Data deep dive

Postgraduate course

Course description

Learning Outcomes

Upon completion of the course the student should have the following learning outcomes defined in terms of knowledge, skills and general competence:


The student should be able to

  • explain one type of data thoroughly, including the entire data-generating process, steps in data preparation, data analyses, and resulting biases in data and interpretation.
  • compare different approaches for the analysis of the selected data type.


The student should be able to

  • preprocess and manage real world data sets
  • analyze and visualize real-world data sets

General competence

The student should be able to

  • create written scientific reports as well as critically assess specialist literature.
  • hold oral presentations on their own work.
  • reflect on central ethical and scientific issues in own and others' work

ECTS Credits


Level of Study


Semester of Instruction


Place of Instruction

Required Previous Knowledge
Recommended Previous Knowledge
Credit Reduction due to Course Overlap
Access to the Course
The course is open for students with admission to our study programme in Data Science (integrated Master¿s), 5 years
Teaching and learning methods
Lectures, presentations, project
Compulsory Assignments and Attendance
Oral presentation. Must be approved
Forms of Assessment

The subject uses the following form of assessment:

  • Compulsory written report

Both the compulsory written report and oral presentation will be on data type or data types containing the following aspects for each data type:

  • data collection
  • data preparation
  • data processing
  • data analysis
  • interpretation of results
Grading Scale
The grading scale used is A to F. Grade A is the highest passing grade in the grading scale, grade F is a fail.
Assessment Semester
Reading List
The reading list will be available within July 1st for the autumn semester and December 1st for the spring semester.
Course Evaluation
The course will be evaluated by the students in accordance with the quality assurance system at UiB and the department
Examination Support Material
Programme Committee
The Programme Committee is responsible for the content, structure and quality of the study programme and courses.
Course Coordinator
Course coordinator and administrative contact person can be found on Mitt UiB, or contact
Course Administrator
The Faculty of Mathematics and Natural Sciences represented by the Department of Informatics is the course administrator for the course and study programme.