IKT461 AI for Media, Language and Communication (Spring 2024)
- ECTS Credits:
- 7.5
- Responsible department:
- Faculty of Engineering and Science
- Course Leader:
- Christian Walter Peter Omlin
- Lecture Semester:
- Spring
- Teaching language:
- English.
- Duration:
- ½ year
Table of contents
The course is connected to the following study programs
- Artificial Intelligence and The Internet of Things, Master's Programme
- Artificial Intelligence, 5-year master programme
Teaching language
English.
Learning outcomes
After completion of the course, the students should
- have a broad overview of current applications of intelligent multimedia
- be able to perform multimedia analysis and synthesis with current techniques and algorithms
- have a systems perspective of implementation, systems, and services for multimedia analytics
- become familiar with current trends and future directions
Contents
Multimedia such as text, image, audio, video, and graphics stands out as one of the most demanding and exciting aspects of the information era. Rich multimedia applications and services such as content analysis, dialogue systems. search and recommendation, streaming, and delivery are emerging. Intelligent multimedia aims to build seamless yet efficient multimedia applications and services through breakthroughs in fundamental algorithm theory and innovation. The availability of vast data, advanced machine learning algorithms, and powerful computational infrastructures are making AI a key-enabling technology for the development of intelligent multimedia systems. The convergence of AI and multimedia drives AI to experience a paradigm shift towards explainable AI, while AI in turn injects new ways of thinking into multimedia. Potential applications include journalism, urban computing, healthcare, digital forensics, social media, and digital heritage. This course addresses problems of intelligent multimedia content sensing, processing, analysis, services, and scalability of multimedia computing systems
Teaching and learning methods
The tasks are done individually or in small groups with group supervision. Guest lectures may be invited to cover specific aspect of intelligent multimedia systems. The workload for the average student is approximately 200 hours.
Examinations
A group project (50%), written group report (50%). Graded assessment.
Student evaluation
The person responsible for the course decides, in cooperation with student representative, the form of student evaluation and whether the course is to have a midway or end of course evaluation in accordance with the quality system for education, chapter 4.1.
Offered as a free-standing course
Yes, if there are places available
Admission Requirement if given as a free-standing course
Admission requirements for the course are the same as for the master’s programme in ICT.
Last updated from FS (Felles studentsystem)
Oct. 15, 2026 10:55:49 AM