Technical University Berlin

In this course, the fundamentals of Python are covered, with a special focus on the skills necessary for in-depth data analyses and data visualization. These two skills are fundamental in a wide range of disciplines, including but not limited to STEM (Sciences, Technology, Engineering and Mathematics) and Humanities fields of study. This course will cover the following: data types and compound data structures, conditional statements and loops, Python functions, importing, exporting and analyzing different types of data using pandas, visualizing data using Matplotlib and Seaborn, and developing interactive plots with Plotly. At the end of the two weeks course, students will work and present a final personal data analytics and visualization project.

Motion planning is a fundamental building block for autonomous systems, with applications in robotics, industrial automation, and autonomous driving. After completion of the course, students will have a detailed understanding of: Formalization of geometric, kinodynamic, and optimal motion planning; Sampling-based approaches: Rapidly-exploring random trees (RRT), probabilistic roadmaps (PRM), and variants; Search-based approaches: State-lattice based A* and variants; Optimization-based approaches: Differential Flatness and Sequential convex programming (SCP); The theoretical properties relevant to these algorithms (completeness, optimality, and complexity). Students will be able to: Decide (theoretically and empirically) which algorithm(s) to use for a given problem; Implement (basic versions) of the algorithms themselves; • Use current academic and industrial tools such as the Open Motion Planning Library (OMPL).

It provides a unified perspective on motion planning and includes topics from different research and industry communities. The goal is not only to learn the foundations and theory of currently used approaches, but also to be able to pick and compare the different methods for specific motion planning needs. An important emphasis is the consideration of both geometric and kinodynamic motion planning for the major algorithm types.

In this project-based workshop course, the background and effects of topics related to environmental justice such as environmental racism, gender issues, disadvantage due to physical impairments and social differences in the city are examined. The discussion-based debate during the event is to be expanded by a media project in which a selected topic is creatively addressed.

You will not only learn about content expertise, but also different methods and the use of different media. This includes:

• Expertise in the meaning of environmental justice and the background and consequences of the prevailing discrepancies
• Expertise in the ecological foundations and ecosystem services in the city
• Different perspectives from different disciplines by working on topic-specific literature
• An ability to reflect on urban infrastructure through a combination of ecological and social expertise regarding environmental justice
• Discussion skills as well as presentation and moderation skills in interdisciplinary exchanges with other participants from different study programs
• Creative process of developing and implementing a media project from finding a topic to presenting the final result
• Scientific and fact-based development of a creative media project and formulation of socio-political demands and solution approaches in a project report
• Be able to apply learned specialist knowledge and critical considerations regarding environmental justice not only to urban areas, but also to transfer them to everyday living environments

In this course we will examine how existing network layers are protected, how to verify the security of a protocol, and how to improve the dependability. We will specifically learn about the common vulnerabilities in the current Internet, such as botnets, viruses, denial-of-service attacks, etc., and design principles to overcome these issues in the future. We will also learn about the security benefits and challenges of network virtualization technologies, about air-gapping, as well as automated network testing methods and fuzzing.

In contemporary building design, sustainability has emerged as a fundamental element. With the growing urgency of climate change and limited resources, the imperative to create buildings that prioritize minimal environmental impact and maximize human comfort has also intensified. Sustainable building can make a crucial contribution in this regard. But what defines a sustainable building and how can a building be designed in a sustainable way? The course provides both theoretical and practical learning materials to address this question. Participants will acquire general knowledge and skills in the fields of sustainable building and building performance simulations. They will be able to gain a deeper understanding of the interactions between various factors when designing or conducting evidence-based analyses of a building's sustainability. Key topics will include: principles of sustainable buildings, future trends, chances, and aims of sustainability by buildings, functional and aesthetical quality of buildings, systems for environment friendly energy supply, thermal comfort and indoor air quality, fundamentals of building performance simulations, and simulative analysis of buildings. The first two weeks cover the theoretical segment and the subsequent two weeks consist of collaborative work on small-scale projects with supervision from lecturers. Furthermore, there will be three excursions in Berlin, where attendees will experience real-life examples of sustainable buildings and plants.

In this course we will explore the relationships between people, nature and space as well as the production and use of open space (e.g., changing interpretation and usage patterns in relation to the city and open space or the change in living, work and leisure) against the background of social development. Particular emphasis is placed on gender as an analytical category for spatial concepts and spatial actions as well the consideration of the interaction between theory and practice. That also includes current trends in spatial development.
 

The goal of this course is to enable students to apply the main instruments of impact assessment and mitigation in practical planning situations based on fundamental knowledge provided in the bachelor's degree program; to gain expertise about the contents and planning processes of instruments such as the German Impact Mitigation Regulation, Environmental Impact Assessment (EIA), Strategic Environmental Assessment (SEA), EU Habitat Regulations Assessment (HRA) and Protected Species Assessment, as well as U.S.-American Wetland Mitigation and Endangered Species Mitigation; to recognize environmental and social needs and plan accordingly, and to identify interfaces with natural and social sciences; to apply planning instruments both in domestic as well international arenas; to judge the different instruments in their effectiveness and know how to generate appropriate research when needed and to identify and formulate research approaches for the further development of planning instruments, and; to identify and analyze aspects of gender mainstreaming in planning processes.

The students learn the implementation and practical application of new (under development) web technologies, particularly in the areas of online media (e.g. web TV, streaming, content protection, social media), telecommunications (e.g. web RTC) , as well as Internet of Things.

In the course, students practice descriptive evaluations as well as inferential statistical analyses with R: In addition to the most common univariate methods, non-parametric and selected multivariate methods are also taken into account. Further focuses are on the diverse options for creating diagrams and data management. After completing the course, participants can carry out standard exploratory and inferential statistical procedures with R, create flexible diagrams and have gained an overview of the diverse possible uses of the additional packages for special problems.

This course covers the following topics: sets and mappings, complete induction; number representations, real numbers, complex numbers; number sequences, convergence, infinite series, power series, limits and continuity of functions; elementary rational and transcendental functions; differentiation, extreme values, mean value theorem and consequences; higher derivatives, Taylor polynomial and series; applications of differentiation; definite and indefinite integral, integration of rational and complex functions, improper integrals, Fourier series; matrices, linear systems of equations, Gauss algorithm; vectors and vector spaces; linear mappings; dimension and linear independence; matrix algebra; vector geometry; determinants, eigenvalues; linear differential equations.