|History:||This course was formerly known as Methods in AI research (INFOMMAIR). You can only do one of these courses.|
|Period:||period 1 (week 36 through 45, i.e., 2-9-2019 through 8-11-2019; retake week 2)|
|Participants:||see Osiris Docent|
|Schedule:||Official schedule representation can be found in Osiris|
Artificial Intelligence is a fast-paced and challenging field that is making visible inroads into our everyday life. AI in Utrecht offers a unique interdisciplinary approach, integrating the areas of computer science and agent systems, cognition and psychology, logic and philosophy, and linguistics. Because of this interdisciplinary character, the variety of techniques and methods used is considerable, ranging from theoretical to empirical, and from formal mathematical to more informal philosophical.
In this course, we will introduce the various perspectives on AI in Utrecht and the methods associated with them. We will look at the basics of machine learning, logic and symbolic reasoning, cognitive science and computational linguistics, and discuss the part they play in modern AI systems. We will further discuss important methods commonly used in AI research: knowledge modelling, system engineering, and empirical evaluation of machine learning and human-computer interaction. We further practice general academic skills such as reviewing literature, working in teams and scientific writing. The linking pin of the course is a central lab project in which you will develop, describe, test, and evaluate a dialog system (sometimes also referred to as “chatbot”). In this way, the theory from the lectures forms the basis of a real AI application that you will evaluate with users.
The learning objectives of this course are as follows. At the end of the course you will:
|Literature:||See Blackboard page for the course.|
|Course form:||Lectures and lab sessions.|
The final grade for the course is composed as follows:
To pass the course all three individual grades need to be at least 5.0 unrounded. Moreover, the weighted final grade needs to be at least 5.5 unrounded.
|Minimum effort to qualify for 2nd chance exam:|
If you score 4.0 or higher for one of the project parts then you can submit an improved version of that part of the project for a maximum grade of 5.5 for the resubmitted part. The deadline and requirements for improvements are set on an individual basis.
If you score higher than a 4.0 for the first exam you can attend the retake exam in January. Note that students who pass the course after the first exam will not be admitted to the re-exam.