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.
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.
As of 2025-2026, and guided by feedback from students, the balance between (a) course presentations given by the lecturer, and (b) presentations held by students themselves, will shift towards more presentations being held by the lecturer, and fewer by students. How exactly this is balanced will be discovered as the 2025-2026 course unfolds. However, students must still expect to present part of the teaching material themselves.
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
In MyTimetable, you can find all course and programme schedules, allowing you to create your personal timetable. Activities for which you have enrolled via MyStudyMap will automatically appear in your timetable.
Additionally, you can easily link MyTimetable to a calendar app on your phone, and schedule changes will be automatically updated in your calendar. You can also choose to receive email notifications about schedule changes. You can enable notifications in Settings after logging in.
Questions? Watch the video, read the instructions, or contact the ISSC helpdesk.
Note: Joint Degree students from Leiden/Delft need to combine information from both the Leiden and Delft MyTimetables to see a complete schedule. This video explains how to do it.
Mode of instruction
Lectures, Student presentations, Class discussion. Language: English.
Assessment method
Written in-class test questions:
Frequent (un-announced) in-class written test questions about the homework and material are graded and collectively make up the larger part of the final course grade. As such attendance in all lectures is mandatory. Non-completed 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 assignments:
Each student must complete a compulsory graded assignment, either alone or as a pair. The assignment may involve writing, presenting, creating a video lecture, etcetera. The assignment outcomes are always shared with the students in class as part of the teaching method. The grade obtained for the assignment forms the component grade "GradeAssignment". If a student fails or does not submit the assignment in time, then it is graded with 0.
Final course grade:
The final grade for the course is established by determination of a weighted average of component grades GradeTest and GradeAssignment.
If both GradeTest and GradeAssignment are larger-or-equal to 5.5, then the final grade is composed by weighing GradeTest : GradeAssignment with ratio N : 1.
Else, the final grade is the lowest of GradeTest and GradeAssignment.
Naturally, the final grade is rounded according to Leiden University rules (nearest half-point with exception of 5.5).
In 2024-2025, in weighing the component grades N was 3. However, due to restructuring of the course in 2025-2026, it is possible that N > 3 (but no more than 5). The exact value of N will be determined by the lecturer before the start of the course, once the exact topics and number of tests is known, and communicated in Brightspace and the first class.
Retake rules:
The student assignment can only be retaken if GradeAssignment < 5.5. In that case, a deadline is communicated before the retake period starts.
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. The date of the single retake test is communicated before the retake period starts.
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
As a student, you are responsible for enrolling on time through MyStudyMap.
In this short video, you can see step-by-step how to enrol for courses in MyStudyMap.
Extensive information about the operation of MyStudyMap can be found here.
There are two enrolment periods per year:
Enrolment for the fall opens in July
Enrolment for the spring opens in December
See this page for more information about deadlines and enrolling for courses and exams.
Note:
It is mandatory to enrol for all activities of a course that you are going to follow.
Your enrolment is only complete when you submit your course planning in the ‘Ready for enrolment’ tab by clicking ‘Send’.
Not being enrolled for an exam/resit means that you are not allowed to participate in the exam/resit.
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 and Creative Intelligence & Techology MSc students) need to be admitted to the course before registration due to limited capacity of a seminar-structured course. Placement in the course is not guaranteed for elective, external and exchange students. Contact the programme's coordinator and course lecturer to request admission; include a short description of your course interest and state your current study programme in your correspondence.
Software
Starting from the 2024/2025 academic year, the Faculty of Science will use the software distribution platform Academic Software. Through this platform, you can access the software needed for specific courses in your studies. For some software, your laptop must meet certain system requirements, which will be specified with the software. It is important to install the software before the start of the course. More information about the laptop requirements can be found on the student website.