Who is this course for?
Innovation refers to how firms and organizations create and capture value, and how customers and end-users adapt new solutions and processes. Typically, innovation is slow, costly and cumbersome and as the availability of information increases, the basis for how and what firms and organizations innovate is increasingly based on their information and problem-solving capabilities. AI promises dramatic improvements in decision making, streamlining operations, and even allowing for an increased innovative ability. However, AI innovations tend to be stand alone solutions, rather than being integrated in a firm’s or the customer’s innovative activities and operations. The course fits you as an engineer or manager who will learn how to apply relevant models and frameworks to better understand, spot, and exploit the opportunities and challenges of innovation for and with AI.
What will you learn from this course?
The course introduces main aspects of innovation in relation to AI. The focus is on different types of innovation, how they are managed and differences and similarities across applications and industries. You will also be introduced to how ‘big data’ and AI affects business models and innovation ecosystems.
The course is based on blended learning, consisting of recorded lectures, lectures, seminars and workshops. Experiential learning is a foundation of the course in that you are to draw on your experiences for learning how AI influences innovation. The course includes one or two recommended campus visits.
What is the format for this course?
Instruction type: The course is delivered online and in English. There is one recommended but voluntary discussion session located at the Halmstad campus. The course consists of online lectures and seminars, pre-recorded videos and reading material.
Frequency: The course consists of bi-weekly online sessions and assignments, distributed over a total of 9 weeks.
Examination: The exams consists of three written handins and one recorded presentation. The course awards Pass or Fail.
Course responsible: