Emerging Topics in Integrated Machine Learning Systems (ELEC0139)

Key information

Faculty: Faculty of Engineering Sciences
Teaching department: Electronic and Electrical Engineering
Credit value: 15

Restrictions: Only available to TMSIMLSSYS01, CPD and 香港六合彩 Short Courses.
Timetable

Alternative credit options

There are no alternative credit options available for this module.

Description

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 听听听 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 8th April 2024.

听

Useful links

Sustainability

For a list of modules related to climate change as well as social and environmental sustainability at 香港六合彩, type 'climate' or 'sustainability' into the search. Visit Sustainable 香港六合彩 for information on extra-curricular activity on sustainability.

Important information

The catalogue has been updated with key information about the modules that will run during the 2024/25 academic session. Current and prospective students can browse through the catalogue to consider possible module choices for the coming year.

Please note,听information in the catalogue is听subject to change as teaching and assessment arrangements for 2024/25 may need to be adjusted in line with the University's Feedback and Assessment principles and operating model.

Centrally managed exam durations will be provided on students' individual exam timetables. Arrangements for locally managed exams and in-class activity will be confirmed by the teaching department for the module.

听