Courses 

This course blends history with social science theory and policy concerns in a study of the theoretical underpinnings of strategy and its intersection with technology. The course examines several historical case studies in which technological innovations intersected with history-making demands. The course also analyzes contemporary issues related to technology and strategy, focusing on U.S. defense policy in the post-World War II era. The overriding idea of the course is that no technology is strategic by definition. It is the way technology is used and continually reinvented that makes it strategic.  

This course examines challenges in energy, logistics and information processing, and rapid offensive and defensive systems in the context of the past, the present and the future to develop new conceptual insights, research priorities, system integration and timely methods to meet emerging national defense engineering needs. The curriculum considers such topics as the Manhattan Project, the development of containerized shipping, artificial intelligence, hypersonics, railgun technology and more. Each module covers different topics while prompting students to examine creative solutions inspired by the past and use the lessons learned to stimulate thinking needed for solving future challenges.  

In today’s rapidly evolving technological landscape, ethical decisions are increasingly crucial for technology developers, entrepreneurs, policymakers and consumers alike. This course explores the principles of ethical reasoning and their application to complex technological dilemmas. 

Through a structured learning approach, we examine key concepts in ethics, including Deontological, Consequentialist and Virtue Ethics, and apply these frameworks to analyze tradeoffs in various technological contexts. Students will engage with real-world case studies that highlight the importance of context-sensitive thresholds and principled reasoning in technology decision-making. 

We delve into the nuances of tradeoff analysis, exploring how competing values such as autonomy, justice, trust, benevolence, non-maleficence and transparency must be weighed against one another. Through a combination of theoretical foundations, experiential learning and critical analysis, this course aims to develop students’ ability to think critically about ethical issues in technology and make informed decisions that balance competing values. 

This course examines how U.S. defense technologies move from concept to capability through the interplay of law, politics and strategy. Framed around the policy levers of Congress —authorizations, appropriations and oversight — it traces how the National Security Council, Department of Defense and the legislative branch define requirements, allocate risk and resources and shape the innovation ecosystem that delivers warfighting advantage. Students analyze historic and contemporary cases (from interwar armor and airpower to the F-14/F-16 debate and the nuclear enterprise) to understand why some innovations flourish while others stall. By the end, participants will be able to (1) describe the institutional and political structures that govern U.S. warfighting innovation, (2) evaluate case evidence to draw lessons for future programs, (3) identify key actors and mechanisms in the NSC, DoD and Congress that influence policy, (4) analyze how military need, political interest and technological feasibility intersect across acquisition and (5) develop policy-relevant insights to improve or reform the defense innovation pipeline. 

The course explores how AI technologies can optimize business processes, improve efficiency and transform operational models across all sectors, including warfighting. It highlights human-AI interaction within organizational contexts. No programming skills are required, but it does require computer and digital literacy appropriate for managing organizations with extensive IT environments.  

This course provides learners with strategic foresight tools and skills to understand and make decisions regarding the future. Strategic foresight is the ability to create and sustain a variety of high-quality, long-term views and apply insights in adaptive ways. Strategic foresight produces forward-looking views, commonly referred to as scenarios. These are used to broadly describe what a future world would look like and how it would feel to live in that world. These scenarios form the basis for strategies and plans to help organizations remain competitive in the foreseeable future. Students in the course will use strategic foresight to create their own scenarios.  

This course analyzes the origins, tensions and promises embedded in space-focused strategies. The course material discusses these issues from the national and strategic interests perspective, focusing on how competition and conflict in space — the most recent domain in which nations and great powers dispute political, military, economic and legal interests — could and should be handled. That question is examined in the context of grand strategy, defined as the harnessing of military, economic and political power over decades and centuries to advance the nation. Space is the ultimate high ground and if the United States wants to continue in its preeminent position, it must remain diligent.  

Cybersecurity is a crucial domain upon which individuals, organizations, communities, states, nations and great powers rely to protect cyber-based personal, business, economic, infrastructural, community, legal, strategic political and military interests. The course analyzes the policies, issues, risks and opportunities embedded in the cyber strategies of organizations. The course will discuss these issues from the perspective of the U.S. national and strategic interests, focusing on how cyber issues and conflicts could and should be handled. Among the cyber strategy key considerations to be discussed are: Understanding and assessing an organization’s cyber threat landscape; Assessing an organization’s cybersecurity maturity; Organizational cyber strategy goals; Cyber strategy policy-making process; Examination of strategies for strengthening, defending and maintaining an organization’s cyber infrastructure — models, requirements, frameworks, and best practices; Management commitment and responsibilities to an organization’s cyber strategy and policies; Cyber strategy staffing, training, and budgeting; Global and domestic cyber business relationships in governmental and private industry; Promoting awareness of historic, ongoing, and emerging cyber threats and actors; Promoting awareness of domestic, global and insider cyber threats and actors; Cyber risk management; Cyber incident management.

