English

This course explores key sustainable development challenges, including climate change, poverty, inequality and social justice. It explores the concept of sustainable development and assesses the effectiveness of a range of approaches to development. The role of government, business and civil society in addressing global challenges is considered.

What are the roots of our concern for the environment? What did environmental activism look like in the 1960s, the 1930s or even the 1870s? This course offers a survey of where environmentalism has come from and where it is going. This course provides students with a deeper appreciation for the history of environmentalism. We learn about links between the development of the sciences of the environment and environmentalism as a social movement. The geographical focus in this course is on Europe and North America. However, students also locate and interrogate how environmental concern and policy has developed in various parts of the globe. Students note the experiences and contributions of different identity groups. In doing so, they consider the impact of and reactions to European imperialism and postcolonial globalization. They also examine and critique the role of the United Nations and other international organizations in environmental affairs.

This course covers the history of western philosophy from the Greek era to the present and changes in debates and concepts of major philosophers.

This course introduces the basic theories, model architectures, algorithms, and implementation of deep learning for computer vision. Students obtain hands-on experience on implementing and training deep neural networks for computer vision tasks. The course covers the following topics: (1) neural network optimization algorithms; (2) backbone network architectures for computer vision, including convolutional neural networks and transformers; (3) network structure design for visual recognition tasks (image classification, object detection, image segmentation), and visual content generation tasks; (4) implementation and training of neural networks for computer vision tasks; (5) advanced topics in computer vision and deep learning. 

This course examines the rise of human rights discourse and its relationship to other discourses on suffering and social justice. It focuses on the experience of victims of human rights abuse and the politics of meaning. Students will engage in critiques of law as a reductionist discourse on the social by exploring the relationships between human rights and cultural differences such as gender, ethnicity, religion and indigenous cultures. The embodied self, social interdependency and the architecture of social institutions are the backdrop through which the course explores the tensions between universal and relativist understandings of human rights and their realization. Students will be introduced to the fundamentals of human rights, the global human rights machinery, and the ethics of humanitarian intervention, and will consider how sociologists have studied and written about human rights.

This course introduces the study of meaning. With the rapid rise in practical applications of artificial intelligence systems, it is now more crucial than ever for us to define what it means to be human, and there is nothing more humanistic than studying the concept of meaning itself. 

Students engage with some of the most influential scientific, literary, and philosophical texts that have shaped the world today with the objective to move beyond a passive understanding. Students are challenged to think critically and actively about how the ideas put forth in these texts have come to be rejected, revised, and/or replaced, and how this very process of the shifting dominant narrative of meaning (i.e., not just the works by themselves in isolation) continues to influence the society and culture that they currently live in. 

Topics include Writing systems, Rhetoric, Similes, metaphors, and meaning, Creating new knowledge via logic, What is knowledge, Are signs arbitrary, Meaning as behavior, Language and thought Sarcasm, Mathematical meaning (axiomatic system), Mathematical meaning (axiomatic system), Can computers and AI understand meaning, Society and language use, How might aliens define meaning. 

This course introduces students to the field of information management with particular emphasis on the management of information within organizations. Students are provided with opportunities to explore the basic concepts and principles of information management as well as apply these concepts and principles to practical problems. Advanced topics are also introduced throughout the course to foster greater depth of understanding, to challenge students to think about established issues in new ways, and to highlight gaps in our current understanding. Some appreciation is also fostered for the limitations of empirical research and for the unique challenges associated with the management of information. The course discusses themes that are directly relevant to producing information management professionals. Some of these topics are measuring the impact of IT on business performance; IT consumerization; Big Data: the role of business intelligence and business analytics; IT governance; and information security. All of these topics are on the top of the agenda of an information manager, and practitioners are constantly looking for methods to better address these issues. For non-IM specialists, a discussion of these topics helps to understand the most relevant problems that are part of using IT in organizations. Given the widespread use of IT, managers who are active outside the field of IT also deal with many of these same problems on a regular basis. The discussion of each topic focuses on methods and tools that are being used by practitioners to deal with these issues. For most topics, additional readings are available to provide background knowledge for students who lack the relevant prior knowledge.

This course covers the tools and systems used to implement cloud computing systems, and presents key issues to be addressed, such as virtualization. Students learn cloud system platform technologies and detailed component technologies then configure servers and perform programming on public clouds like Amazon Cloud System (AWS) or Google Cloud System. 

Topics include Cloud computing concepts, Cloud computing models, Cloud computing architecture, Cloud computing platforms, Virtualization, Synchronization, Coordination, Distributed deadlock. 

This course is part of the Laurea Magistrale degree program and is intended for advanced level students. Enrollment is by permission of the instructor. The purpose of the course is to provide students with a background in science to the methods and policy tools used in environmental and resource economics in order to achieve efficient management of pollution and environmental resources. More specifically, the course will introduce the concept of environmental externalities as the main source of environmental degradation, and the policy instruments used to correct these externalities. The course also includes an introduction to climate change economics and climate policy. Student having successfully completed the course are expected have a good understanding of issues and economic policies related to controlling environmental pollution and climate change. The course covers the two main approaches to the economics of the environment and natural resources - Environmental economics and Ecological economics - with a special focus on the Economics of climate change.