Young Researcher Entrepreneurship Bootcamp

• Develop an entrepreneurial mindset that cuts across academic and business cultures.
• Understand the fundamentals of creating a novel startup (how to develop a research project or idea to a business opportunity) while working on hypothetical case studies in groups or on their own preconceived startup idea.
• Learn and discuss some of the basics of MLOps as a prerequisite for building an AI startup (Bridging Machine Learning, DevOps and Data Engineering). Students will be introduced to and discuss a set of practices that aims to deploy and maintain machine learning models in production reliably and efficiently.
• Learn and explain how having an entrepreneurial mindset can benefit how you approach your current research and future career.
• Learn key concepts for early-stage enterprise/startup building, including ideation, business modelling, and startup building, prototyping, testing, building networks, sales, marketing and raising finance.
• Significantly improve their business knowledge and the professional skills needed to start a business; and in adition develop an entrepreneurial mind-set as well as transferable skills such as collaborative working, innovative thinking, and presentation skills and communicate complex commercialization projects.
• Exaplin intellectual property (IP) based startups, including software IP, Open Source etc.
• Understand, interact, network and navigate within the innovation ecosystem (investors, venture builders, suppliers and other stakeholders and other startups) through peer-learning and role-play exercises. This includes working with tech-trans officers, business developers and other IPR professionals and university administration.

The course is divided into three steps:

1. Develop your entrepreneurial knowledge, skills and mindset. This one-day workshop is for doctoral students and early career researchers who want to learn more about the benefits of thinking entrepreneurially. You will learn the fundamentals of creating a novel startup while working on hypothetical case studies in groups. You will also learn how having an entrepreneurial mindset can benefit how you approach your current research and future career.
2. Learn how to turn an idea into an enterprise. This one-day workshop delves deeper into business language and entrepreneurial thinking. You will learn about key concepts for early-stage enterprise creation, including ideation, prototyping, testing, building networks, sales, marketing, and raising finance. This workshop will also help you develop an entrepreneurial mind-set as well as transferable skills such as collaborative working, innovative thinking, and presentation skills.
3. Build your enterprise – management and negotiation skills. This one-day workshop is for doctoral students and early career researchers who are considering starting a business but are unsure how to get started. This workshop will help you significantly improve your business knowledge and the professional skills needed to start a business. Sessions one and two focus on company administration and financial planning for intellectual property (IP)-rich startups. Sessions three and four explore how to have conversations with investors, suppliers and other stakeholders through role-play exercises.

The course will leverage the newest research from DTU on how to teach entrepreneurship to young researchers. The didactic approach will be an engaging learning-by-doing format that reflects the applied nature of entrepreneurship:
• Lectures given by experts
• Experiential and game-based learning
• Group works, Peer-to-peer learning
• Masterclasses by business mentors and successful entrepreneurs
• Startup pitch for investor panel and university startup eco-system

Minimum: 30, Maximum: 60.

Please be aware that this course has a minimum requirement for the number of participants needed, in order for it to be held. If these requirements are not met, then the course will not be held. Furthermore, there is a limited number of seats available. If there are too many applicants, a pool will be created for the remainder of the qualified applicants, and they will be selected at random. You will be informed 8 days before the start of the course, whether you have been allocated a spot.