Maritime Data Analytics
About the course
The course is reserved for students at Bachelor in Ocean Engineering and cannot be taken as singular course.
This course content is aimed to give the necessary skills for handling data in the maritime sector. This will give solid understanding in how collected data should be handled and analysed with emphasis on the following topics:
- vessel IoTs and data collecting platforms
- data collection and storage onboard and onshore storage communication and storage facilities.
- different techniques for preprocessing, data cleaning, merging and transforming data sets will be treated.
- identification of data anomalies and recovering such data anomalies
- techniques for exploratory data analytics and visualization.
- utilization of big data in ship emission reduction and energy efficiency applications.
- concepts of Big Data handling, architecture and technologies and knowledge of it impact on the maritime sector
Objectives of the course
Knowledge
The student ...
- has knowledge of data set retrieval, requirements for preprocessing, explorative data analysis, cleaning, transforming, merging and transforming data and methods for handling missing data.
- has knowledge of how data is collected from the different maritime business areas, what characterizes the datasets as size, volume, velocity, variation and veracity
- has knowledge of how to utilize different techniques for handling Big Data.
Skills
The student ...
- can carry out data analyses for datasets typical of the maritime field with the use of programming language Python
- can assess which machine learning techniques are suitable for analyzing datasets generated from the maritime field
- can evaluate, visualize and communicate results from data analysis for shipping applications.
General competence
The student ...
- can perform a data analysis of a dataset generated from a maritime business area and communicate its results.
- can utilize big data techniques to improve and enhance energy efficiency and emission reduction for shipping applications.
Prerequisites
Anbefalte forkunnskaper
MAT-0001 Calculus in Applications, MAT-1050 Mathematics 1 for Engineers, MAT-1052 Mathematics 2 for Engineers, MAT-1060 Computational programming and Statistics, MFA-2100 Maritime Digitalization
Credit reduction
If you pass the examination in this course, you will get an reduction in credits (as stated below), if you previously have passed the following courses:
- BED-2056 Introduction to Data Science 5 ects
Teaching methods
Language of instruction and examination
EnglishSchedule
The schedules are normally finalized and published well in advance of the start of the semester, often a few weeks beforehand. This gives students the opportunity to organize their studies and prepare for upcoming activities.
It is recommended to check the schedule regularly, as changes may occur.
Examination
| School exam | Date: 16.06.2026 09:00 Duration: 4 Hours |
Grade: A–E, fail F |
To take an examination, the student must have passed the following coursework requirements
| Assignment | Grade: Approved – not approved |
| Assignment | Grade: Approved – not approved |
| Assignment | Grade: Approved – not approved |
| Assignment | Grade: Approved – not approved |
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