Summer & Fall Online Classes

Explore how dispute resolution shapes environmental and public-policy conflicts through U.S. and international case studies, mediator guest speakers, and interdisciplinary readings. 
Learn how mediation, courts, agencies, and emerging technologies (including AI) affect public participation, policy outcomes, and democratic processes.
Satisfies the Integrative Experience requirement.

*For summer 2026, Public Policy courses use the "SPP" rubric EXCEPT for this course, which is using our new rubric: "PUBPOL".
 

Theories of policy-formation are applied to several timely issues of US and global policy. Issues are grouped around a broad theme, such as environmental policy or security. Relevant experts/policymakers will help students complete policy simulations on our issues.

Learn how emerging technologies, such as artificial intelligence, big data, and algorithmic systems, reshape public administration, policy design, and service delivery. Students will examine the opportunities and risks of digital governance, with attention to ethics, public value, and practical implementation. Through case studies and applied analysis, students will develop strategic and managerial tools to lead innovation in complex, tech-driven public environments.

This course is excellent for those who may be involved in nonprofit organizations as directors, employees, volunteers, customers, funders, or founders. 

Learn about how nonprofit and tax-exempt organizations shape US society and policy. Discuss the theoretical bases for the nonprofit sector and for tax exemption as well as the key legal elements of managing a charitable entity in the U.S.

Study the contemporary public policy issues and debates. The course offers various perspectives on public policy, including equality, justice, and efficiency. The subjects covered are: environmental policy, affirmative action, immigration, welfare policy, education, health, and other public policies.Emphasis on in-class discussion and debates.
(Gen. Ed. SB, DU)

Examine the influence of political factors, including institutions and interests, on the initiation, formulation, and implementation of public policy. Analyze the role of information and expertise in politics. 

This is an advanced seminar focusing on public budgeting. Develop an understanding of the institutions, issues, and processes involved in budgeting as well as related analytical skills that will give you the ability to function in careers in financial analysis and budgeting.

Learn how local governments handle fiscal stress and economic development, and how elected officials build support and resources. Study New England case studies, examine the political DNA of the millennial generation, study the unique obstacles young people face when they run for office, examine the techniques for finding success in large, complicated government and legislative institutions, and closely analyze specific policy areas where millennial state legislators, mayors, and city councilors are making a real difference. Identify a real local problem, draft state/municipal legislation, and produce a strategic roadmap to secure its passage.
Requires full preparation and active participation.

This course is an introduction to Geographic Information Science (GIS) - the science of spatial relationships, linking data to locations to explore relations between objects. Learn the basic concepts of GIS through practice and theory, to enable you to make useful and meaningful contributions to various disciplines through spatial analysis.

Introduction to methodologies for analyzing, implementing, and evaluating public policy. Topics include research methods, participant observation survey research and questionnaire construction, research design, measurement theory and practice, and framing categories.

This is a high-level overview of Internet and technology policy from a Public Interest Technology perspective, covering key issues in areas like AI, social media, fintech, and health within a global and public sector context. It will provide the information, bibliography, identification of field actors, and networking opportunities for students to be empowered to build their own life-long learning experience if desired and/or apply the ideas to whatever context they are actively working in or want to be working in.

Explore the use of grant funding as a revenue strategy. Build knowledge of grant funding opportunities and learn about the process for developing a grant proposal from beginning to end including the creation of a grant budget and compelling case for support.

*This class will have some synchronous meetings.

Learn the basics of the R programming language while building essential data management and wrangling skills to meet the need for versatile data science expertise required for advanced quantitative coursework.

Learn the language of behavioral research with an emphasis on designing social science research. Engage with measurement reliability and efficacy, internal or external research design validity and generalizability.

Learn the causal thinking plus modules on measurement, prediction, exploratory data analysis, probability, and uncertainty (estimation, confidence intervals, hypothesis testing, power).

Learn how to use Python, a popular and powerful programming language known for flexibility and ease of use, by diving into the tools that are particularly beneficial for social data scientists and data professionals.

