Courses 

Description This course introduces students to the mathematical tools and techniques used in jurimetrics, the field that applies mathematical and statistical methods to legal science. The course covers topics such as logic, set theory, graph theory, probability theory and primary linear algebra, with a focus on applications to legal problems. Students will learn how to use mathematical models and techniques. The course will also explore the ethical and social implications of using mathematical methods in law, including issues related to bias, fairness, and transparency. The primary emphasis is on discovering the accurate mathematical solution to a legal science problem, rather than on calculations or generating mathematical proofs.

Learning path Jurimetrics research, Legal risk management

Status Available

Description This course provides an introduction to mathematical and computational tools used in LegalTech, the intersection of law and technology. The course covers topics such as statistics, advanced linear algebra, calculus, and optimization methods, with a focus on their applications in computer and data science for law. Students will learn how to apply these techniques to legal (process) problems. The course will also explore the ethical and social implications of using these technologies in law, including issues related to privacy, bias, and transparency. The primary emphasis is on discovering the accurate mathematical solution to a legal science problem, rather than on calculations or generating mathematical proofs.

Learning path LegalTech start-up, Legal process management

Status Available

Description This course provides an introduction to computer science tools and techniques used in Jurimetrics and LegalTech. The course covers topics such as database management, programming, software engineering, and (cyber)security with a focus on their applications in legal systems and decision making. Students will learn how to collect, process, analyze, and visualize (legal) data using programming languages such as Python and SQL. The course will also explore the ethical and social implications of using these technologies in law, including issues related to privacy, bias, and transparency.

Learning path Jurimetrics research, LegalTech start-up, Legal process management, Legal risk management

Status Available

Description This course provides an introduction to data science tools and techniques used in Jurimetrics and LegalTech. The course covers topics such as machine learning, deep infrastructure, Bayesian reasoning and artificial intelligence with a focus on their applications in legal systems and decision making. Students will learn how to built simple data science solutions using Python and Jupyter Notebook. The course will also explore the ethical and social implications of using these technologies in law, including issues related to privacy, bias, and transparency.

Learning path LegalTech start-up, Legal process management

Status Available

Description This course provides a historical survey of legal thought with a focus on its relevance to Jurimetrics and LegalTech. The course covers key figures and movements in legal history, including ancient legal systems, natural law, positivism, legal realism, critical legal studies, and postmodernism. Students will explore how legal thought has evolved over time and how it continues to shape contemporary legal debates and practices. The course will also examine the intersection of legal thought and technology, including how digital technologies are transforming legal scholarship, teaching, and practice.

Learning path Jurimetrics research, Legal risk management

Status Available

Description This course provides an overview of legal systems and their relevance to Jurimetrics and LegalTech. The course covers different legal systems, including common law, civil law, and religious law, and examines how they function and evolve over time. Students will learn how legal systems are organized, how they create and enforce laws, and how they handle disputes. The course will also explore the intersection of legal systems and technology, including how digital technologies are changing legal systems and how data-driven approaches can be used to analyze legal systems.

Learning path Jurimetrics research, LegalTech start-up, Legal process management, Legal risk management

Status Available

Description This course provides an overview of the Law and economics and its relevance to Jurimetrics and LegalTech. The course covers topics such as law and economics theory, cost-benefit analysis, quantitative finance, and the economics of regulation. Students will learn how to apply economic analysis to legal problems, including how to assess the costs and benefits of legal decisions and policies. The course will also explore the intersection of economics and technology, including how digital technologies are changing the economics of law and how data-driven approaches can be used to analyze legal and regulatory systems.

Learning path LegalTech start-up, Legal risk management

Status Available

Description The course on the methodology of jurimetrics introduces students to the application of advanced mathematical tools in legal research. Students will learn how to use mathematical models and statistical methods to analyze legal decision-making and systems, and extract valuable insights. Topics covered include model derivation, statistical analysis, simulation, decision theory, and applied machine learning. The course will also cover ethical considerations related to the use of mathematical methods in legal research. Students will develop critical thinking skills and the ability to apply mathematical tools to abstract- and real-world legal problems. This course is ideal for students interested in pursuing a career in legal research or data analytics in the legal industry. Prior knowledge of law, mathematics and statistics is recommended.

Status Open for enrollment

Description This course explores how quantitative methods can be used to analyze and understand legal issues and disputes. It covers topics such as data preparation, data governance, statistical analysis, and data visualization techniques, and how they can be applied in the context of legal research. Students will gain practical skills in collecting, cleaning, and analyzing data relevant to legal disputes, and learn how to interpret and communicate their findings to stakeholders. Case studies and examples will be drawn from various legal contexts, including litigation, arbitration, and regulatory compliance. This course is ideal for students interested in the intersection of law and data science, and for legal professionals seeking to enhance their quantitative analysis skills.

Status Open for enrollment

Description This course will introduce students to the use of empirical research methods in legal studies. Students will learn how to formulate research questions, design studies, collect and analyze data, and draw conclusions using statistical and other quantitative techniques. The course will cover a range of topics, including legal decision-making, judicial behavior, and the impact of legal policies on society. Students will also learn about various data sources and types, such as survey data, administrative records, and court opinions. The course will provide hands-on experience with statistical software and tools for data visualization. By the end of the course, students will be able to critically evaluate empirical legal research and conduct their own studies to answer legal questions.

