Key information
- Faculty
- Faculty of Engineering Sciences
- Teaching department
- Electronic and Electrical Engineering
- Credit value
- 15
- Restrictions
-
Only available to TMSIMLSSYS01, CPD and Ïã¸ÛÁùºÏ²ÊÖÐÌØÍø Short Courses.
- Timetable
-
Alternative credit options
There are no alternative credit options available for this module.
This module consists of a series of weekly seminars delivered by high-profile academics,
industrialists, or other stakeholders in machine learning technology to expose students to the most
cutting-edge topics in the field, including recent advances in machine learning theory, algorithms, and
applications, as well as issues such as privacy, fairness and ethics in artificial intelligence. Each
student will be required to maintain an up-to-date blog reporting the state-of-the-art in key topics.
Module deliveries for 2024/25 academic year
Intended teaching term:
Term 2 ÌýÌýÌý
Postgraduate (FHEQ Level 7)
Teaching and assessment
- Mode of study
- In person
- Methods of assessment
-
100%
Coursework
- Mark scheme
-
Numeric Marks
Other information
- Number of students on module in previous year
-
35
- Module leader
-
Professor Miguel Rodrigues
- Who to contact for more information
- eee-msc-admin@ucl.ac.uk
Last updated
This module description was last updated on 19th August 2024.
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