Introduction to qualitative research methods, including interview and ethnographic research, inductive data collection and analysis, and the benefits and challenges of qualitative research.

*Class will start JUNE 15 and run through Summer Session II.

Grasp an overview of machine learning (ML) with special attention to applications for social and behavioral analytics. Machine learning combines insights from AI, probability theory, statistical inference, and information theory to help automate tasks involving pattern recognition, prediction, and classification.

A math boot camp for incoming DACSS and select PhD students, designed to build or refresh the math needed for applied statistics and computational work. Covers algebra, key calculus concepts, probability, and basic linear algebra as a fast-paced review of fundamentals.

Learn the basics of the R programming language while building essential data management and wrangling skills to meet the need for versatile data science expertise required for advanced quantitative coursework.

This course reviews different computational social science methods that are applied under different academic and professional situations. This includes different but complementary methods to format and explore data as tables, maps, graphs, and text.

Study networks across the sciences have exploded recently. Deep dive on the network scientific theory as it applies to the social sciences, network data collection and management, network visualization and description; and methods for the statistical analysis of networks. Will make extensive use of real-world applications to gain a thorough background in the use of network analytic software. 

Join this math boot camp for incoming DACSS and select PhD students, designed to build or refresh the math needed for applied statistics and computational work. Covers algebra, key calculus concepts, probability, and basic linear algebra as a fast-paced review of fundamentals.

Learn the basics of the R programming language while building essential data management and wrangling skills to meet the need for versatile data science expertise required for advanced quantitative coursework.

Learn the language of behavioral research with an emphasis on designing social science research. Engage with measurement reliability and efficacy, internal or external research design validity and generalizability.

Learn the causal thinking plus modules on measurement, prediction, exploratory data analysis, probability, and uncertainty (estimation, confidence intervals, hypothesis testing, power).

Learn how to use Python, a popular and powerful programming language known for flexibility and ease of use, by diving into the tools that are particularly beneficial for social data scientists and data professionals.

Gain the tools to think critically about how data-driven systems influence our lives—and the responsibilities we share in shaping their future.

Learn how social scientists convey data through narrative and visual reports geared toward general audiences or non-scientists. This hands-on course provides students with the knowledge and skills needed to generate strong, data-driven communication.

Learn the computational approaches for studying complex social systems, combining foundations from complexity science with agent-based modeling (ABM) as a tool for theory construction, exploration, and policy-relevant reasoning.

This course offers an introduction to spatial analytics using both GIS and R, with primary focus on social scientific research, social justice concerns, and social and public policy related inquiries. Dive into descriptive statistics in the context of spatial data and overview techniques of introducing robustness in the specification of spatial OLS.

Gain the tools and skills to collect, organize, cleanse, format, integrate and transform data so that it is ready for analytical work in the social sciences. We will cover R and Python in parallel, so that you enhance your skills with these popular and powerful languages, while understanding what each one offers for the pre processing stage.

Grasp an overview of machine learning (ML) with special attention to applications for social and behavioral analytics. Machine learning combines insights from AI, probability theory, statistical inference, and information theory to help automate tasks involving pattern recognition, prediction, and classification.

Learn learn how to convert text to formats suitable for quantitative analysis. This will include relatively simple dictionary approaches for measurement and feature supervised learning approaches for document classification, vector representations, contextualized embeddings, and more.

This course teaches you how to program in Python for working with large, complex datasets often used in computational social science. You’ll learn how to build scalable data workflows, handle different types of data (like text, geospatial, and administrative data), and use tools such as pandas, SQL, and PySpark. The course also emphasizes writing efficient, reproducible, and responsible code, while helping you understand the tradeoffs and real-world implications of working with big data.

Learn advanced methods for analyzing text as data, from foundational concepts to cutting-edge techniques like word embeddings and deep learning. Build and apply your own models while exploring how text analysis is transforming social science research and causal inference.

