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Technology Investing
Last Updated: 2026-06-03 00:07:38
Abstract
In this course dedicated to digital innovations, we will bust the most stubborn myths around AI software patents such as “Software/AI isn’t patentable”, “AI patents are useless because you can’t figure out if they are infringed”, and many others. We will look at how AI and software start-ups can use patents to create a strong IP position in a scalable way.
Objective
After attending this course, students will be able to: - Understand the basics of patenting in the digital space relevant for a global market - Evaluate patenting opportunities with a more differentiated view on the topic - Effectively use patents as a cost-effective part of a technology startup’s business plan - Conduct patent searches, freedom-to-operate analysis and infringement analyses - Write their first software/AI-related invention disclosure suitable for patenting
Content
The course is focused on patenting digital innovations. It is designed for students with entrepreneurial interests that like to get a hands-on perspective on the topic of intellectual property strategies and patents. The detailed program is listed here, under its respective semester: https://ai.ethz.ch/education/courses/patenting.html The course includes presentations and practical group exercises to apply the acquired knowledge in practice. Entrepreneurs and leading IP experts are joining the course as guest speakers for discussion of real-life examples. Topics that will be covered include: - Best practices that any AI/software startups should know about IP and patents - How investors evaluate a strong IP situation of a start-up - How to efficiently monitor competitor patent activity and obtain “FTO” - How to create an effective patent filing strategy that grows with the business - How to efficiently create AI patents while not getting distracted from the founder’s core business The course also contains a group work of a “FTO battle” where two teams compete in a freedom-to-operate analysis and individual work to write their first invention disclosure related to an AI or software topic.
General Information
- Language
- English
- Levels
- DR , MSC
- Frequency
- Yearly recurring
Examination
- Type
- graded semester performance
Registration & Places
- Max Places
- 50
Course Components
| Type | Title | Time & Place | Hours |
|---|---|---|---|
| seminar |
Technology Investing
Block course:
Dates: tba,
Rooms: OAT S 17 / HSG
|
No time listed | 42 h semesterly |
Offered In
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Elective Courses (Students can individually choose from the entire Master course offerings from ETH Zurich, EPF Lausanne, the University of Zurich and - but only with the consent of the Director of Studies - from all other Swiss universities.)
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Doctorate Computer Science (More Information at: )