Facts about the course

ECTS Credits:
Responsible department:
Faculty of Logistics
Course Leader:
Berit Irene Helgheim
Lecture Semester:
Teaching language:
½ year

LOG904-153 Big Data (Autumn 2020)

About the course

Future logistics evolution based on ICT (Information Communication Tecnology) new developments. Big data analyses to improve the process and identify savings actions. IoT for tracking and real-time environment data. The potential of blockchain in the distribuited process for logistics, definition, and use-cases. Hand on data on big data using the R platform. Basic concepts for future applications, taking into account a load of data, data cleaning, data representation, and data analitics


Topics covered: Big Data Analysis and a soft introduction to R. IoT vision and the potential of real-time tracking. Blockchain concept and potential applications. Upcoming application use-case of this ICT approach. A small introduction to R for data analysis and hands-on.

The course is connected to the following study programs

Recommended requirements

No special needs

The student's learning outcomes after completing the course

Peception of future logistics process driver based on new ICT outputs. First steps on data analysis using R platform

Forms of teaching and learning

Perception of new challengers on logistics taking into account ICT developments – Homework1 (deliver on Tuesday) – small essay on a related topic. Hw2 (deliver on Thursday).Based on R a small use case is performed for student load data, clean and create.


Form of assessment: Home assessment with presentation:

  • Proportion: 30%

  • Duration: -

  • Grouping: Group

  • Grading scale: Letter (A - F)

  • Support material: All printed and written supporting material

Form of assessment: Work report:

  • Proportion: 70%

  • Duration: -

  • Grouping: Individual

  • Grading scale: Letter (A - F)

Last updated from FS (Common Student System) Oct. 18, 2021 7:20:05 PM