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Introduction

Location

Wheatley

Course Length

Full time: MSc - 1 year (12 months)

Why choose this course?

Overview

Our Artificial Intelligence (AI) course allows you to develop the skills, knowledge and understanding to:

 pursue careers in the cutting edge of AI
 implement novel technological solutions in real world problems.

It is ideal for recent graduates in computing, mathematics, engineering or a science-related subject with good programming skills. And those with substantial experience in the computing industry who want to gain a qualification that develops their expertise.

The course is informed by the state-of-the-art research being undertaken in the school. You will study:

 machine learning
 deep learning
 data science
 data visualisation
 big data and the cloud
 intelligent autonomous systems
 fundamental relevant aspects of cybersecurity.

Our labs are equipped with industry-standard equipment and software tools. This includes a ‘Fab’ lab and robotics lab with a range of platforms for you to implement Artificial Intelligence algorithms.

Modules

Compulsory modules

Introduction to Machine Learning (10 credits)

This module studies the fundamentals of machine learning methodologies, implementations and analysis methods appropriate for machine learning applications. Compulsory for MSc and PG Dip.

Foundations of Artificial Intelligence (AI) (10 credits)

This module teaches the fundamental concepts of AI including classical and modern approaches to AI and the philosophical bases of AI. Compulsory for MSc and PG Dip.

Autonomous Intelligent Systems (20 credits)

This module equips you with the knowledge and critical understanding how Autonomous Intelligent Systems are employed in a wide range of environments with different functionalities. Compulsory for MSc.

AI Systems Engineering (20 credits)

This module provides students with skills to critically evaluate and analyse the application artificial intelligence in the domain of systems engineering. Compulsory for MSc.

Data Visualisation (10 credits)

This module covers state of the art tools and techniques to build useful visualisations for different types of data sets and application scenarios. Compulsory for MSc.

Big Data and the Cloud (20 credits)

The cloud has become a key part of modern life and with it comes vast amounts of data. This module looks at how clouds work and can be used to tackle the big data challenges of modern science and business. Compulsory for MSc.

Research, Scholarship and Professional Skills (20 credits)

Advanced Machine Learning (10 credits)

This module equips students with skills to critically evaluate complex machine learning algorithms in different application scenarios. Compulsory for MSc.

Final Project

Compulsory modules

Dissertation in Computing Subjects (60 credits)

This is an individual research and development project that allows you to study a topic of your choice in the area of Artificial Intelligence in depth, guided by your supervisor. The work may be undertaken in close cooperation with a research, industrial or commercial organisation. You undertake your dissertation over the summer period if you are a full time student.

independent Study II (20 credits)


Research

The School of Engineering, Computing and Mathematics is home to world-leading and award-winning research. Our focus is on user-inspired original research with real-world applications.

We have a vibrant and growing research community, with a wide range of activities from model-driven system design and empirical software engineering through to web technologies, cloud computing and big data, digital forensics and computer vision.

Staff and students collaborate on projects supported by the EPSRC, the EU, the DTI, and several major UK companies.

Computing achieved an excellent assessment of its UoA (Unit of Assessment) 11 return for REF 2014 (Research Excellence Framework).

Students on this course can be involved with research in the following research groups:

 Institute for Ethical Artificial Intelligence
 Advanced Reliable Computer Systems (ARCoS)
 Applied Software Engineering and Data Analytics (ASEDA)
 Cloud Computing and Cybersecurity group (CCC)
 Artificial Intelligence and Robotics Group (AIR)
 Visual Artificial Intelligence Laboratory (VAIL)

Entry Criteria

ENTRY REQUIRED DOCUMENTS
Home Office Share Code
For EU students only.

IF no Qualification
Please provide CV with at least 2 years of work experience, and employee reference letter.
Entry requirements

Specific entry requirements

Due to great interest in this course for September 2023 entry, the deadline to receive applications is Wednesday 22 March 2023 for all applicants who will require a visa to study in the UK. As long as we receive your application on or before 22 March 2023 it will be given full consideration. Those not requiring a visa to study in the UK can continue to apply beyond 22 March 2023.

To join this course you'll need a 2:2 bachelor's degree in computing, maths, engineering or a science-related subject, in which good programming skills have been developed. Those without a degree in these areas, but who have worked in a related industry, and have good relevant experience and programming skills, can also apply.

If you have no experience or degree in a computing related discipline you should consider our MSc in Computing Science.

For the Postgraduate Certificate Research Project you should provide evidence of experience in research and study methods.

