What will I learn on this module?
The aim of the module is to provide you with knowledge and understanding of machine learning techniques and computer vision systems, including how to solve problems in these areas. In particular, you will cover topics such as:
• Machine learning
• Supervised machine learning techniques and classifiers
• Unsupervised machine learning techniques
• Computer vision and digital image fundamentals
• Legal, ethical and social issues in computer vision, and techniques for security.
• Application of machine learning techniques in computer vision (biometric systems, face, iris, fingerprint, etc.)
How will I learn on this module?
You will learn about concepts, mathematical principles and theories in formal lectures and these will be demonstrated, practised and discussed in practical workshop sessions. During these practical sessions you will complete/write program code and analyse/solve machine learning and computer vision problems. Two guided independent learning homework exercises will also be set for you to work on outside of class time. These will include problems in machine learning and computer vision intended to aid your understanding.
All module material will be available on the eLearning Portal (ELP) so that you can access information when you need to. The university library offers support for all students through its catalogue and an Ask4Help Online service.
How will I be supported academically on this module?
Your tutors will provide you with feedback on your work in the practical sessions and on the homework exercises to help you and them assess your progress.
What will I be expected to read on this module?
All modules at Northumbria include a range of reading materials that students are expected to engage with. The reading list for this module can be found at: http://readinglists.northumbria.ac.uk
(Reading List service online guide for academic staff this containing contact details for the Reading List team – http://library.northumbria.ac.uk/readinglists)
What will I be expected to achieve?
Knowledge & Understanding:
1. Demonstrate a comprehensive and detailed knowledge and critical understanding of the theory and practice of modern digital techniques in computer vision
2. Demonstrate a comprehensive understanding of machine learning systems and their applications.
Intellectual / Professional skills & abilities:
3. Apply and critically evaluate techniques to solve problems in machine learning and computer vision systems.
Personal Values Attributes (Global / Cultural awareness, Ethics, Curiosity) (PVA):
4. Critically analyse legal, ethical and social issues in computer vision as well as current technologies for cyber security
How will I be assessed?
Summative assessment
The summative assessment for the module
is a single individual assignment that combines programming and discursive writing. For this you will investigate computer vision and machine learning problems, and will develop and critically evaluate systems to solve them. The assessment will rely heavily on the work done during the practical lab sessions and will assess all of the module’s MLOs.
Written feedback on the summative assignment will be provided to you in the form of detailed marks and comments, highlighting strengths and improvements.
Formative assessment and feedback
The exercises in the practical workshops and two homework exercises are intended to help you and your tutor formatively assess your understanding and progress. You will be provided with feedback on these by your tutor.
Pre-requisite(s)
None
Co-requisite(s)
None
Module abstract
The aim of the module is to provide you with knowledge and understanding of machine learning techniques and computer vision systems, including how to solving problems in these areas.
Course info
UCAS Code G405
Credits 20
Level of Study Undergraduate
Mode of Study 3 years full-time or 4 years with a placement (sandwich)/study abroad
Department Computer and Information Sciences
Location City Campus, Northumbria University
City Newcastle
Start September 2022
All information on this course page is accurate at the time of viewing.
Our Campus based courses starting in 2022 and 2023 will be delivered on-campus with supporting online learning content. We continue to monitor government and local authority guidance in relation to Covid-19 and we are ready and able to adjust the delivery of our education accordingly to ensure the health and safety of our students and staff.
On-campus contact time is subject to increase or decrease in line with any additional restrictions, which may be imposed by the Government or the University in the interest of maintaining the health and safety and wellbeing of students, staff, and visitors. This could potentially mean increased or fully online delivery, should such restrictions on in-person contact time be required.
Our Campus based courses starting in 2022 and 2023 will be delivered on-campus with supporting online learning content. We continue to monitor government and local authority guidance in relation to Covid-19 and we are ready and able to adjust the delivery of our education accordingly to ensure the health and safety of our students and staff.
On-campus contact time is subject to increase or decrease in line with any additional restrictions, which may be imposed by the Government or the University in the interest of maintaining the health and safety and wellbeing of students, staff, and visitors. This could potentially mean increased or fully online delivery, should such restrictions on in-person contact time be required.
Current, Relevant and Inspiring
We continuously review and improve course content in consultation with our students and employers. To make sure we can inform you of any changes to your course register for updates on the course page.
Your Learning Experience find out about our distinctive approach at
www.northumbria.ac.uk/exp
Admissions Terms and Conditions - northumbria.ac.uk/terms
Fees and Funding - northumbria.ac.uk/fees
Admissions Policy - northumbria.ac.uk/adpolicy
Admissions Complaints Policy - northumbria.ac.uk/complaints
