All courses are compulsory:
Data Applications and Regulation in Digital Society
This course introduces students to legal perspectives on the big data revolution. This course aims to provide students a general overview of how these new technologies (artificial intelligence, machine learning and data science) influence and change our lives. This course also explores on legal implications of these new technologies in various areas of the society. This course is intended both for students of data science who want to reflect on the legal implications of their field, and for students from other disciplines who want to explore the legal impact of data sciences.
Big Data Analytics and Compliance in E-business
Big data analytics is emerging as a fundamental part of strategic planning and decision making in modern businesses. The success of data-analytics embedded e-business strategy not only depends on proficient analytical models but also effectively addressing a range of challenges and externalities that are beyond the control of individual enterprises. This course is aimed at developing the ability to identify and address various challenges including legal and compliance requirements impacting relevant strategies. Challenges facing data-analytics applications at various stages of e-business cycle including predictive-analytics in business-to-business and business-to-consumer sectors and effective means to strengthen the strategies will be covered.
Data Strategy and Protection in Healthcare and E-governance
The course is designed to introduce students to gain an in-depth understanding of e-governance for the regulation of data security and information protection. It examines a regulatory framework for addressing data privacy issues in e-governance and legal challenges associated with the data collection and usage by various public agencies. The course also gives a focused examination of digitalized healthcare and biomedical research, and the regulations that govern them. It addresses not only privacy and security matters but also other important challenges, such as those related to data quality and data analysis in precision medicine and clinical research.
Artificial Intelligence and Comparative Law
Developing effective Artificial Intelligence (AI) applications entails the ability to identify relevant opportunities and challenges and address them strategically. This course aims to explore the nexus between AI and law and introduce contemporary and emerging issues in the field. It will study specific AI applications and identify related legal challenges and compare how key jurisdictions regulate such challenges. The course will cover potential legal risks and liability facing users of AI and discuss precautionary measures to limit liability. Data protection and privacy obligations and Intellectual Property Rights Protection of AI Programing and Algorithms of Machine Learning will be comparatively studied. Read More
The Project Report serves the purpose of demonstrating the ability to systematically analyze the fundamental relationship between law and data applications and related strategies in a specific context. Students will identify, study, and critically examine key inter-disciplinary issues arising in the context of a chosen topic or a case study approved by the Faculty. The students may conduct a fundamental or applied research to seek practical solutions to legal and policy challenges facing formulation and implementation of effective data strategies. A faculty member competent in the selected legal field will supervise the project research and finally approve the project report.