Admission requirements
Bachelor degree (completed)
Description
This seminar-style course studies the topic of artificial intelligence, taking a broad and historical view. Goal of the course is to learn studying, processing and presenting scientific material, and to learn about artificial intelligence. The seminar consists of lectures, multiple homework assignments/tests, and student presentations. Students are expected to participate in class discussions.
Up to 2023-2024, course presentations were mainly held by the students themselves, while few were given by the lecturer. As of 2024-2025, and guided by feedback from students, this balance will shift towards more presentations being held by the lecturer, and fewer by students. How exactly this is balanced will be discovered as the 2024-2025 course unfolds. However, students must still expect to present part of the teaching material themselves.
The course covers various topics from the field of artificial intelligence, to the level that should enable students to discuss AI comfortably and sensibly with other scientists. The selected topics were chosen to be relevant for understanding AI techniques, the history of AI, the broader context of AI (including alternative approaches to computation), and to make students think about future directions of AI. Topics include the questions of why we need AI and whether machines can think, evolutionary computation, neural network basics, computing with DNA, computers and emotions, computational creativity, and more. It is not a complete overview of AI topics. Some topics are not strictly AI but related; they were included to understand the history and broader context of artificial intelligence.
Course objectives
Through successfully completing the course, students learn to
outline the history and challenges of AI;
interpret the breadth of the field, articulate different views on what AI is, and characterize how these views relate;
articulate key concepts, such as philosophical concepts, the Turing Test, neural networks, evolutionary algorithms, DNA computing, social robotics, fear of AI, and more;
operate basic neural networks (training and testing) and evolutionary algorithms;
compare and contrast various topics and views of AI within an academic environment;
assess what is an appropriate AI method or approach for a given problem;
interpret and appraise future scenarios regarding AI.
Naturally, after the course, students can take a more in-depth course on specific topics from this course.
Timetable
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
Lectures, Seminar, Student presentations, Class discussion. Language: English.
Assessment method
Written homework test questions:
Frequent (un-announced) in-class written homework test questions are graded and collectively make up the larger part of the final grade. As such attendance in all lectures is mandatory. Non-completed homework test questions are graded with 0. The lowest of the homework test question grades is dropped from consideration, while the remaining ones are averaged to form component grade "GradeTest".
Student presentation:
Each student gives a compulsory graded presentation, either alone or as a pair. The presentation is evaluated to form component grade "GradePres". If a student fails to present, the presentation is graded with 0.
Final course grade:
The final grade for the course is established by determination of a weighted average of component grades GradePres and GradeTest.
If both GradePres and GradeTest are larger-or-equal to 5.5, then the final grade is composed by weighing GradePres:GradeTest with ratio 1:N.
Else, the final grade is the lowest of GradePres and GradeTest.
Naturally, the final grade is rounded according to Leiden University rules (nearest half-point with exception of 5.5).
Up to 2023-2024, in weighing the component grades N = 2. However, due to the abovementioned restructuring of the course in 2024-2025, it is possible that N > 2 (but no more than 4). The exact value of N will be determined by the lecturer, once the course has started and together with students the structure for the 2024-2025 course is set.
Retake rules:
The student presentation can only be retaken if GradePres < 5.5.
If-and-only-if the GradeTest < 5.5, then a single retake test is available that covers all course topics. The outcome of the retake test replaces GradeTest.
Grades resulting from retakes always replace the initial grade, regardless of being higher or lower than the initial grade.
Reading list
No book, only web-available materials. Communicated via the course Brightspace.
Registration
From the academic year 2022-2023 onward 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.
Contact
Contact the lecturer(s) for course specific questions, and the programme's coordinator for questions regarding admission and/or registration.
Remarks
Elective, external and exchange students (other than Media Technology MSc students) need to be admitted to the course before registration due to limited capacity of a seminar-structured course. Contact the programme's coordinator to request admission; include a short description of your course interest and state your current study programme in your correspondence.