Postgraduate Course: Credits Awarded for Taught Courses [University of Glasgow] Deep Learning (M) COMPSCI15085 (FREN11062)
Course Outline
| School | Deanery of Molecular, Genetic and Population Health Sciences |
College | College of Medicine and Veterinary Medicine |
| Credit level (Normal year taken) | SCQF Level 11 (Postgraduate) |
Availability | Not available to visiting students |
| SCQF Credits | 10 |
ECTS Credits | 5 |
| Summary | This is a placeholder course, designed to record marks for the University of Glasgow part of the programme, PRPHDISPME1F: Precision Medicine (PhD with Integrated Study) |
| Course description |
Please see [University of Glasgow] Deep Learning (M) COMPSCI15085 for Components of Assessment
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Entry Requirements (not applicable to Visiting Students)
| Pre-requisites |
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Co-requisites | |
| Prohibited Combinations | |
Other requirements | None |
Course Delivery Information
| Not being delivered |
Learning Outcomes
On completion of this course, the student will be able to:
- Understand the major technology trends in advanced machine learning
- Build, train and apply fully connected deep neural networks
- Know how to implement efficient, vectorised neural networks in python and understand the underlying backends
- Apply deep learning methods to new applications
- Understand the machine learning pipeline, and engineering aspects of training data collation, and the importance of unlabelled data
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Additional Information
| Graduate Attributes and Skills |
Not entered |
| Keywords | Not entered |
Contacts
| Course organiser | Dr Susan Farrington
Tel: (0131) 332 2471
Email: Susan.Farrington@ed.ac.uk |
Course secretary | Mrs Maree Hardie
Tel:
Email: maree.hardie@ed.ac.uk |
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