Technology and Entrepreneurship
A bootcamp course to learn to identify a problem, construct a team, build a real technology prototype, and validate the business, in 1 week.
General Information
Type: block course (4 days, 9am-6pm)
Language: English
Level: Master / PhD
Open to: ETH, HSG, EPFL, UZH, ...
ECTS: 3 credits
Catalog ID: 263-5058-00L
Abstract
This course provides theoretical and practical insights into technology entrepreneurship. It focusses on the process of building new ventures from the idea to successfully scaling its business operations. All tasks will lead students to give a complete pitch presentation in front of business experts and investors at the end of the seminar. The course structure will broadly follow the four dimensions of the St.Galler Startup NavigatorTM.
Learning Objectives
Students will develop internationally scalable and technology‑based ventures using the Startup Navigator and ScaleUp Navigator Framework. They will learn how to structure and communicate these ideas to business angel and venture capital investors.
Content
- Profiling (Problem‑Solution‑Fit): Here, students will learn to answer questions such as
- What is your motivation to start a business?
- What is the real customer problem?
- What solution can be identified?
- Who are the customers?
- What is the job they need done? etc.
- Prototyping (Product‑Market‑Fit): After this section, students will be able to answer questions such as
- What is the product or service that solves a customer need?
- What is the value proposition?
- What is the unique selling proposition?
- What is the go‑to market strategy?
- Who are the competitors? etc.
- Sourcing (Execution‑Fit): Here, students will learn to address questions such as
- What are important team roles?
- How to leverage network and partners?
- What are the requirements to execute the business?
- Are there any IP‑related challenges?
- How may we co‑create with others? etc.
- Scaling (Performance‑Fit): In this section, students will reflect their concept in terms of scalability. They will learn to answer questions such as
- How do we create purpose‑driven culture for growth?
- How do we scale‑up revenues?
- How do we optimize our startupʹs valuation in Series‑X funding?
- What kind of exit options are there?
As a result, students develop internationally scalable and technology‑driven businesses in teams. The special focus lies on the ability to successfully pitch these ventures to business angels or venture capital investors.
Main instructors
Melanie Gabriel (Co-Director & COO ETH AI Center,Co-founder of Yokoy & Follow the Gradient)
Melanie Gabriel is Co-Director & COO of the ETH AI Center. Previously, she was Co-Founder and CMO of Yokoy, a FinTech and AI company that was successfully acquired in early 2025. In her weekly podcast and newsletter Follow the Gradient, Melanie and her guests discuss how to scale a business from Europe while staying sane. Melanie lectures on entrepreneurship at ETH Zurich and the University of St. Gallen, serves on the boards of SICTIC and Moodtalk, and is active as an angel investor and advisor. She holds a Master’s degree in Business Management from the University of St. Gallen. Melanie was inducted into the Hall of Fame of Switzerland’s 100 Digital Shapers and received the HSG Founder of the Year Award in 2023.
Alexander Ilic (Executive Director, ETH AI Center)
Swiss-German deep tech entrepreneur, researcher, and investor. Alex was a professor at University of St.Gallen (HSG), an e-Lab fellow at MIT, has two exits under his belt as entrepreneur (Dacuda, acquired by Magic Leap 2017) and investor (VAY acquired by Nautilus 2021), was named twice "Entrepreneur of the Year" (2011 by HSG, 2012 by EY) and won the Swiss Economic Award. He is passionate about helping talents to find their path to entrepreneurship as chairman of Talent Kick and board member of the student-run S2S Ventures.
Arnout Devos (Academic Program Mangager, ETH AI Center)
Dr. Arnout Devos is the Academic Program Manager at ETH AI Center and a Scientific Coordinator at ELLIS. He holds a PhD from the Swiss Federal Institute of Technology Lausanne (EPFL), where he worked on few-shot machine learning research and innovation, including time at Amazon and Spotify. He has received several awards for his work, including a Marie Curie doctoral fellowship and an EPFL Computer Science Teaching Assistant award.
TA Contact
Vera Balmer