Alexander Ilic: Katalogdaten im Herbstsemester 2024 |
| Name | Herr PD Dr. Alexander Ilic |
| Adresse | ETH AI Center ETH Zürich, OAT X 16 Andreasstrasse 5 8092 Zürich SWITZERLAND |
| alexander.ilic@ai.ethz.ch | |
| URL | https://ai.ethz.ch/people/alexander-ilic |
| Departement | Informatik |
| Beziehung | Dozent |
| Nummer | Titel | ECTS | Umfang | Dozierende | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| 263-3300-00L | Data Science Lab   Only for Data Science MSc, Programme Regulations 2017. | 14 KP | 9P | A. Ilic, V. Boeva, R. Cotterell, J. Vogt, F. Yang | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Kurzbeschreibung | In this class, we bring together data science applications provided by ETH researchers outside computer science and teams of computer science master's students. Two to three students will form a team working on data science/machine learning-related research topics provided by scientists in a diverse range of domains such as astronomy, biology, social sciences etc. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lernziel | The goal of this class if for students to gain experience of dealing with data science and machine learning applications "in the wild". Students are expected to go through the full process starting from data cleaning, modeling, execution, debugging, error analysis, and quality/performance refinement. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Voraussetzungen / Besonderes | Prerequisites: At least 8 KP must have been obtained under Data Analysis and at least 8 KP must have been obtained under Data Management and Processing. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 263-3300-10L | Data Science Lab Only for Data Science MSc, Programme Regulations 2023. | 10 KP | A. Ilic, V. Boeva, R. Cotterell, J. Vogt, F. Yang | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Kurzbeschreibung | In this class, we bring together data science applications provided by ETH researchers outside computer science and teams of computer science master's students. Two to three students will form a team working on data science/machine learning-related research topics provided by scientists in a diverse range of domains such as astronomy, biology, social sciences etc. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lernziel | The goal of this class if for students to gain experience of dealing with data science and machine learning applications "in the wild". Students are expected to go through the full process starting from data cleaning, modeling, execution, debugging, error analysis, and quality/performance refinement. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Voraussetzungen / Besonderes | Prerequisites: At least 8 KP must have been obtained under Data Analysis and at least 8 KP must have been obtained under Data Management and Processing. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 263-5053-00L | Technology Investing | 2 KP | 3S | A. Ilic, C. Jurytko | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Kurzbeschreibung | Venture Capital is important to fund big transformational ideas and is often misunderstood by tech or research entrepreneurs. This lecture immerses participants in the role of a Venture Capitalist (VC) to learn from experienced entrepreneurs and investors. In small teams, you work on a case of a real start-up and defend the case in a simulated investment committee consisting of experienced VCs. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lernziel | After attending this course, students will be able to: - Explain the differences between VC and founder thinking - Evaluate if a start-up is suited for venture capital (“VC readiness”) - Evaluate founder friendliness of term sheets - Determine funding needs & strategy for a start-up from research to first round - Write and evaluate an investment memo | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Inhalt | The course is practically oriented and features guest speakers from leading venture capital firms and start-ups. The course embraces a unique perspective combining technology and investor thinking. The seminar is structured around five days with the following themes. The detailed program is listed here: https://bit.ly/techinvesting24 The macro picture. Why does venture capital exist? What are major tech break-through areas and their disruptive potential? We also review the differences in the US and European perspective as well as developments towards more impact and diversity conscious funds. A peek into the mind of a VC. How to build a successful VC? Learn what key factors & processes required to build a successful venture capital company. This includes strategic decisions for investment thesis, structure of a fund, portfolio economics, valuation & ownership targets, cap table. In addition, we introduce the fundamentals of the investment process (including due diligence, term sheets, and deal memo) as well as portfolio management. The founder’s perspective. Why should you raise venture capital and how? Learn to evaluate the founder friendliness of terms, company approach, strategic decisions, negotiation and valuation. Fundraising types. Learn about different types of funding and their implications. This includes an overview of the Swiss ecosystem and a discussion of the different types (grants, equity, loans, SAFE, crowd, …). We also include a practical session on crypto technology for modern fund-raising using launchpads and tokenized shares. Tying it all together. The last day is focused on simulating an investment committee meeting where the groups present their deal memos and discuss with the audience. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Kompetenzen |
