Artificial Intelligence for Managers
Why offer a course on Artificial Intelligence? After all, the concept is gaining more and more importance. Consulting companies try to push their ideas and related solutions. As an IT or business manager you need to develop at least a basic understand regarding what AI is (not only what the abbreviation stands for) and how it can help you to improve business processes or to realize new business models. Besides covering the basics in a traditional lecture and workshop setting we will introduce different AI use cases and guide you through the implementation for your own AI use case.
The best way of learning something new is to try and experience it yourself. Dive into AI!
-- Umberto Michelucci, Stefan Bischoff and Claus Horn
At a glance
Certificate of attendance "Artificial Intelligence for Managers" (1 ECTS)
1 day / 09:00 - 17:00
Language of instruction:
Objectives and content
This course is for people who would like to get a better understanding of the concepts behind Artificial Intelligence. During an intense period of four to six week you will dig deep into the topic and need to be willing to develop your own AI use case. We will help you to get started also to identify a suitable use case which can be implemented as a team. You will also experience how to collaborate in distributed teams. Some background in programming and understanding of basic mathematics is useful.
- Students know what Artificial Intelligence (AI) is
- Students learn how AI-based applications work and what components they consist of
- Students experience the development process of an AI application
- Students develop own AI applications and identify its practical value
- Students understand the role of data in the context of AI applications
- Students become aware of ethical challenges when it comes to using AI applications
- Students experience the importance of organizational factors within an AI project and understand the different roles that are important for its success
- Advanced training course with certificate
- Mandatory homework assignments
- Course language: English (based on participants the lectures can be held in German)
Exam and credits
To obtain the 2 ECTS credits students have to pass a comprehensive team project where students design, develop, describe and present an individual AI use case.
- Comprehensive practical project (60%)
Summary paper describing the project in detail including the individual contributions of each student
- Presentation (40%)
The course is strongly based on applied exercises. In addition to traditional lectures, where we introduce the basic concepts and components of Artificial Intelligence solutions, students will experience the implementation of their own AI use case. This includes project design, data collection, algorithm selection and implementation. This approach demystifies Artificial Intelligence.
CAS in Digital Life Sciences
This module is part of the CAS in Digital Life Sciences continuing education programme, but can also be attended independently of the CAS. Credit points earned for this module can be credited to the CAS course at a later date, provided the relevant general conditions are fulfilled.
More information here: CAS in Digital Life Sciences
Enquiries and contact
Umberto Michelucci studied Theoretical Physics in Italy, USA and Germany. He is author of two books on deep learning and has published several peer-reviewed papers in Machine Learning. He is actively collaborating with many universities in Europe (ETH, University of Basel, University of Torino, Politecnico di Torino between others) in many research projects (including EU funded ones in the program Horizon 2020) that deal with artificial intelligence in many fields as medicine, economics, insurance, mathematics, physics and astrophysics. He is also the founder of TOELT llc, a company that does international research in artificial intelligence in many fields (www.toelt.ai), and leads the AI Center of Excellence at Helsana Versicherung AG.
Stefan Bischoff is Head of Enterprise Architecture at Helsana Versicherung AG. He received his Ph.D. from the University of St. Gallen and holds a master’s degree in Information Systems from Murray State University and a Master of Science with Honors degree from the University of Regensburg. His research mainly focuses on use-, user-, and utility-centric aspects of business intelligence systems, executive information systems and enterprise architecture. He acts as an advisory board member of the TDWI Switzerland conference.
Dr. Claus Horn is a physicist (formerly working at CERN and Stanford University) with over ten years of experience in leading applied AI projects in various industries in Switzerland. He works as a lecturer and researcher at ZHAW where he focuses on the development of life science-specific methods and applications of artificial intelligence. He is the founder of the Reinforcement Learning Zurich community and leads the continued education at the Institute of Applied Simulation.
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