Course - Data science - TMA4269
Data science
New from the academic year 2026/2027
About
About the course
Course content
Data science is about extracting knowledge from data. This includes identifying patterns, making predictions, communicating results, and supporting decision-making. This course provides a practical and example-based introduction to fundamental topics such as data visualisation, regression models, and machine learning. We will discuss the limitations of data analysis and modeling to avoid misinterpretation or misuse of model results.
Learning outcome
The student is familiar with the most common methods and algorithms for data visualisation, modeling, and prediction. The student can critically evaluate results from various data science processes. This includes understanding the limitations of models, as well as being able to discuss the implications of these with others.
Learning methods and activities
Primarily discussion of case studies in groups and in plenary sessions with the course instructor.
Further on evaluation
(the information may be changed until June 15th)
Portfolio assessment. The portfolio includes group assignments that are submitted at different times throughout the semester. Details will be specified on the course website at the start of the semester.
Recommended previous knowledge
No prerequisites required; TDT4110 and TMA4240/45 or equivalent are recommended.
Course materials
The course material will be communicated at the beginning of the semester.
Subject areas
- Statistics
- Technological subjects