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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.

-- Umberto Michelucci and Stefan Bischoff

Auf einen Blick

Abschluss: AIM (2 ECTS)

Start: 07.02.2020

Dauer: 2.5 Days

Kosten: CHF 990.00

Bemerkung zu den Kosten: 

  • Standard price: CHF 990.00  (inkl. Kursmaterial)
  • Students (ID required): CHF 330.00 (incl. lecture material)

Durchführungsort: 

ZHAW Life Sciences und Facility Management, Zürich, Campus Zentrum, Lagerstrasse 41 (PDF 729KB)

Unterrichtssprache: Deutsch, Englisch
English

Duration & Dates: 

Overall 2.5 days

Dates
07.02.2020 09:00 - 16:00
Lagerstrasse 41, Zurich, ZL O3.17

28.02.2020 09:00 - 16:00 
Lagerstrasse 41, Zurich, ZL O3.17

06.03.2020 14:00 - 20:00 (incl. networking Apéro)
Lagerstrasse 41, Zurich, ZL O3.17

Ziele und Inhalt

Zielpublikum

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.

Ziele

  • 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

Inhalt

Format

  • Advanced training course with certificate. 2 ECTS credits.
  • Mandatory homework assignments.
  • Course language: English (based on participants the lectures can be held in German)

 

Exam / 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%)

Methodology

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.

 

Beratung und Kontakt

  • Umberto Michelucci

    Umberto Michelucci studied theoretical Physics and now leads the continuing education program at the IAS Institute at the ZHAW. He is also author on two books on deep learning published by Apress. HIs research focus on deep learning and machine learning.

    umberto.michelucci@gmail.com

     

     

  • Stefan Bischoff is Head of Enterprise Architecture at Helsana Insurance Company. 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. 

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Startdaten und Anmeldung

Start Anmeldeschluss Anmeldelink
07.02.2020 Anmeldung

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