Data Science & Intelligent Analytics PT
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Trends in Smart Products (elective)

level of course unit

Master's course

Learning outcomes of course unit

The following learning outcomes are developed in the course:

- Students will understand the concepts of smart applications such as Smart House, Smart City, Smart Production, Connected Vehicles etc.- Students know and understand the latest trends in the field of these applications

prerequisites and co-requisites

No prerequisites

course contents

The contents of this course are not set, but will be adapted to the current prevailing trends. Content examples may include:

- Current best practice approaches and concepts in application areas (e.g. Smart Home, Smart City, Smart Production, Connected Vehicles etc.)
- Current best practice approaches with regard to development processes and tools
- Current research and development activities or research and development results

recommended or required reading

- Huber W.; Industrie 4.0 kompakt – Wie Technologien unsere Wirtschaft und unsere Unternehmen verändern: Trans-formation und Veränderung des gesamten Unternehmens; Wiesbaden; 2018
- Iyer B., Venkatraman V.; “What comes after smart products?”, Havard Business Review; 2015
- Roth A.; Einführung und Umsetzung von Industrie 4.0: Grundlagen, Vorgehensmodell und Use Cases aus der Praxis; Wiesbaden; 2016

assessment methods and criteria

Seminar thesis

language of instruction

German

number of ECTS credits allocated

3

eLearning quota in percent

0

course-hours-per-week (chw)

2

planned learning activities and teaching methods

Lecture, exercise

semester/trimester when the course unit is delivered

4

name of lecturer(s)

Prof. (FH) Dipl.-Informatiker Karsten Böhm

course unit code

WPF.11

type of course unit

integrated lecture

mode of delivery

Compulsory

work placement(s)

none