Status Open for enrollment

Description This course explores the use of modelling and simulation techniques to gain insights into the functioning of legal systems. Students will learn how to design and implement simulation models that can be used to analyze and predict the behavior of legal processes and institutions. Topics covered will include agent-based modelling, system dynamics, and network analysis, as well as the use of data and computational methods to calibrate and validate models. The course will also address the practical challenges of modelling legal systems, such as identifying relevant variables, selecting appropriate modelling approaches, and evaluating model results. Students will gain hands-on experience with modelling tools and techniques, and will apply their skills to real-world legal problems.

Status Open for enrollment

Description This course in Capita Selecta in Jurimetrics Research provides an opportunity for students to delve deeper into a specific area of interest within the interdisciplinary field of jurimetrics. Through a combination of self-directed study, group discussion, and expert guest lectures, students will explore cutting-edge research topics, methodologies, and techniques in the field of jurimetrics. Students will work on individual research projects and present their findings to the class. Topics may include legal text analysis, machine learning for legal prediction, network analysis of legal systems, or other advanced quantitative techniques for studying law and legal systems. This course is designed for students with a strong background in statistics, computer science, or other quantitative disciplines, who are interested in applying their skills to the study of law and legal systems.

Status Open for enrollment

Description This course provides an overview of the LegalTech ecosystem, exploring the emerging trends and innovations in the legal industry. Students will learn about the different types of LegalTech solutions and their applications in various legal domains, such as contract analysis, legal research, e-discovery, and document automation. The course will also cover the challenges and opportunities presented by LegalTech, including the impact on legal practice and the legal profession. Through case studies, guest lectures, and hands-on activities, students will gain a deep understanding of the LegalTech ecosystem and develop critical thinking skills to evaluate and implement LegalTech solutions.

Status Open for enrollment

Description This course introduces students to the key methods and techniques used in legal process management. Students will learn how to identify inefficiencies in legal processes, and how to design and implement improvements to streamline workflows and enhance efficiency. Topics covered may include process mapping, workflow analysis, data analysis, Lean Six Sigma principles, and project management methodologies. Students will have the opportunity to work on real-world case studies to apply these methods and develop practical solutions for optimizing legal processes. By the end of the course, students should have a solid understanding of how to identify, analyze, and improve legal processes using modern management techniques, leading to increased productivity and enhanced client satisfaction.

Status Open for enrollment

Description This course provides a comprehensive introduction to blockchain technology and its applications in the legal industry. Students will learn the fundamental principles of blockchain, including distributed ledgers, consensus mechanisms, and smart contracts. They will explore the legal implications of blockchain technology, such as digital identity, regulatory compliance, and dispute resolution. The course will also cover the technical aspects of blockchain, such as cryptography, data structures, and consensus algorithms. Students will gain practical experience through hands-on projects and case studies, including the design and implementation of blockchain-based solutions for legal use cases. By the end of the course, students will have a deep understanding of the potential of blockchain technology in the legal industry and its impact on legal practice.

Status Open for enrollment

Description This course on Expert Systems in the context of law provides a comprehensive understanding of how this advanced technology is applied within the legal domain. Students will explore the principles and techniques of developing expert systems specifically tailored to legal knowledge and decision-making processes. Topics covered include knowledge representation, rule-based reasoning, case-based reasoning, and natural language processing. Practical applications of expert systems in legal research, case analysis, contract review, and legal decision support will be examined. Ethical and legal considerations surrounding the use of expert systems in the legal field will also be discussed. By the end of the course, students will be equipped with the skills to design and deploy expert systems that enhance legal processes and improve efficiency in legal practice.

Status Open for enrollment

Description This course introduces students to the methods and techniques used in quantitative legal risk management. Students will learn how to use statistical models and probabilistic analyses to assess legal risks and predict their potential impact on organizations. The course covers various topics, including decision analysis, risk modeling, scenario analysis, and simulation. Students will also explore the role of data in legal risk management, including how to collect, process, and analyze legal data. Through case studies and real-world examples, students will gain practical experience in applying these techniques to legal risk management challenges, such as litigation risk, regulatory risk, and reputational risk. By the end of the course, students will have the skills and knowledge necessary to make informed decisions about legal risk management and enhance their organizations' overall risk management capabilities.

Status Open for enrollment

Description This course will explore the principles of actuarial modeling as applied to legal risk insurance. Students will learn how to use mathematical models and statistical methods to estimate the likelihood and potential financial impact of legal risks. The course will cover topics such as loss distributions, risk measures, pricing models, and reserving methods in the context of legal risk. Students will gain an understanding of how actuarial science can be used to develop and analyze legal risk insurance products, and how these products can help businesses and individuals manage their legal risks. By the end of the course, students will be equipped with the skills and knowledge to develop and implement actuarial models in the context of legal risk insurance.

Status Open for enrollment

Description This course will cover the fundamentals of litigation reserving and funding, including the legal and financial aspects of both. Students will learn how to calculate and manage litigation reserves, as well as the various funding options available to parties involved in legal disputes. The course will also cover the role of third-party litigation funders and the ethics and regulations governing their activities. Through case studies and simulations, students will gain practical experience in evaluating the financial risks and rewards of litigation and learn how to structure funding arrangements to maximize their benefits. Overall, this course will provide students with the skills and knowledge to navigate the complex landscape of litigation reserving and funding.

Status Open for enrollment

Description This course in legal risk modeling will cover the fundamentals of modeling risk in the legal domain. Students will learn about the various types of legal risks, such as litigation risk, regulatory risk, and reputational risk, and how to quantify and model them using statistical techniques and mathematical models. The course will also cover the applications of legal risk modeling, such as pricing legal risk insurance policies and forecasting the impact of legal events on a company's finances. Students will gain hands-on experience with modeling techniques, and will develop a strong understanding of how to apply them to real-world legal risk management problems.

Status Open for enrollment