English

This course examines the fundamentals of European integration from an economic, social and political perspectives, with emphasis on both microeconomics and macroeconomics. It mobilizes a very limited mathematical formalized demonstration yet is significantly backed by data collection and analysis. It examines a variety of key EU policies: competition, industry, trade, agricultural, regional, monetary and fiscal policy. Finally, the course offers a thorough analysis of the multilateralism crisis and the war in Ukraine (among economic sanctions efficiency). Various course topics are illustrated with press releases on the latest news or interesting scientific articles and deepened through group presentations, group case studies and an individual term paper.

Evolutionary thinking provides useful new insights into the origins of diseases and contemporary health problems. This course explores the applications of the tools and concepts of evolutionary biology to human health and health-related behavior. Incorporating examples from the lecturer’s ongoing research on BaYakahunter-gatherers living in the Northern rainforests of Congo and current health problems, students cover a range of topics including: Evolution and human-microbe interactions; Hunter-gatherers as models in public health; Diet, exercise, evolutionary mismatches and non-communicable diseases; Life-history theory and reproductive health; Evolutionary perspectives on mental health and wellbeing; Cultural evolution and health-related behavior; and Applied evolutionary medicine: future of medicine and how evolutionary thinking can be applied to current health problems.

This course examines human behavior and humans' expectations of computers, computer interfaces and the interaction between humans and computers, the significance of the user interface, interface design and user centered design process in software development, and interface usability evaluation methodologies and practice.

The course covers the connection between international corporate taxation and sustainability within the frameworks of law, economics, and politics. The course topics include a range of relevant perspectives in an engaging narrative, including political challenges related to tax and sustainability (e.g. initiatives from governments and international organizations) as well as corporate challenges (e.g. how to align corporate strategies with sustainable strategies, and how to communicate tax behavior to interested parties). This is a digital, distance course consisting of a large number of video lectures, quizzes, and the writing of an individual paper.

Studying sustainable development today means recognizing the urgency of social and environmental problems facing current and future generations across the world. Students explore the relationship between human lives and the environment, debate what human "development" and "sustainability" mean, and discuss how to understand these complex and flexible concepts together. The first term focuses on understanding current and historical challenges for sustainable development, and the second term looks more closely at sustainable development programs and proposed solutions. 

This course teaches the foundational knowledge necessary to understand how modern AI systems work, with a particular focus on deep neural networks. It moves from first principles through to exploring core training algorithms that power today’s models. 

Students will construct deep networks, image classification models, and generative models such as autoencoders as well as consider how transformer architectures enable large language models such as ChatGPT.

This course explores the universe at the smallest distances and highest energies where quantum mechanics and special relativity collide. Through lectures from world-experts and hands on seminars, students will join the particle physicists from the Large Hadron Collider's ATLAS experiment in analyzing real proton collisions from the world’s largest machine - uncovering the secrets of the building blocks of the universe. The course uses coding notebooks to teach Python data analysis techniques used by professional particle physicists, progressing from the very basics, to rediscovering the Higgs boson, and culminating to an original analysis of real data. Along the way students develop computer coding, big data analysis and machine learning skills that will carry over to the real world.

This course gives students an overview of physical and chemical treatment systems for water and wastewater.

The course aims are to describe water and wastewater sources; explain the characteristics of water and wastewater (physical, chemical, and biological parameters); provide an overview of both national and international regulatory frameworks governing drinking water and wastewater management; discuss the fundamental principles of physical and chemical processes for water and wastewater treatment, and water reclamation; introduce water treatment processes including coagulation and flocculation, sedimentation, filtration, adsorption, disinfection, softening, and membrane filtration.

The course begins with an introduction to the basics of programming in Python, in particular understanding object-oriented programming and its importance to deep learning. The course quickly proceeds to an introduction to artificial intelligence, examining the fundamentals of supervised machine learning, including linear regression, logistic regression, neural networks, and gradient descent. In the second week, students explore image processing, investigating transformations, convolutional filters, and edge detection, before an introduction to convolutional neural networks and some prominent CNN architectures such as VGG and ResNet. In the final part of the course, students look at the core concepts of natural language processing, including sequence modeling, autoregressive models, and recurrent neural networks.