Postgraduate MSc/PgDip

Artificial Intelligence

School of Science, Engineering and Environment

Attendance

Full-time

Part-time

Course

One year

Three year

Next enrolment

January 2023

Introduction

In a nutshell

Artificial intelligence is poised to take a leading role in our daily lives. Powerful big data combined with intelligent machine learning will change how organisations function and how we use and experience services.  If you’re ready to be part of this exciting digital transformation, our Artificial Intelligence postgraduate degree will equip you with in-demand knowledge and skills.

Businesses and organisations in many industries are discovering how AI can transform productivity, realise efficiencies and introduce personalised products and services.  To build AI capacity, many will rely on skilled professionals to oversee its integration, governance and monitoring.  Predicted to be one of the UK’s fastest growing career fields over the next decade, now is the time to develop relevant skills to take advantage of exciting opportunities.

Based on research in Machine Learning and Deep Learning, our Artificial Intelligence postgraduate degree course delivers specialist knowledge that connects to trends emerging in healthcare, commerce, transport, professional services and the built environment. Available with full and part-time study pathways, and with start dates each January and September, we recommend the course as a platform for graduates and existing professionals to build knowledge and skills that can lead to exciting career opportunities.

The University of Salford is a great place to start your artificial intelligence journey.  Location at the heart of Greater Manchester, home to one of the fastest-growing tech communities in Europe, we use our industry collaboration strategy to provide you with access to real-world projects and career networks. We’re also a delivery partner in the Greater Manchester AI Foundry, our region's plan to empower businesses and organisations to take advantage of machine learning and intelligence.

This course starts in January 2023.

Start your study journey

Register for our next Open Day to learn more about studying Artificial Intelligence and speak to the course team

You will:

  • Engage with advanced methods and techniques such as Deep Learning and Natural Language Processing
  • Develop practical skills as you learn how to develop AI application using Tensorflow and Keras
  • Experience specialist labs, computer workstations, and online tools supported by research-active tutors and technicians
International

students accepted

This is for you if...

1.

You're a recent graduate looking to add artificial intelligence knowledge and skills to enhance your first degree in computing or a computing related discipline

2.

You're an industry professional seeking to enhance your existing skills and knowledge for a future career focus in artificial intelligence

3.

You're a knowledge-seeker and want to explore the 'art of the possible' in using artificial intelligence to address global and societal challenges

Course details

All about the course

Get ready to join the digital revolution. Our MSc Artificial Intelligence postgraduate degree offers advanced knowledge and skill development, driven by industry collaboration, and delivered in research-focused learning environment.

"At Salford, we strive to provide our students with skills for the future. This new and exciting course is a perfect example of how we adapt and pivot to our ever-changing world, and is a direct response to the exponential importance of AI and the role it plays in our digital lives." 

Professor Sunil Vadera

Course delivery

The course is delivered through a range of highly-focused modules. The 180-credit MSc award comprises four taught modules, plus a research dissertation.  The 120-credit PgDip award comprises four taught modules.

Flexibility is at the heart of our learning approach. You can choose to study this postgraduate course full-time or part-time on campus, with start dates in January and September:

  • Full-time students will complete taught modules in each of the first two trimesters, and complete the 60-credit dissertation project in trimester three
  • Part-time students will complete taught modules in years one and two, and complete the dissertation project in year three

During your studies, you will have access to specialist project labs, computer workstations, and online tools. You will also benefit from our strong links with local businesses through our membership of the Greater Manchester Artificial Intelligence Foundry.

Course content

Drawing on research in machine learning and deep learning, our course provides you with a systematic understanding of AI techniques that will enable you to develop and apply AI solutions in a range of settings. Along with developing technical skills, you will also develop research and professional skills, so you can be ready to meet the needs of employers in this exciting and rapidly evolving field.

Current course topics include data mining, big data analytics, deep learning and natural language processing. We regularly review module content with our industry partners to ensure your acquired knowledge and skill set reflects trends and needs within professional and business communities. Learn more about the current course modules in the section below.

Course team

The Artificial Engineering postgraduate programme is delivered by an academic team with extensive industry experience and research connections, and a track record of developing software solutions through industry partnerships.

Course leader: Professor Sunil Vadera

Modules

Big Data Tools and Techniques (AI)

This module introduces you to the tools and techniques to build decision making systems for business organisations. You will learn how to gather large sets of data and information, and produce outputs and reports that enable organisations to make strategic decisions to improve their businesses and predict future trends.

You will learn to critically assess diverse issues regarding the use of statistics in real-world contexts, including:

  • ethics
  • how to design, justify, apply and evaluate strategies for using data mining techniques in diverse business contexts
  • how to devise strategies for making effective use of analytical software such as SAS Enterprise Miner

Deep Learning

This module is designed to develop your understanding of the fundamental principles and theories of deep learning.

The module content covers topics such as convolutional neural networks, recurrent neural networks, sequential networks, transformers and their applications.

Natural Language Processing

In this module you will develop your skills and understanding of Tokenisation, Stemming, and Segmentation, and Maximum Entropy Models, Semantics, Text classification and Neural Network Architectures for NLP.

MSc Project

The project module aims to provide you with an opportunity to integrate learning from the course modules, working under the direction of an academic supervisor to carry out high-level coordinated academic and practical work on researching a suitable problem and developing, evaluating and critically assessing a robust, scalable and usable solution.

New

Machine Learning and Data Mining

In this module, you will explore the full data mining lifecycle, from data pre-processing and exploratory data analysis to the application and evaluation of supervised and unsupervised machine learning algorithms. Through practical, hands-on workshops using Python and Microsoft Azure Machine Learning, you will gain experience at using machine learning and data mining tools and techniques to extract insights from data. 

Please note that it may not be possible to deliver the full list of options every year as this will depend on factors such as how many students choose a particular option. Exact modules may also vary in order to keep content current. When accepting your offer of a place to study on this programme, you should be aware that not all optional modules will be running each year. Your tutor will be able to advise you as to the available options on or before the start of the programme. Whilst the University tries to ensure that you are able to undertake your preferred options, it cannot guarantee this.

What will I be doing?

TEACHING

The majority of teaching and learning is delivered through tutorial and seminar groups.

You will benefit from high-quality teaching materials and software. Interaction is face-to-face wherever practical, but we also use web-based learning support packages (databases of materials, discussion boards etc.).

Group activities are designed to develop your team working and professional skills (though all assessment is individual). Supervised work in computer laboratories puts into practice principles you have covered in supporting lectures.

Independent learning

When not attending lectures, seminars and other timetabled sessions, we encourage you to continue learning independently through self-study. 

Independent learning typically involve reading journal articles and books, working on individual and group projects, undertaking research, and preparing coursework, assignments and presentations.

We support your independent learning through a range of excellent facilities, including our 24-hour campus library, online resources, and dedicated learning zones.

ASSESSMENT

Projects and assignments are designed to develop your independent learning skills and your ability to make decisions in uncertain situations. Blending research-based assignments and practical mini-projects, we will get you to apply your learning to authentic problem-solving. 

Professionalism and ethics are woven throughout the course, and form an integral part of all assignments and projects.

The final 60-credit Project module is your opportunity to demonstrate your ability to conduct research, develop an application and use appropriate AI toolkits. You can choose an AI-focused topic from the course, or something connected to your current role or future career plans.

Feedback

You will receive feedback on all practical and formal assessments undertaken by coursework. Feedback on examination performance will be available upon request from the relevant module leader. 

School of Science, Engineering and Environment

Rising to the challenge of a changing world, our postgraduate courses are designed to shape the next generation of urbanists, scientists, engineers, consultants and leaders.

Shaped by industry, and delivered by supportive programme teams, you can develop the skills to take your career potential further.

Learning Environment

Our computing suites are equipped with software platforms and languages used in machine learning, data mining, and statistical analysis. These include SAS Enterprise Guide & Miner, Python, Apache Hadoop & Spark, RapidMiner, plus NoSQL databases, such as MongoDB.

Leading the way

The University of Salford is at the forefront of developing AI to revolutionise transport. 

