students clarify professional interests, build adaptability, and articulate the impact of their internship on future career pathways.
This asynchronous, 1.5-credit elective integrates a supervised professional internship with structured reflection and applied coursework to help students connect academic learning to real-world practice. Through career design, goal setting, and reflective exercises, students clarify professional interests, build adaptability, and articulate the impact of their internship on future career pathways.
This asynchronous, 1.5-credit elective integrates a supervised professional internship with structured reflection and applied coursework to help students connect academic learning to real-world practice. Through career design, goal setting, and reflective exercises, students clarify professional interests, build adaptability, and articulate the impact of their internship on future career pathways.
This asynchronous, 1.5-credit elective integrates a supervised professional internship with structured reflection and applied coursework to help students connect academic learning to real-world practice. Through career design, goal setting, and reflective exercises, students clarify professional interests, build adaptability, and articulate the impact of their internship on future career pathways.
This asynchronous, 1.5-credit elective integrates a supervised professional internship with structured reflection and applied coursework to help students connect academic learning to real-world practice. Through career design, goal setting, and reflective exercises, students clarify professional interests, build adaptability, and articulate the impact of their internship on future career pathways.
This asynchronous, 1.5-credit elective integrates a supervised professional internship with structured reflection and applied coursework to help students connect academic learning to real-world practice. Through career design, goal setting, and reflective exercises, students clarify professional interests, build adaptability, and articulate the impact of their internship on future career pathways.
This asynchronous, 1.5-credit elective integrates a supervised professional internship with structured reflection and applied coursework to help students connect academic learning to real-world practice. Through career design, goal setting, and reflective exercises, students clarify professional interests, build adaptability, and articulate the impact of their internship on future career pathways.
This asynchronous, 1.5-credit elective integrates a supervised professional internship with structured reflection and applied coursework to help students connect academic learning to real-world practice. Through career design, goal setting, and reflective exercises, students clarify professional interests, build adaptability, and articulate the impact of their internship on future career pathways.
This asynchronous, 1.5-credit elective integrates a supervised professional internship with structured reflection and applied coursework to help students connect academic learning to real-world practice. Through career design, goal setting, and reflective exercises, students clarify professional interests, build adaptability, and articulate the impact of their internship on future career pathways.
This asynchronous, 1.5-credit elective integrates a supervised professional internship with structured reflection and applied coursework to help students connect academic learning to real-world practice. Through career design, goal setting, and reflective exercises, students clarify professional interests, build adaptability, and articulate the impact of their internship on future career pathways.
This asynchronous, 1.5-credit elective integrates a supervised professional internship with structured reflection and applied coursework to help students connect academic learning to real-world practice. Through career design, goal setting, and reflective exercises, students clarify professional interests, build adaptability, and articulate the impact of their internship on future career pathways.
This course offers a comprehensive introduction to a branch of machine learning called generative modeling, focusing on the underlying concepts, theoretical techniques, and practical applications. The defining property of Generative AI models is their ability to generate new data similar to a given dataset. In recent years, Generative AI has seen rapid advancement, revolutionizing various industries by enabling machines to create realistic and novel content, ranging from images, videos, and music to text and complex simulations.
Students will learn to use, fine-tune, and programmatically interface with high-level APIs and open-source foundational models, allowing them to leverage state-of-the-art tools in Generative AI. Additionally, the course delves into the theory and practice of low-level implementations, empowering students to train their own models on their own data and understand these models from first principles. The course covers various types of generative models, including Variational Autoencoders (VAEs), Generative Adversarial Networks (GANs), and Transformers with their applications to text, image, audio, and video generation.
By combining these approaches, this course provides a robust foundation in both the practical application and deep theoretical knowledge required to develop innovative AI solutions.
Over the past decade, the Internet of Things (IoT) has transformed industries by enabling real-time data collection, analysis, and automated control through interconnected devices. Advancements in networking, cloud computing, and robotics have expedited IoT adoption, impacting a wide range of fields from home safety and industrial automation to healthcare and autonomous driving. Additionally, the rise of artificial intelligence (AI) led to the emergence of the Artificial Intelligence of Things (AIoT), which combines IoT connectivity with AI-driven decision-making to enhance smart systems.
