IN9490 – Advanced Topics in Artificial Intelligence for Intelligent Systems
Course description
Schedule, syllabus and examination date
Course content
Learning outcome
After taking the course, you will:
- have insight into novel methods (within e.g. evolutionary computation, neural networks, swarm intelligence) used in artificial intelligence (AI) and machine learning (ML)
- have knowledge about how to use AI and ML for various applications
- be able to search for and review literature outlining state-of-the-art within a specific research field.
- be able to critically assess scientific papers and be familiar with the structure of a scientific paper
- be able to design and conduct extensive experiments using AI and ML, with emphasis on evaluation
- have experience in presenting scientific work to others
- have experience in writing a scientific paper at a level suitable for publication at a relevant conference or journal
Admission to the course
The course is limited to 5 students (25 in IN5490 and 5 in IN9490, 30 in total). If the number of enrolled students is higher than the limit, they will be ranked as follows:
- PhD candidates affiliated to ROBIN and/or RITMO who have the course approved in their study plan and who will do research including AI/ML
- PhD candidates affiliated to the Department of Informatics or AUTOSENS who have the course approved in their study plan and who will do research including AI/ML
- PhD candidates with other affiliations at UiO who have the course approved in their study plan and who will do research including AI/ML
- Others
Recommended previous knowledge
Overlapping courses
- 10 credits overlap with IN5490 – Advanced Topics in Artificial Intelligence for Intelligent Systems.
- 5 credits overlap with IN9495 – Advanced Topics in Artificial Intelligence for Intelligent Systems (continued).
Teaching
The course material is taught through lectures, discussions, supervision, and assignments. Lectures and student presentations will be organised as two- or three-week workshop sessions. Teaching is combined with IN5490. Project work is done in groups in between the workshop weeks and will be guided by a group supervisor who is an expert on the chosen topic.
80% workshop sessions (lectures, discussions etc) attendance is required, and the students must be active in discussions and give at least one paper summary presentation and one or more presentation(s) of their project. There are mandatory assignments/tasks that must be approved. Mandatory assignments and other hand-ins at Department of Informatics during the pandemic
Examination
To pass, the following requirements need to be fulfilled throughout the semester:
- Students must give at least one paper summary presentation.
- Prepare one paper draft and get approved compulsory assignments. Equal contribution of each project member in a group is expected, otherwise, additional assignments may have to be passed.
- Attend at least 80% of all seminar sessions.
The paper draft will consist of a more thorough set of experiments and a 50% longer paper compared to IN5490, and assignments of the PhD-students will entail additional work compared to IN5490.
It will also be counted as one of your three attempts to sit the exam for this course, if you sit the exam for one of the following courses: IN5490 – Advanced Topics in Artificial Intelligence for Intelligent Systems
Language of examination
Grading scale
Resit an examination
In this course, postponed exams are not offered for exam candidates who are ill before the exam or who become ill during the exam. A deferred submission deadline may be offered. Deadlines may be extended up to 7 days; the duration of the extension depends on the duration of the exam. The illness must be documented with a doctor's certificate dated no later than the ordinary submission date. You must submit the doctor's certificate to the Student Administration at IFI before the submission deadline for the home exam.
https://www.uio.no/english/studies/examinations/illness-postponed/index.html
More about examinations at UiO
- Use of sources and citations
- How to use AI as a student
- Special exam arrangements due to individual needs
- Withdrawal from an exam
- Illness at exams / postponed exams
- Explanation of grades and appeals
- Resitting an exam
- Cheating/attempted cheating
You will find further guides and resources at the web page on examinations at UiO.