English

This course offers interpretations of current (and past) development processes and patterns, specifically in relation to Asia, Africa, and Latin America. Taking into account a range of overlapping dimensions (from social, economic, cultural, and political to institutional), the course explores the multifaceted and layered nature of development and its variegated impacts on the ground. Thus, the course adopts a geographical lens to unpack various economic and societal shifts taking place in developing and emerging countries. Questions addressed in the course include what are the main dimensions of development in the so-called global South? What are the primary drivers of change? What opportunities and barriers exist? What are the main strategies to induce development? What coping strategies are employed? Central to this course is the critical reflection on, and recognition of the multiple meanings of, development and its manifold local expressions within an interconnected world. Entry Requirements: Introduction to Human Geography.

This course examines international nuclear non-proliferation regimes and geopolitical situations as an important part in international peace and security. Via case studies, the course explores the history of nuclear weapon development and the establishment of nuclear non-proliferation regimes as well as nuclear disarmament agreements between the United States and Russia (formerly the Soviet Union) and the UN’s efforts to ban nuclear weapons. 

The course further addresses the history of nuclear weapon development, use, and related, resultant negotiations, treaties, and subsequent political impact upon and by various governing bodies throughout the world. The course situates and reviews cases in the geopolitical context: nuclear development and possession in India, Pakistan, and Israel; the Cuban Missile Crisis; and Iranian nuclear development.  

In addition, the possibility of further nuclear proliferation by Saudi Arabia, Egypt, Japan and Taiwan is discussed in relation to geopolitical interests, and North Korea's nuclear tests and South Korea’s nuclear option are debated in the context of North Korea’s nuclear threat and geopolitical strategy. 

This course introduces exciting new developments in advanced mathematics. The barriers between fields are being broken, many new unexpected applications are continually found, and out of this cross-fertilization, new kinds of mathematics are born. Topics are subject to change but may include various new advances of pure mathematics and logic, computational science and numerical analysis, fluid mechanics and geophysics, wavelets and signal processing, cryptology, quantum computation, mathematical biology (including bioinformatics, proteomics and neuroscience), intelligence science, financial mathematics and mathematical economics, and probability theory with various applications.  

This course uses logic and discrete mathematics to model the science of computing. It provides a grounding in the theories of logic, sets, relations, functions, automata, formal languages, and computability, providing concepts that underpin virtually all the practical tools contributed by the discipline, for automated storage, retrieval, manipulation and communication of data.

The course focuses on Berlin as a case study of urban governance for sustainability. It compares local policy challenges in national and international contexts, developing a more nuanced view on the top down and bottom up strategies of building sustainable cities. The course combines a comparative policy analysis approach with concepts of international relations studies. The objective is to unravel the concept of sustainability and study its translation into politics and policies in multi-level governance structures.

This course examines video games, including the great games, the history, the techniques, and the future of this developing medium and industry. To understand the full picture of video games it is impossible to separate the commercial elements from the artistic and the technological from the social and mental. A wide range of disciplines need to be explored and the connections between them as well as looking at the game industry itself and how it is transforming. Each week will combine the issues that surround games and an overview of the best and most complex games from multi million dollar blockbusters to the new ‘art games’ and independent games that re-invent the concept of a game. 

This course examines histories and continuing legacies of colonialism and racialization and their interaction with legal systems and criminalization. Topics covered could include dispossession and theft of sovereignty in settler colonial nations, structural racism and its relation to law, racialized policing and profiling, mass incarceration policies and movements by Indigenous peoples and people of color to achieve social and legal justice.

This course explores generative artificial intelligence (GAI) and its applications. Students gain a comprehensive understanding of generative models, including deep learning architecture, and probabilistic models. The course covers theoretical foundations and practical implementations of generative AI algorithms. Students also engage in hands-on projects to apply generative AI methods. Topics include introduction to generative AI (overview of generative modeling, brief history of GAI, applications of GAI), probability theory and information theory, parameters estimation, latent variable models, variational inference (introduction), variational autoencoders (VAEs) - autoencoders - variational autoencoders (VAE) - conditional VAE - VQ-VAE v1, v2, generative adversarial networks (GANs) - introduction to GANs - GAN training, issues and solution - generative model evaluation, GAN variants: DCGAN, CGAN, WGAN, ProGAN and Style-GAN, GAN applications: image manipulation and editing, diffusion-based generative models - DDPM - DDIM, diffusion-based generative models - classifier guidance DMs - classifier-free guidance DMs - cascaded DMs - latent DMs, autoregressive generative models - MADE, PixelNN, language generative models - Transformer - GPT family, multi-modal generative models - DALL-E (DALL-E 2 and DALL-E 3) - stable diffusion, flow-based generative models - RealNVP, GLOW.

Prerequisite: Solid understanding of machine learning and deep learning principles - Proficiency in programming - Familiarity with deep learning frameworks (e.g., TensorFlow, PyTorch)

This course introduces the recently emerging fields of decision-making neuroscience and neuroeconomics. Topics include the core elements of the brain mechanism related to decision-making, such as dopamine function, approach and avoidance circuits, value calculation, and the dilemma of stability versus flexibility. In addition, this course covers the neuroscientific model of decision-making and how to understand and apply it to various choices in everyday life. 

This course is intended for advanced-level undergraduate students who have completed an introductory psychology course and are familiar with basic terms in neuroscience and elementary statistics. 

This course examines computation and data handling, integrating sophisticated use of existing productivity software, e.g. spreadsheets, with the development of custom software using the general-purpose Python language. Students will see examples from many domains, and be able to write code to automate the common processes of data science, such as data ingestion, format conversion, cleaning, summarization, creation and application of a predictive model.