This course provides a comprehensive understanding of IoT technologies and their integration with AI and robotic systems. Students will explore IoT architecture, key components, and communication protocols while gaining hands-on experience with IoT platforms, sensors, and data acquisition devices. The curriculum emphasizes practical AIoT applications for real-time decision-making in manufacturing, public safety, smart cities, healthcare, etc., and addresses the ethical considerations of these technologies.
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.
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.
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.
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.
Explores key concepts of behavioral economics and cognitive psychology, how to identify key cognitive biases in ERM activities, and how to apply techniques to address these, enhancing the quality and integrity of an ERM program. The course also includes best practices in leveraging analytic models to improve decision making.
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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.
Retirement Planning offers a comprehensive foundation in the principles, practices, and policies that shape retirement readiness. The course examines the major types of retirement plans, their structures, and the regulatory and taxation considerations that influence them. Students will develop the ability to conduct retirement needs analyses, evaluate key assumptions, and align plans with client goals. In addition, the course engages students in a comparative study of Social Security, Medicare, and Medicaid, highlighting their roles, limitations, and intersections with private retirement strategies. Through case analyses and applied exercises, students will learn to distinguish among plan options, weigh trade-offs, and make informed recommendations, culminating in a problem-based learning project.
This highly experiential course helps students design, launch, and sustain a successful career. Blending scholarly foundations with practical tools and hands-on coaching, this course guides students through identifying their personal strengths and professional identity, developing a compelling personal pitch, and building the skills needed to navigate interviewing, networking, teamwork, organizational culture and change. Each session integrates theory, applied practice, and structured role-play with peer feedback, enabling students to move beyond a job search mentality toward a proactive, values-aligned approach to career development and long-term professional success.
This course offers students a strategic and applied framework for understanding the global financial services industry, spanning commercial and investment banking, asset and wealth management, central banking, and financial regulation.
Students will examine the sector’s evolution, current challenges, and future direction. Topics include risk management, regulatory change, global competitive positioning, and the strategic dilemmas facing today's financial CEOs.
The course emphasizes leadership and critical thinking over technical specialization, and culminates in a team-based final project. The course is intended for students preparing for leadership roles in global finance..
Delivered in person during Summer Session A, this 1.5-credit elective course is open to graduate students across the School of Professional Studies and other Columbia University programs. There are no specific competencies, prerequisite knowledge, or prior coursework in the discipline required to enroll.
This course offers students a strategic and applied framework for understanding the transformative impact of financial technology (FinTech) on the global banking and financial services industry. Through case studies, industry analysis, and collaborative projects, students will explore how traditional banks, fintech unicorns, and big tech firms are reshaping the competitive landscape.
The course traces the evolution of fintech across the payment network, while examining the rise of disruptive technologies such as artificial intelligence, open banking, and digital currencies, including CBDCs, and cryptocurrencies. Students will also analyze the regulatory and governance challenges emerging from rapid innovation in financial services.
Emphasizing strategic thinking, leadership, and applied analysis over technical specialization, the course culminates in a team-based final project. It is designed for students aspiring to leadership roles in the evolving global digital financial ecosystem.
Delivered on-line during Summer Session B, this 1.5-credit elective course is open to graduate students across the School of Professional Studies and other Columbia University programs. There are no specific competencies, prerequisite knowledge, or prior coursework in the discipline required to enroll.
At the end of this course, students will be prepared to fully evaluate the technical and financial aspects of a solar project. They will be equipped with skills allowing them to either develop or rigorously vet solar project proposals. The course introduces and provides students with a holistic understanding of the end-to-end solar development process. The course has two goals:
To provide students a deep understanding of the dozens of critical interrelated steps critical to developing a successful operating solar project.
To equip the students with the tools and understanding of the skills necessary to develop a solar project beginning with site selection encompassing the entire process to commissioning and operations.
This course serves as the introduction and prerequisite for PS5705.001 Global Fieldwork in Communication. Students learn foundational frameworks for cross-cultural communication and collaboration in a global context, preparing them for success during their study abroad experience. Students must attend all three intro sessions to be eligible for the Global Fieldwork course.