Strategic Intelligence refers to the collection of organizations, technologies, procedures and policies that great powers, particularly the United States, use to provide the supreme political leadership with the understanding needed to plan and execute future national security strategies. A significant portion of the strategic intelligence process is conducted by specialized organizations that use advanced technologies. The intelligence can, in turn, focus on the technological capabilities of the country hosting the strategic intelligence organization or its adversaries. Thus, strategic intelligence has a significant technological component, both as a tool for and as a domain for investigation. The course will examine all facets of strategic intelligence, anchoring the investigation around specific organizations and processes from the major civilian to the major military-strategic intelligence agencies, the legislation that directs their work, and the supervisory bodies. The course will also include case studies that analyze and operationalize how intelligence agencies contribute to national security. The course aims to provide students with a rounded and practical education in strategic intelligence, describing who is responsible for its deployment and exploitation and what its benefits are for national security. 

This course centers around understanding and communicating data in a way that informs, compels or reassures — a core personal and professional skill for anyone who wants to be a successful member of the 21st century community. Telling effective data stories combines elements of rhetoric, data science, visualization and storytelling, with artificial intelligence now becoming a prominent tool in the process. The course is subdivided into six modules. The first module covers the basics of storytelling with the following five modules diving deeper into each step of building a data story that surprises, provides a new, more convincing alternative to time-worn ideas and proposes a course of action. The goal of the class is to train learners in making memorable, teachable and data-driven arguments in the form of stories.  

This course equips organizational leaders to understand and govern AI as an operational capability that improves process performance, efficiency and mission outcomes across sectors, including defense. It frames AI primarily as predictive decision-support built on statistical and probabilistic inference, then shows how real organizations industrialize AI — using Uber’s Michelangelo platform as a case in disciplined scaling that reduces duplicated engineering, controls infrastructure costs and ensures AI systems deliver measurable value. Building on that foundation, the course focuses on evaluation, monitoring and lifecycle management (from pilot to enterprise deployment), emphasizing risk, accountability and performance at scale. The defense segment applies these same principles to warfighting organizations, examining how AI can shape information advantage and command-and-control and then compares contemporary AI doctrines and operational approaches across the U.S., China, Russia, Ukraine and other actors to surface tradeoffs, constraints and likely near-term scenarios. The course concludes by applying a structured uncertainty lens (Johari window) to future human–AI teaming — highlighting where AI is reliable, where it is brittle and where “unknown unknowns” create strategic surprise — before culminating in a capstone in which participants design and critique AI-enabled solutions for realistic defense cases. No coding is required, but participants should be comfortable navigating the digital realities of IT-intensive organizations. 

This course examines concepts, models and methods useful for applying data analytics in business environments. Focusing on hypothesis generation, capturing, storage and expression of data and analysis for research and visualizations.   

Examines how emerging technologies like artificial intelligence (AI), automated decision systems and digital platforms are being adopted in the public sector. It explores the benefits as well as ethical risks and challenges associated with implementing these technologies in areas like healthcare, education, child welfare and criminal justice. Students will analyze governance strategies, policies and administrative procedures to promote responsible technology use in government.   

This course provides an overview of the role of tech diplomacy in international relations and foreign policy, focusing on how emerging technologies can disrupt global power structures and create both risks and opportunities. Students will study core theories, analyze case studies, and develop skills in applied research and communication.

This course focuses on understanding contemporary emerging technologies and their implications for tech diplomacy, national security, and foreign policy. Students develop skills through analyzing case studies and developing applied projects that assess threats and opportunities in an area of emerging technology.

This course provides an overview of how to transform social media and digital media information into business intelligence and actionable insight. Although students are not expected to know a programming language prior to taking the course, students are expected to understand basic statistics and to have a desire to learn the processes, procedures and vocabulary used by data analysts in modern organizations. The goal is not to train them as practicing data scientists but as knowledgeable data analytics consumers and as informed teammates and leaders of cross-functional teams tasked to make decisions using data.