Our standard entry requirement is three A-levels or equivalent qualifications. In some cases, courses have specific required subjects and additional GCSE requirements. In addition to A-levels, we accept a wide range of other qualifications including:

 the Welsh Baccalaureate
 the Access to Higher Education Diploma
 a BTEC National Certificate, Diploma or Extended Diploma at a good standard and in a relevant subject
 the International Baccalaureate Diploma
 the European Baccalaureate Diploma
 Scottish qualifications – five subjects in SCE with two at Higher level or one at Advanced Higher level, or three subjects in Scottish Highers or two at Advanced Higher level
 a recognised foundation course
 T-levels*.
 * T-levels are a relatively new qualification but are already included in the UCAS tariff. We welcome prospective students who are taking this qualification to apply. For some programmes with specific required subjects, particular subject areas or occupational specialisms may be required.

English language requirements

If your first language is not English you will require a minimum IELTS score of 6.0 with 6.0 in all components.
OR
An equivalent English language qualification acceptable to the University.

If English is not your first language then you will need to show that your English language skills are at a high enough level to succeed in your studies.

The entry requirement for your course will be expressed as an IELTS level and refers to the IELTS Academic version of this test. We are now also accepting the IELTS Indicator test, you can find out more about the test on the IELTS Indication site. The University however does accept a wide range of additional English language qualifications, which can be found below.

The university’s English language requirements in IELTS levels are as follows:

Course IELTS level
All other undergraduate courses 6.0 overall with 6.0 in reading and writing, 5.5 in listening and speaking
Law, Architecture, Interior Architecture, English Literature (including combined honours), English Literature and Creative Writing 6.5 overall with 6.0 in reading and writing, 5.5 in listening and speaking
Health and Social Care courses 6.5 or 7.0 overall with 6.5 or 7.0 in all components (see individual entries for course details)
Nutrition BSc (Hons) 6.5 overall with a minimum of 6.0 in each component
Built Environment Foundation,
Computing Foundation,
Engineering Foundation 6.0 with 6.0 in reading and writing, 5.5 in listening and speaking
International Foundation Business and Technology,
International Foundation Arts, Humanities and Law 5.5 overall with 5.5 in all skills
International Foundation Diploma 5.0 overall with 5.0 in all skills
If you need a student visa you must take an IELTS for UKVI test.
International Foundation Diploma (Extended pathway) 4.5 overall with 4.5 in all skills
If you need a student visa you must take an IELTS for UKVI test.

Assessment

ASSESSMENT METHODS

1. INTERNAL ENGLISH TEST if you don't have an English accredited certificate
2. Academic Interview
Learning and assessment

You need to gain credits depending on the level of award you are studying:

MSc in Artificial Intelligence

You need 180 credits including:

 120 credits from taught modules
 60 credits from your dissertation.

Postgraduate Diploma in Artificial Intelligence

You must achieve 120 taught module credits.

In some cases, it may be possible for you to gain 60 taught module credits and 60 credits from a dissertation).

Postgraduate Certificate in Artificial Intelligence

You must achieve 60 credits.
You can also do a Postgraduate Certificate in Artificial Intelligence Research Project.

Part-time students normally distribute the work evenly over two years.

Learning and teaching

You will be taught with a combination of lectures and practical sessions. Lectures provide a theoretical basis, while practical sessions strengthen your understanding with active involvement.

You will be provided with a varied experience, as well as the opportunity to discuss your work directly with lecturers.

Many of the modules are enriched by the teaching staff's research expertise. We also invite visiting lecturers from research organisations and industry to come and give guest lectures.

Assessment

Assessment is continuous and includes:

 coursework exercises
 presentations
 lab work
 examinations
 reports.

Career Opportunities

We focus on using industry standard tools to solve practical and industrially relevant problems, and using those problems to teach the theoretical concepts. This ensures that students have the opportunity to acquire skills which will not just equip them for today's computing industry, but for a lifelong career in the computing industry.

Graduates, from the programme, will be ideally equipped for a career in wide variety of industries. Graduates are employed across a whole range of jobs, including

 data scientist
 software data engineer
 machine learning engineer
 machine learning scientist
 AI architect
 AI consultant
 AI specialist
 ML architect
 knowledge engineer.

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CONTACT

+44 777 477 5759
+44 33 3303 4135

info@study4abetterfuture.uk
admissions@study4abetterfuture.uk

Hours

Monday - Friday:

09:00 am - 06:00 pm

Saturday - Sunday: Closed

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