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| 263-5054-00L | Patenting Digital Innovations | 1 KP | 2S | A. Ilic, B. Best | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Kurzbeschreibung | In this seminar 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. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lernziel | 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 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Inhalt | 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 seminar includes presentations and practical group exercises to apply the acquired knowledge in practice. Entrepreneurs and leading IP experts are joining the seminar 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. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 263-5055-00L | Talent Kick: From Student to Entrepreneur | 3 KP | 2G | V. Gropengiesser, A. Ilic | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Kurzbeschreibung | The transfer of the latest research results into scalable start-ups creates the prerequisite forsuccessful innovations. An entrepreneurial spirit and mindset enables young leaders to navigate complex environments and bring their research into practice. Studies are the best time to develop an entrepreneurial mindset and explore the entrepreneurial career path. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lernziel | This seminar helps aspiring student/research entrepreneurs to gain hands-on entrepreneurial experience on the path from research into practice. The examples and cases will be primarily from software, AI, and other deep-tech ventures. The seminar was created with the support of ETH AI Center and University of St. Gallen and received competitive funding from the ETH Board, Fondation Botnar, Gebert Rüf Foundation, as well as support from the ETH Foundation. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Inhalt | After attending this course, students will be able to: ● Explain the importance and tools to form successful interdisciplinary teams ● Structure customer calls and sales pitchdecks ● Build their first prototypes and MVPs ● Find the right markets and customers to bring your research into practice ● Deal with complexity in bringing innovative / novel products into market ● Develop customer-centric business strategy ● Convince first supporters incl. Entrepreneurial mentors, first investors etc. Content & Timeplan The course is practically oriented and features guest speakers from leading start-ups. The course embraces a unique perspective combining technology and investor thinking. The seminar is structured around six days with the following themes. 25.09.2024 - In-person - 11:00 to 18:00 What makes a good entrepreneur (5 hrs / around 1 hr keynotes and 4 hrs guided group work) Learn how to develop an entrepreneurial mindset, starting with your skillset, purpose, vision, and passion. 16.10.2024 - In-person - 11:00 to 18:00 What makes a good team (5 hrs / around 1 hr keynotes and 4 hrs guided group work) Learn how to find and work successfully in a diverse team with similar values and different skill sets and personality types, creating a basis for communication and mutual respect. 23.10.2024 - Online - 17:00 to 19:00 The Idea does not matter (1.5 hrs keynotes & Q&A) Learn how successful startups found the best opportunities based on customer contact and their skillset and research. 06.11.2024 - In-person - 11:00 to 18:00 Problem Deep-Dive (5 hrs / around 1 hr keynotes and 4 hrs guided group work) Learn how to find problems that matter with a customer-centric approach. 11.12.2024 - In-person - 11:00 to 18:00 Validation (5 hrs / around 1 hr keynotes and 4 hrs guided group work) Learn how to continuously test your assumptions and measure your success with objective indicators that matter. 18.12.2024 - Online - 17:00 to 19:00 Sales Psychology (1.5 hrs keynotes & guided group work) Better understand your own limitations and motivations in sales and how to start and lead a sales conversation for different types of stakeholders and prospects. 20.01.2025 - Online - 17:00 to 19:00 Market Opportunity Navigator part 1 (1.5 hrs keynotes & Q&A) Learn how to find the right market to bring your research into practice and build a successful company 29.01.2025 - In-person - 11:00 to 18:00 Convincing supporters (5 hrs / around 1 hr keynotes and 4 hrs guided group work) Learn how to convince diverse supporters to join your journey with a diverse team and a convincing strategy. 05.02.2025 - Online - 17:00 to 19:00 Market Opportunity Navigator part 2 (1.5 hrs keynotes & Q&A) Learn how to find the right market to bring your research into practice and build a successful company 12.02.2025 - Online - 16:00 to 19:00 System thinking and Culture (3 hrs / around 1 hr keynotes and 2 hrs guided group work) Learn what’s next and how to move forward with a great idea and a strong team. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Voraussetzungen / Besonderes | The course is practically oriented and features guest speakers from leading start-ups. The course embraces a unique perspective combining technology and investor thinking. The seminar is structured around ten days. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Kompetenzen |
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| 263-5058-00L | Technology and Entrepreneurship | 3 KP | 6S | A. Ilic | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Kurzbeschreibung | 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. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lernziel | 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. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Inhalt | 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. The detailed program is listed here: https://bit.ly/techpreneur24 - Profiling (Problem‑Solution‑Fit): Here, students will learn to answer questions such as (1) what is your motivation to start a business? (2) What is the real customer problem? (2) What solution can be identified? (3) Who are the customers? (4) What is the job they need done? etc. - Prototyping (Product‑Market‑Fit): After this section, students will be able to answer questions such as (1) What is the product or service that solves a customer need? (2) What is the value proposition? (3) What is the unique selling proposition? (4) What is the go‑to market strategy? (5) Who are the competitors? etc. - Sourcing (Execution‑Fit): Here, students will learn to address questions such as (1) What are important team roles? (2) How to leverage network and partners? (3) What are the requirements to execute the business? (4) Are there any IP‑related challenges? (5) 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 (1) How do we create purpose‑driven culture for growth? (2) How do we scale‑up revenues? (3) How do we optimize our startupʹs valuation in Series‑X funding? (4) 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. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literatur | - Grichnik, D., Hess, M., Probst, D., Antretter, T., & Pukall, B. (2020). Startup Navigator‑Guiding Your Entrepreneurial Journey. Red Globe Press, London. - Course slides and case‑based literature provided by the instructor. - Additional material pointed out by the instructor prior to and during the course. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Kompetenzen |
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