|Dr. Philipp Kammerlander
ETH Zürich, HIT G 31.2
|+41 44 633 03 28
|New Technologies in Banking and Finance
|B. J. Bergmann, P. Cheridito, H. Gersbach, P. Kammerlander, P. Mangold, K. Paterson, J. Teichmann, R. Wattenhofer
|Technological advances, digitization and the ability to store and process vast amounts of data has changed the landscape of financial services in recent years. This course will unpack these innovations and technologies underlying these transformations and will reflect on the impacts on the financial markets.
|After taking this course, students will be able to
- Understand recent technological developments in financial services and how they drive transformation
- Understand the challenges of this digital transformation when managing financial and non-financial risks
- Reflect on the impacts this transformation has on workflows, agile working, project and change management
|The financial manager of the future is commanding a wide set of skills ranging from a profound understanding of technological advances and a sensible understanding of the impact on workflows and business models. Students with an interest in finance and banking are invited to take the course without explicit theoretical knowledge in financial economics. As the course will cover topics like machine learning, cyber security, distributed computing, and more, an understanding of these technologies is welcomed, however not mandatory. The course will also go beyond technological advances and will also cover management-related contents. The course is divided in sections, each covering different areas and technologies. Students are asked to solve online quizzes and small cases for each section. Invited guest speakers will contribute to the sessions. In addition, separate networking sessions will provide entry opportunities into finance and banking.
More information on the speakers and specific session can be found here: https://riskcenter.ethz.ch/education/lectures.html and on the moodle page.
|There will lecture slides to each section shared in advanced to each session.
|Selected readings and books are presented in each session.
|Prerequisites / Notice
|The course is opened to students from all backgrounds. Some experience with quantitative disciplines such as probability and statistics, however, is useful but not mandatory.
|Quantum Information Processing I: Concepts
This theory part QIP I together with the experimental part 402-0448-02L QIP II (both offered in the Spring Semester) combine to the core course in experimental physics "Quantum Information Processing" (totally 10 ECTS credits). This applies to the Master's degree programme in Physics.
|2V + 1U
|The course covers the key concepts of quantum information processing, including quantum algorithms which give the quantum computer the power to compute problems outside the reach of any classical supercomputer.
Key concepts such as quantum error correction are discussed in detail. They provide fundamental insights into the nature of quantum states and measurements.
|By the end of the course students are able to explain the basic mathematical formalism of quantum mechanics and apply them to quantum information processing problems. They are able to adapt and apply these concepts and methods to analyse and discuss quantum algorithms and other quantum information-processing protocols.
|The topics covered in the course will include quantum circuits, gate decomposition and universal sets of gates, efficiency of quantum circuits, quantum algorithms (Shor, Grover, Deutsch-Josza,..), quantum error correction, fault-tolerant designs, and quantum simulation.
|Will be provided.
|Quantum Computation and Quantum Information
Michael Nielsen and Isaac Chuang
Cambridge University Press
|Prerequisites / Notice
|A good understanding of finite dimensional linear algebra is recommended.