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Explainable Artificial Intelligence 3 Credits

In this course, we present an introduction to Explainable Artificial Intelligence (XAI). We describe the challenges associated with the use of black-box models and how we can overcome such challenges using interpretable and explainable methods. Moreover, we study other aspects related to interacting with AI-based systems, for example, trust, acceptance, evaluation, and Fairness Accountability and Transparency-issues.

For more information see https://ju.se/yrkesverksam/xai

Course Contents

This course gives an introduction to Explainable AI (XAI), providing an overview of relevant concepts such as interpretability, transparency and black-box machine learning methods. The course provides an overview of state-of-the-art methods for generating explanations, and touches upon issues related to decision-support, human interaction with AI/intelligent systems and their evaluation. In summary, the Explainable AI course covers the following topics:

- Definitions and concepts such as black-box models, transparency, interpretable machine learning and explanations.
- Decision-making and decision support, Human-Computer Interaction (HCI) and AI.
- Explainable AI.
- Methods for Explainable AI.
- Applications and examples.
- Trust and acceptance.
- Evaluation methods and metrics.
- Ethical, legal and social issues of explainable AI.

Prerequisites

The applicant must hold the minimum of a bachelor’s degree (i.e the equivalent of 180 ECTS credits at an accredited university) with at least 90 credits in computer engineering, computer science, information systems, mathematics, electrical engineering (both mathematics and electrical engineering should include relevant courses in computer engineering or computer science), or equivalent. The bachelor’s degree should comprise a minimum of 15 credits in mathematics. Proof of English proficiency is required.

Level of Education: Master
Course code/Ladok code: TEXR21
The course is conducted at: School of Engineering

Previous and ongoing course occasions

Type of course
Single subject
Study type
Distance
Number of required meetings
3
Semester
Autumn 2022: Oct 24 - Dec 18
Rate of Study
20%
Language
English
Location
Jönköping
Time
Mixed times
Number of places
20
Course coordinator
Maria Riveiro
Examiner
Maria Riveiro
Tuition fees do NOT apply for EU/EEA citizens or exchange students
7500kr
Syllabus
HTML  PDF
Application code
HJ-13161
Last modified 2023-03-15 14:06:56