Program Overview

Course Information

Course Description

The course DD2430 Project Course in Data Science is a 7.5 credit course that aims to bridge the gap between the courses in each sub-track and the degree project. The course will start with a part where students study how a scientific article is constructed, and then, in groups of 2-5, choose articles in their sub-track, implement the method in the article, and recreate the experiment.

Intended Learning Outcomes

After passing the course, students should be able to:

• read scientific articles critically
• reproduce methods in articles
• plan and carry out work in a group

Literature and Preparations

Specific Prerequisites

• DD2421 Machine learning or the equivalent

Recommended Prerequisites

• The student should have completed most of the courses in one of the sub-tracks of the track Data Science in the Computer Science masters programme

Literature

Information about course literature can be found in the course memo for the course offering or in the course room in Canvas

Examination and Completion

Grading Scale

• P, F

Examination

• PRO2 - Oral evaluation, 4.0 credits, grading scale: P, F
• PRO1 - Project report, 3.5 credits, grading scale: P, F Based on recommendation from KTH's coordinator for disabilities, the examiner will decide how to adapt an examination for students with documented disability

Ethical Approach

• All members of a group are responsible for the group's work
• In any assessment, every student shall honestly disclose any help received and sources used
• In an oral assessment, every student shall be able to present and answer questions about the entire assignment and solution

Further Information

Course Room in Canvas

Registered students find further information about the implementation of the course in the course room in Canvas

Offered by

• EECS/Intelligent Systems

Main Field of Study

• Computer Science and Engineering

Education Cycle

• Second cycle

Program Details

Part of Programme

• Master's Programme, Computer Science, year 2, CSDA, Mandatory
• Master's Programme, Machine Learning, year 2
• Master's Programme, Systems, Control and Robotics, year 1

Information per Course Offering

• Course location: KTH Campus
• Duration: 24 Aug 2026 - 11 Jan 2027
• Periods: Autumn 2026: P2 (4 hp), P1 (3.5 hp)
• Pace of study: 25%
• Application code: 11253
• Form of study: Normal Daytime
• Language of instruction: English
• Number of places: Min: 1
• Target group: No information inserted
• Planned modular schedule: No information inserted
• Schedule: Schedule is not published