Course

Project in Computer Science (DAT620)

Facts

Course code DAT620

Credits (ECTS) 10

Semester tuition start Autumn

Language of instruction English

Number of semesters 1

Exam semester Autumn

Time table View course schedule

Literature Search for literature in Leganto

Introduction

The project gives practice in solving a research assignment within the computer science area.

Content

Note! This is an elective course and may be cancelled if fewer than 10 students are enrolled by August 20 for the autumn semester/January 20 for the spring semester. 

The project gives practice in solving a research assignment within the computer science area. The project is intended as a pre-project for the master thesis. Project tasks are announced by the Department before the semester starts; projects can also be proposed by the student or a company, but approval is strict. It is not required that the student continues the work in a master thesis project, but such an opportunity is given in some cases. That is, the student is free to choose another master project. The Department assigns projects based on grades and the students ability to solve the selected task. If the student lacks the necessary prerequisites, one may risk not being assigned a project.

Every project must have a responsible Professor and a supervisor. For Department projects, the supervisor and responsible Professor may be the same person.

If deemed suitable by the supervisor, it is possible to take the project as group work with maximum two students per group. In this case, the division of tasks between each group member should be clearly stated in the final joint report. The total workload for each student will correspond to 10 ECTS.

Learning outcome

After having completed this course the student shall have detailed knowledge of the topic covered by the project, and be able to perform thorough research and development work within the specific topic.

Required prerequisite knowledge

None

Exam

Fakta

Weight 1/1

Duration 1 Semesters

Marks Letter grades

Aid All

Exam system Canvas

The course is assessed (internally) based only on the submitted report.

Each student must submit an individual report.

For group projects, a joint report will be submitted. Division of tasks must be explained in the report.

The project report must be handed in before 17th of December.

Re-sit exam opportunities are not offered on the project assignment. Students who do not pass the project assignment can take this part again the next time the course has regular teaching.

Method of work

15 hours of project work per week corresponding to 10 ECTS. There are not ordinary lectures in this course; each student or student group will receive independent supervision from the assigned supervisor. It is expected that the student performs independent work between supervision sessions similar to what is expected for a Master's thesis.

Using AI to support learning and study activities

AI tools may be used in DAT620 as a learning aid, but must never substitute for the ability to do independent research and development work the course builds — carrying out a thorough project and owning the method, results and report yourself is precisely what you must master. Productive uses include asking AI to explain a concept (e.g., how a research question is delimited, how a method is chosen, or how results are critically assessed), to gather background and references to inform your own work, or to improve the structure and language of work you have written yourself. Any use of AI must always be disclosed in your submission as specified in the syllabus, and you remain responsible for critically evaluating whatever the AI produces.

Overlapping courses

Course Reduction (SP)
Project in Computer Science (DAT620_1) , Project in Computer Science (MID240_1) 10

Open for

Admission to Single Courses at Master Level at the Faculty of Science and Technology
Data Science - Master Data Science - Master (Part-Time) Computer Science - Master Computer Science - Master (Part-Time)

Admission requirements

Must meet the admission requirements of one of the study programmes the course is open for.

Course assessment

The faculty decides whether early dialogue will be held in all courses or in selected groups of courses. The aim is to collect student feedback for improvements during the semester. In addition, a digital course evaluation must be conducted at least every three years to gather students’ experiences.

Contact

Course teacher:
Hein Meling
Head of Department:
Tom Ryen
Course teacher:
Rong Chunming
Course teacher:
Erlend Tøssebro
Course teacher:
Krisztian Balog
Course teacher:
Martin Georg Skjæveland
Course teacher:
Vinay Jayarama Setty
Course teacher:
Mina Farmanbar
Course teacher:
Naeem Khademi
Course coordinator:
Ferhat Özgur Catak
Mentor:
Nan Zhang

Offered by

Faculty of Science and Technology

Department of Electrical Engineering and Computer Science

The course description is retrieved from FS (Felles studentsystem). Version 1