Study the basic issues of law's relationship to contemporary society and how law affects almost all human activity. Interdisciplinary topics include the nature, historical, and social functions of law and the culture, tension between ideals and realities in law and the role of law in addressing contemporary social problems. This general education course, based on the assumption that "law is too important to be left to lawyers," is intended to foster analytical and critical skills and to discuss broad, interdisciplinary questions of individual responsibility, social morality, and justice.
(Gen.Ed. SB, DU)

This is an interactive, interdisciplinary course on resolving environmental and public-policy disputes.
- Learn through U.S. and international case studies and guest mediators.
- Read core texts from legal studies, conflict resolution, political science, public policy, geography, computer science, public health, and more.
- Examine how dispute resolution affects democratic participation and how courts and agencies use mediation and ADR in high-stakes environmental conflicts.
- Explore the impact of technology and the emerging role of AI in public disputing.
- Ideal for students of law, policy, environment, conflict resolution, and anyone interested in practical, scholarly approaches to real-world disputes.
IE, Sr & Jr Legal Studies majors only, consent of the instructor for non-Legal Studies majors.

Improve your ability to analyze and write about complicated legal issues. Learn how to read and understand court opinions and how to find your way around a law library. Writing assignments include your own resume and a job application letter, case briefs, memoranda, op-eds, and a research paper.
Open only to Legal Studies majors who have completed LEGAL 250 and College Writing (CW).

Explore how the Supreme Court has shaped American rights and liberties—historically and today.
Start with the power of textual rights protections and the rise of legal institutions that mobilized for individual rights.
Analyze landmark decisions and learn why some rights were recognized earlier than others.
Thematic focus: religious freedom, speech, guns, criminal defendants’ rights, and gender & sexuality discrimination.
Finish with recent constitutional controversies about personal freedom.
Ideal for students of law, political science, history, and anyone who wants to read and argue major Supreme Court cases.

Intensive, interdisciplinary course on human trafficking—its definitions, debates, and real-world responses.
Study legal definitions and policy frameworks in the U.S. and internationally.
Analyze debates over slavery vs. trafficking, and the meanings of choice, coercion, and victimization.
Learn how trafficking is measured, how victimhood is framed by different stakeholders, and ethical challenges in research and advocacy.
Examine law enforcement investigations and practical responses to trafficking in persons.
Ideal for students in law, policy, social work, criminology, public health, and human rights who want rigorous, applied understanding of modern forced labor and exploitation.

Improve your ability to analyze and write about complicated legal issues. Learn how to read and understand court opinions and how to find your way around a law library. Writing assignments include your own resume and a job application letter, case briefs, memoranda, op-eds, and a research paper.
Open only to Legal Studies majors who have completed LEGAL 250 and College Writing (CW).

Study the basic issues of law's relationship to contemporary society and how law affects almost all human activity. Interdisciplinary topics include the nature, historical, and social functions of law and the culture, tension between ideals and realities in law and the role of law in addressing contemporary social problems. This general education course, based on the assumption that "law is too important to be left to lawyers," is intended to foster analytical and critical skills and to discuss broad, interdisciplinary questions of individual responsibility, social morality, and justice.
(Gen.Ed. SB, DU)

As we think through what shape AI laws may take, it is important to ponder the ethical implications for- and obligations of- society. In this course, we will examine the historical foundations of ethics, pertinent concepts and terms, the role of bias, social impacts, current events, laws and regulations, as they relate to AI. This is designed to be an interactive course. Students will have the chance to work on group case studies and engage in thoughtful classroom discussions about these topics. Students will also be assessed primarily on written essays where they will be asked to think critically and reflect on the topics presented in class.

Introduction to humanitarian law. Topics include theory and history of international human rights law, growth and nature of human rights organizations, regional human rights schemes, cross-cultural contexts and meanings for human rights, the politics and law of immigration and refugees, international criminal law and other mechanisms for humanitarian intervention. 

Prerequisite: LEGAL 101
Satisfies the Integrative Experience requirement for BA-Legal major.