Since 2019, the University has pioneered industry-focused research and industry focus through its acquisition of a NAVYA autonomous shuttle, and the creation of the Automotive and Autonomous Vehicle Technology (AAVT) Labs.

 

Industry collaboration and research

When you start this degree with Salford, you are also joining a community making a difference in industry, our local region and in our wider society.

Many of our academics and technicians who support your course also deliver collaborative, interdisciplinary, high-impact work in a range of local and global computing and informatics issues and challenges.

Discover how you are part of something bigger.

Employment and stats

What about after uni?

Computer scientist

EMPLOYMENT

Artificial Intelligence (AI) skills are in high demand.  The technology is revolutionising industries and sectors, including healthcare, finance (Fintech), energy, transport (autonomous vehicles), manufacturing, central government, neuroscience companies, plus marketing, social media, mobile and gaming.

With these exciting developments in mind, we’ve designed our MSc Artificial Intelligence course to prepare graduates for AI roles, and to help current technology and business professionals build new knowledge and skills to apply in their roles. Budding tech entrepreneurs and future research candidates will also gain essential AI knowledge to support their ambitions.

Equipped with the knowledge and skills you will develop on our MSc Artificial Intelligence course, graduates can look for careers working in artificial intelligence development, machine learning, or data science. Typical roles may include AI engineer, business intelligence developer, data analyst or machine learning engineer.

FURTHER STUDY

You might be interested in taking your subject interest further with postgraduate research. The Salford Innovation and Research Centre (SIRC) is home to our Informatics PhD and Research Master’s opportunities in knowledge discovery and semantic web, software engineering, big data, data mining and analytics, cyber security, information visualisation and virtual environments.

Explore our Doctoral School to learn more about research training, support and opportunities.

A taste of what you could become

A machine learning engineer

An AI consultant

A data engineer

A data analyst

A business intelligence developer

And more...

Requirements

What you need to know

APPLICANT PROFILE

Over the next few years, artificial intelligence will have a major impact in many areas of society. We've designed our Artificial Intelligence postgraduate degree course to appeal to recent graduates and experienced industry professionals looking to develop relevant knowledge and open up career pathways in this field.

Our course is recommended for applicants with an undergraduate degree in a computer science, or a related science, technology, engineering or mathematics subject that included programming content. Our course is also relevant to industry professionals who hold or aspire to secure roles in senior management, digital transformation, marketing or information management.

ENGLISH LANGUAGE REQUIREMENTS

All of our courses are taught and assessed in English. If English is not your first language, you must meet our minimum English language entry requirements. An IELTS score of 6.0 (no element below 5.5) is proof of this, and we also accept a range of equivalent qualifications.  

Read more about our English language requirements, including information about pathways that can help you gain entry on to our degree courses. 

Standard entry requirements

Undergraduate degree

The minimum requirement is a second class (2:2) division honours degree or equivalent in a computer science, or a related science, technology, engineering or mathematics subject, which included programming content.

Alternative entry requirements

Accreditation of Prior Learning (APL)

We welcome applications from students who may not have formal/traditional entry criteria but who have relevant experience or the ability to pursue the course successfully.

The Accreditation of Prior Learning (APL) process could help you to make your work and life experience count. The APL process can be used for entry onto courses or to give you exemptions from parts of your course.

Two forms of APL may be used for entry: the Accreditation of Prior Certificated Learning (APCL) or the Accreditation of Prior Experiential Learning (APEL).

For more information about the APL scheme: email enquiries@salford.ac.uk or call 0161 295 4545.

How much?

Type of study Year Fees
Full-time home 2023/24 £9,090per year
Full-time international 2023/24 £15,750per year
Part-time 2023/24 £1,515 per 30 credits

Additional costs

You should consider further costs which may include books, stationery, printing, binding and general subsistence on trips and visits.

International student scholarships

If you are a high-achieving international student, you may be eligible for one of our scholarships. We offer a range of scholarships worth between £3,000-£5,000.

Learn more about our latest international scholarships.

Apply now

All set? Let's apply

Enrolment dates

January 2023

September 2023

January 2024

September 2024

This course is currently closed to international applications.

Read more: information about international application windows