Assumed prior knowledge
You must have completed the course Introduction to Deep Learning 2022-23 (or an equivalent course elsewhere) with a grade of at least 8.5. See the registration procedure below.
In recent years we have witnessed an explosion of research, development, and applications of Deep Learning. The main objective of this course is to provide a wide overview of the current state of this area and to focus on a few, carefully selected topics, covering them in depth by studying and presenting most relevant papers, and doing own research on these selected topics. This research will have a form of producing new experimental results, developing new algorithms or theories and documenting findings in scientific reports. The best reports can be submitted to conferences or published as research papers.
During the course students will work (in small teams) on selected topics/problems, performing experiments on GPU-computers (if applicable), reporting on their progress during weekly meetings. Each team will have to summarize their work in a final presentation and a project report.
During the course students will:
gain an overall picture of the recent developments in Deep Learning,
identify some promising research directions,
gain some hands-on research experience, including studying related papers, identifying research problems, inventing solutions of these problems, verifying their ideas by experimenting and documenting findings in a scientific style,
learn to work together is small research teams,
learn to prepare and give presentations,
learn to write scientific reports.
The most recent timetable can be found at the Computer Science (MSc) student website.
You will find the timetables for all courses and degree programmes of Leiden University in the tool MyTimetable (login). Any teaching activities that you have sucessfully registered for in MyStudyMap will automatically be displayed in MyTimeTable. Any timetables that you add manually, will be saved and automatically displayed the next time you sign in.
MyTimetable allows you to integrate your timetable with your calendar apps such as Outlook, Google Calendar, Apple Calendar and other calendar apps on your smartphone. Any timetable changes will be automatically synced with your calendar. If you wish, you can also receive an email notification of the change. You can turn notifications on in ‘Settings’ (after login).
For more information, watch the video or go the the 'help-page' in MyTimetable. Please note: Joint Degree students Leiden/Delft have to merge their two different timetables into one. This video explains how to do this.
Mode of instruction
Presentations, discussions, feedback on students presentations and reports.
Total hours of study: 168 hrs. (= 6 EC)
The final grade will depend on student's participation in discussions, quality of presentations and the quality of the final report. Each team will receive a grade which is a rounded average of grades for the following components:
Other (code publication, new data, conference submission,etc)
The team's grade will be internally distributed among team members according to their individual contributions to the project.
Various articles, reports, conference proceedings.
Students should also sign up for the course before 15 January 2023. Due to the format of the course, the maximal number of students that can participate in this course is limited to 30. In case when more than 30 students would like to attend this course we will use the final grade for the required courses (see the Admission Requirements) and the result of individual interviews with course organizers to make the final selection.
From the academic year 2022-2023 on every student has to register for courses with the new enrollment tool MyStudyMap. There are two registration periods per year: registration for the fall semester opens in July and registration for the spring semester opens in December. Please see this page for more information.
Please note that it is compulsory to both preregister and confirm your participation for every exam and retake. Not being registered for a course means that you are not allowed to participate in the final exam of the course. Confirming your exam participation is possible until ten days before the exam.
Extensive FAQ's on MyStudymap can be found here.
Lecturers: dr. Wojtek Kowalczyk, drs. Andrius Bernatavicius
- Due to the format of the course, the maximal number of students that can participate in this course is limited to 30.
- This course is also suitable/recommended to PhD students who want to use Deep Learning in their projects.