Technical University Berlin

The course is for students who want to improve their language skills in a practical context and get to know Berlin better. They will discover very different sides of the city: discussing current topics, exploring the Berlin world of media, looking at the city in film and music and dealing with city history and Berlin notabilities. An important aspect will be the real "discovery": Students explore places and neighborhoods during excursions and get into a conversation with Berliners. In addition, students learn to carefully extract and reproduce information from complex reading and listening texts, videos, and conversations. They also train their skills to discuss, present or write on current topics.
 

Students further expand their listening, reading, speaking and writing skills with authentic texts and communication situations in the fields of everyday life, popular science, culture and society, and literature.

In this course, students learn about a number of key topics in the philosophy of mathematics. It ensure students are familiar with the main views such as Platonism, nominalism, logicism, formalism, intuitionism, and structuralism, as well as the main criticisms of each. Students learn about the philosophical significance of Russell’s paradox and Gödel’s incompleteness theorems. From here, they consider topics in the philosophy of mathematical practice, such as the nature of mathematical proofs, the use of diagrams in mathematical reasoning, explanation and understanding in mathematics, mathematical knowledge, and the ethics of mathematics.  

Engineering Innovation introduces students to the concepts of innovative thinking and innovation practices. Using lectures, case studies, team exercises and guest speakers, the course teaches life skills in innovative thought and action that students can use in careers ranging from starting companies to executing research and development projects in large companies. Students examine the innovator’s mindset and explore the culture of innovation. In a real- work, hands-on way, students learn how to be innovative and understand why innovation is integral to commercial success in the 21st Century’s digital revolution. Innovation strategies and tactics are evaluated from the perspective of ideation; that is, transforming innovative problem-solving ideas into viable solutions that are produced, sold, consumed, and or implemented in society. Students develop an understanding of the importance of innovation – and how innovation is applied. A best practices approach is used to demonstrate how innovators conceive and implement impactful solutions for a variety of problems. Students learn how technology can serve as both a pathway and a roadblock in organizations committed to operating with an innovator’s mandate. Students are taught practical and applicable skills that can be applied in enterprises ranging from startup ventures to Fortune 100 companies.

The technological and physical basics of Brain-Computer Interfacing will be elaborated. It covers the path from the (electrical) activity of single neurons and networks via the volume conduction of the human head. At the end of the class, students will know the essential physical background of Brain-Computer Interfacing (BCI). They will understand the pathway from the activity of single neurons to the signal of the electroencephalogram (EEG) They will be capable of programming simulations of the electrical properties of the human head as well as simple neural and neural network models.

The lecture covers elementary concepts in machine learning and their application on real data with a special focus on methods that are simple to implement. The course alternates lectures and practice sessions. In the practice sessions, students implement and apply machine learning algorithms on real data in Python. Topics include: supervised learning (linear regression techniques, linear classification, kernel based regression), unsupervised learning (principal component analysis, clustering), and model selection.

The course contains the learning materials, practices and case studies to develop the knowledge and skills of the students in the field of data science and its application in the real business/work world. The students learn how to apply analytical techniques and scientific principles to extract valuable information from business data for decision-making, strategic planning. This course covers practical contents of statistics, machine learning, information visualization, and data analysis techniques through python programming language and other tools.

The course provides an overview over the history of racism from antiquity to the postwar era. It addresses the relationship with different historical developments like colonialism, slavery, race science, eugenics, segregation and genocide. The course discusses the exemplary developments in different European and non-European societies. While the perspective of the victims of racist discrimination is addressed frequently, the course also focuses on the logic of such discrimination. For this, various related issues are raised, like anti-black racism, antisemitism, hatred against Sinti and Roma etc.

This course includes knowledge of common methods in asymmetric encryption, as well as possible attacks in faulty implementations of these methods: RSA, El-Gamal, Diffie-Hellman-Key-Exchange, elliptic curves, and selected methods of Post-Quantum-Cryptography. Students who completed this course possess profound knowledge of cryptographic methods. They are able to correctly and securely use cryptographic protocols. They are proficient in verifying the security of One-Way-Functions and (Pseudo-)Random-Number-Generators. Furthermore, they are able to recognize and avoid typical mistakes in asymmetric encryption.

The course introduces engineering students to the concepts and practices of technological entrepreneurial thinking and entrepreneurship. Using lectures, case studies, business plans, and student presentations, the course teaches life skills in entrepreneurial thought and action that students can utilize in starting technology companies or executing R&D projects in large companies. Major course modules include introduction to entrepreneurship, idea generation and feasibility analysis, and business planning and execution.