- Deep networks.
- Probabilistic deep learning.
- Deep transfer and sharing of knowledge.
- Unsupervised deep representation learning.
- Higher order learning.
- Adversarial learning.
DD2412 Deep Learning, Advanced Course 6.0 credits
This course will be discontinued.
Last planned examination: Autumn 2026
Decision to discontinue this course:
The course will be discontinued at the end of HT 2024 according to faculty board decision: J-2024-2663.
Decision date: 2024-11-12
The course is offered for the last time HT 2024. The last opportunity to take an examination in the course is HT 2026.
Students who wish to complete the course must contact the examiner.
The course goes beyond the basic principles of deep learning by delving into the frontiers of deep learning research.
Information per course offering
Choose semester and course offering to see current information and more about the course, such as course syllabus, study period, and application information.
Course syllabus as PDF
Please note: all information from the Course syllabus is available on this page in an accessible format.
Course syllabus DD2412 (Autumn 2024–)Content and learning outcomes
Course contents
Intended learning outcomes
After passing the course, the students should be able to:
- explain and justify the subareas of deep learning,
- account for the theoretical background for advanced deep learning techniques,
- identify the directions in which additional research can be made to develop the field,
- implement methods based on recently published results,
- analyse advanced research in the area and critically evaluate the methods' weaknesses and strengths
in order to
- prepare for degree project/postgraduate studies in deep learning,
- become better trained to meet industry's need of key competence in the area.
Literature and preparations
Specific prerequisites
Knowledge in deep learning, 6 credits, corresponding to completed course DD2424/DD2437.
Active participation in a course offering where the final examination is not yet reported in Ladok is considered equivalent to completion of the course.
Registering for a course is counted as active participation.
The term 'final examination' encompasses both the regular examination and the first re-examination.
Recommended prerequisites
DD2424
Equipment
Literature
Examination and completion
If the course is discontinued, students may request to be examined during the following two academic years.
Grading scale
Examination
- LAB1 - Laboratory work, 3.0 credits, grading scale: P, F
- PRO1 - Project assignment, 3.0 credits, grading scale: A, B, C, D, E, FX, 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
Opportunity to raise an approved grade via renewed examination
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
Offered by
Main field of study
Education cycle
Add-on studies
Contact
Transitional regulations
The former module TEN1 has been replaced by PRO1.
Supplementary information
In this course, the EECS code of honor applies, see:
http://www.kth.se/en/eecs/utbildning/hederskodex