Key information
- Faculty
- Faculty of Engineering Sciences
- Teaching department
- Electronic and Electrical Engineering
- Credit value
- 15
- Restrictions
-
Only available to TMSIMLSSYS01, UMNEENSEEE14, UMNEENSINT14, UMNEENWCME14, UMNEENWCOM14, TMREENCEPE19, CPD and MyAV范 Short Courses.
- Timetable
-
Alternative credit options
There are no alternative credit options available for this module.
This module will cover basic principles and practice of machine learning systems engineering. In particular, the module will cover a wide range of topics such as introduction to machine learning engineering, supervised learning algorithms, unsupervised learning algorithms, kernel learning, and neural networks. The module will encompass a series of lectures as well a series of hands-on programming sessions (or carried out remotely) so that students can learn how to apply machine learning technology to address various data science problems.
Module deliveries for 2024/25 academic year
Intended teaching term:
Term 1 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
- MyAV范 of students on module in previous year
-
39
- Module leader
-
Professor Miguel Rodrigues
- Who to contact for more information
- eee-msc-admin@ucl.ac.uk
Intended teaching term:
Term 1 听听听
Undergraduate (FHEQ Level 7)
Teaching and assessment
- Mode of study
- In person
- Methods of assessment
-
100%
Coursework
- Mark scheme
-
Numeric Marks
Other information
- MyAV范 of students on module in previous year
-
31
- 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.
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