Energy & Sustainability Management FT
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Digitization in Energy & Sustainability Management (E)

level of course unit

Consolidation

Learning outcomes of course unit

The students are able to:
• Present characteristics and performance parameters of various transmission tech-nologies
• Name systems, procedures and protocols of data transmission
• Explain basic terms concerning economic and legal aspects of the Internet infrastruc-ture
• Describe contents, results/applications and working methods of Data Science
• Apply basic functions in the processing of mass data including evaluation functions
• Describe basic concepts of programs for evaluating large quantities of data and independently create simple program codes for evaluations
- Apply tools for the evaluation of data

prerequisites and co-requisites

Scientific and Empirical Methods (WIS.1)

course contents

• Fundamentals of data transmission
• Technologies and applications of modern networks and data transmission
• Performance parameters of data transmission including broadband powerline, inter-net nodes, backbone networks
• Internet Protocol and domain name
• Business models for infrastructure service providers
• Legal requirements for infrastructure provision
• Data protection and data security
• Evaluation of measurement data
• Fundamentals of time series analysis

The module is made up of 67% exercises. This form of teaching takes place in small groups.

recommended or required reading

• Baun, C., 2018. Computernetze kompakt. 4. Auflage. Wiesbaden: Springer Vieweg
• Sauter, M., 2015. Grundkurs Mobile Kommunikationssysteme: LTE-Advanced, UMTS, HSPA, GSM, GPRS, Wireless LAN und Bluetooth. 6. Auflage. Wiesbaden: Springer Verlag
• Grus, J., 2016. Einführung in Data Science: Grundprinzipien der Datenanalyse mit Python. Sebastopol: O’Reilly Media
• Fasel, D., A. Meier, 2016. Big Data: Grundlagen, Systeme und Nutzungspotentiale. Wiesbaden: Springer Verlag
• Runkler, T.A., 2016. Data Analytics: Models and Algorithms for Intelligent Data Analysis. 2. Auflage. Wiesbaden: Springer Verlag

assessment methods and criteria

Examination and portfolio

language of instruction

English

number of ECTS credits allocated

9

eLearning quota in percent

30

course-hours-per-week (chw)

4.5

planned learning activities and teaching methods

Blended Learning

semester/trimester when the course unit is delivered

2

name of lecturer(s)

Asc. Prof. (FH) Dipl.-Ing. Christian Huber

year of study

1

course unit code

DIT

type of course unit

integrated lecture

mode of delivery

Compulsory

work placement(s)

none