Data deep dive
Postgraduate course
- ECTS credits
- 20
- Course code
- DSC316
- Teaching language
- Engelsk
- Resources
- Schedule
Course description
Objectives and Content
The course aims to develop a deeper understanding of at least one (or more) data types used in the real world. It contains methods from data collection, data preparation, data analysis, understanding biases in data and how to reduce them, as well as interpretation of results.
This course is linked to the project course DSC399K and will convey a deeper understanding of data types used in the master's project.
Learning Outcomes
Upon completion of the course the student should have the following learning outcomes defined in terms of knowledge, skills and general competence:
Knowledge
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.
Skills
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
Teaching and learning methods
Compulsory Assignments and Attendance
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