Bastian Jörg Bergmann: Catalogue data in Autumn Semester 2024 |
| Name | Dr. Bastian Jörg Bergmann |
| Address | RiskLab ETH Zürich, HG F 42.1 Rämistrasse 101 8092 Zürich SWITZERLAND |
| Telephone | +41 44 632 61 63 |
| bbergmann@ethz.ch | |
| Department | Management, Technology, and Economics |
| Relationship | Lecturer |
| Number | Title | ECTS | Hours | Lecturers | ||||||||||||||||||||||||||||||||
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| 365-1181-00L | Introduction to Quantum Computing: Current Challenges and Business Insights  Exclusively for MAS MTEC students (1st and 3rd semester). | 1 credit | 1V | P. Kammerlander, B. J. Bergmann | ||||||||||||||||||||||||||||||||
| Abstract | In recent years quantum computing has become one of the most talked-about technological promises yet it is still often misunderstood. This 2-day course will give you an introduction to the basic principles of quantum computing and related technologies with lectures from both academic experts and business leaders. | |||||||||||||||||||||||||||||||||||
| Learning objective | After taking this course, students will - have a basic, pragmatic, and practical understanding of quantum computing: how it works, what makes it different from classical computing, what kinds of problems it may be useful for, and what kinds of problems it won’t be useful for - be able to judge the real-world impact of quantum computing today and in the coming years, as well as the challenges and opportunities it poses with respect to data security, simulation of complex systems, optimization problems, and AI/ML, to name a few examples - be able to name and explain on a high level other quantum technologies (besides quantum computing) that may have a significant impact on the market, now or in the future - be able to explain examples of business models in the area of quantum technology - have had hands-on experience from working at challenges in developing business models in the quantum technology sector - have had the chance to network and facilitate contacts with companies and experts at local research institutions and players in the local quantum technologies network | |||||||||||||||||||||||||||||||||||
| Content | Quantum computing is a type of computing that uses quantum mechanics principles, such as superposition and entanglement, to process information. Unlike classical computers, which store information in bits (either 0 or 1), quantum computers use quantum bits, or qubits, which can exist in multiple states simultaneously. However, quantum computing is still in its early stages of development and faces significant challenges, such as maintaining the stability of qubits and minimizing errors due to environmental noise. On day 1 of the 2-day course there will be introductory lectures to quantum computing and related quantum technologies such as quantum communication, quantum sensing, and quantum simulation by experts from academia. You will get an overview of Quantum mechanics, quantum computing algorithms as well as quantum hardware. In addition, we will offer lab tours where state-of-the-art quantum computing equipment can be seen in action, presented by scientists doing cutting-edge research at ETH Zurich. Guest lectures from Swiss businesses in the field of quantum technologies will share their view on the current and future market and present their companies’ histories, strategies, and goals. Together we will discuss some of the current challenges facing quantum computing as well as potential future directions for research and development in this field. On day 2, further guest lectures will present challenges on which the students can work in teams, followed by a final round of presentations and feedback. The students will benefit from first-hand insights by experts in the field with diverse backgrounds (academic, startup, business, industrial). Grading (ungraded semester performance) is based on active participation on both days. | |||||||||||||||||||||||||||||||||||
Competencies |
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| 365-1190-00L | Climate Risk and Sustainability in Finance and Insurance Exclusively for MAS MTEC students (3rd semester). Please register by 02.09.2024 at the latest via myStudies. | 2 credits | 2V | B. Huber, B. J. Bergmann, D. N. Bresch, A. Goussebaïle | ||||||||||||||||||||||||||||||||
| Abstract | As extreme weather, driven in concert with a changing climate, will continue to evolve and become increasingly severe over time, it is generally rendering greater costs across industry sectors. This course introduces climate risk modelling and how to derive business decisions from it, how to identify and assess sustainability in the current regulatory environment. | |||||||||||||||||||||||||||||||||||
| Learning objective | The main objectives of the course are: - Get an idea of climate change causes, physical vs. transition risks, consequences and scenarios, economic trade-offs, and the barriers for mitigation policies. - Understand climate risk modelling and how to derive actionable results from it. - Understand the basics of sustainability risks and ESG, basics of sustainability and the role of banks and insurers. - Learn about the latest regulatory developments and the most relevant sustainability frameworks and initiatives. - Learn from experts from industry and agencies how they tackle the challenges towards a sustainable economy. - Get practice insights on a sustainable investment strategy. - Learn about regulation and types of greenwashing. - Learn about green fintech initiatives and startups from the Swiss ecosystem. The Course is offered as a block course, allowing for a workshop character. Students will work in groups on selected cases on each day and share their thoughts and findings with industry professionals. Participation on all course days is mandatory. Performance assessment is based on active contribution and presentation of group work and cases. | |||||||||||||||||||||||||||||||||||
| Content | Climate change is on par with political instability, violent conflicts, cybersecurity and volatile interest rates. However, there is one exception – these other factors will eventually reverse course – climate change will not. This MAS MTEC elective lecture aims to empower future business leaders to navigate the intersection of climate risk and sustainability. By engaging with industry experts, start-ups, and thought leaders, participants will gain practical insights and actionable strategies to create positive impact within their organizations and beyond. This course is structured as follows: - Day 1: Introduction to Climate Risk, climate change causes, physical vs. transition risks, consequences and scenarios. Treating uncertainty in modeling climate-related financial risk, fundamentals of Climate risk modelling and how to derive business decisions from it. - Day 2 & 3: basics of sustainability risks, the sustainability frameworks, and initiatives. Definition and origin of ESG, drivers of ESG and how to measure ESG, the role of banks, insurer and the real economy, regulation and reporting standards. Case study on understanding how companies identifies and priorities financial and non-financial risk; how effectively is the organization achieving its sustainability goal and how double materiality influence the strategic decision-making process. - Day 4: Corporate Innovation in the context of climate risk, insights on innovative solutions from green fintech and start-ups on how to leverage technology to promote sustainable finance. During the 4 days, participants will also learn and hear from the guest speakers about cultivating leadership skills to address climate-related challenges, ethical decision-making, and fostering a culture of resilience in order to promote organizational agility and adaptability. The course is not targeted to participants with a background and work experience in the finance, banking, or insurance sector only. This course will benefit from participants with diverse backgrounds and industry experience. | |||||||||||||||||||||||||||||||||||
| 441-3000-00L | Innovation Project | 3 credits | 2S | B. J. Bergmann, P. Cheridito, J. Teichmann | ||||||||||||||||||||||||||||||||
| Abstract | This final task challenges the CAS in Machine Learning in Finance and Insurance participants to transform an inspired idea into a tangible prototype. Drawing inspiration from the workshops of Block II and Block III, you will develop and implement a pioneering project that showcases your acquired expertise. | |||||||||||||||||||||||||||||||||||
| Learning objective | Only open to Participants of the CAS ETH in Machine Learning in Finance and Insurance | |||||||||||||||||||||||||||||||||||
| Content | Details on Moodle. | |||||||||||||||||||||||||||||||||||
| Competencies |
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