The course will start with a part, where we study how a scientific article is constructed. The students will then, in groups of 2-5, choose articles in their sub-track (machine learning, natural language processing or bioinformatics), implement the method in the article and recreate the experiment. The type of project therefore will vary depending on sub-track, but the intended learning outcomes are the same for all three sub-tracks. The aim of the course is to bridge the gap between the courses in each sub-track and the degree project.
DD2430 Project Course in Data Science 7.5 credits
Information per course offering
Information for Autumn 2024 DSPHT23 programme students
- Course location
KTH Campus
- Duration
- 26 Aug 2024 - 13 Jan 2025
- Periods
- P1 (3.5 hp), P2 (4.0 hp)
- Pace of study
25%
- Application code
50273
- Form of study
Normal Daytime
- Language of instruction
English
- Course memo
- Course memo is not published
- Number of places
Places are not limited
- Target group
- No information inserted
- Planned modular schedule
- [object Object]
- Schedule
Contact
Danica Kragic Jensfelt (dani@kth.se)
Course syllabus as PDF
Please note: all information from the Course syllabus is available on this page in an accessible format.
Course syllabus DD2430 (Autumn 2021–)Headings with content from the Course syllabus DD2430 (Autumn 2021–) are denoted with an asterisk ( )
Content and learning outcomes
Course contents
Intended learning outcomes
After passing the course, the 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 subtracks of the track Data Science in the Computer Science masters programme.
Equipment
No information inserted
Literature
No information inserted
Examination and completion
If the course is discontinued, students may request to be examined during the following two academic years.
Grading scale
P, F
Examination
- PRO1 - Project report, 3.5 credits, grading scale: P, F
- PRO2 - Oral evaluation, 4.0 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.
The examiner may apply another examination format when re-examining individual students.
Opportunity to complete the requirements via supplementary examination
No information inserted
Opportunity to raise an approved grade via renewed examination
No information inserted
Examiner
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. A link to the course room can be found under the tab Studies in the Personal menu at the start of the course.
Offered by
Main field of study
Computer Science and Engineering
Education cycle
Second cycle
Add-on studies
No information inserted
Contact
Danica Kragic Jensfelt (dani@kth.se)
Supplementary information
In this course, the EECS code of honor applies, see:
http://www.kth.se/en/eecs/utbildning/hederskodex