Artificial Intelligence - MSc
This course will create graduates with a sound understanding of the theory and practice of AI in industry. As a conversion course we will assume all students are starting fresh with no experience of computer programming and little experience of using mathematics or statistics in their undergraduate programmes or in work....
This course will create graduates with a sound understanding of the theory and practice of AI in industry. As a conversion course we will assume all students are starting fresh with no experience of computer programming and little experience of using mathematics or statistics in their undergraduate programmes or in work.
What's covered in the course?
We will begin by creating a foundation in programming and mathematics upon which we will build the expertise in several key areas of artificial intelligence, going from your first Python code and basic algebra right through to Deep Learning. The core applied areas of data science that will be taught will include:
- Data Visualisation and Interpretation - Analysis that can’t be properly interpreted, explained and understood is a waste of time from a commercial point-of-view. We will teach you how to generate attractive and interpretable visualisations and tell the story of whatever data you’re working with to a range of audiences.
- Image Analysis - Machine learning has shown incredible results recently in understanding the themes of images and video which are being applied in a range of commercial settings; from security and driverless cars, to online clothes shopping.
- Natural Language Processing - Being able to understand speech and text is one of the cornerstones of artificial intelligence systems. Chatbots built on AI are appearing all over the internet, but more than this technology giants are searching for ways that machines can have detailed conversations with one-another and to be able to read and understand text documents.
- Time Series - Dealing with dynamic data is vital to AI systems in finance, AI and defence; whether predicting the future of stock prices to predicting patient outcomes in ICU and how a virus outbreak will permeate through a population.
A strong focus on technology monitoring and ethics will be taught in a way to suit learners from all backgrounds. The masters’ project will have an industrial route for learners who want to work on an applied project with a corporate partner and there will be a route for graduates to undertake a professional placement or to go on to a doctoral research programme. If you have any further questions please get in touch with the course leader, Iain Rice, at email@example.com.
MSc AI course leader, Iain Rice, shares why it is an exciting time to become an AI specialist and what’s covered in the course. Watch the video and find out how you can convert into an AI specialist.
Why Choose Us?
- Become an AI specialist - No matter your background, this course will prepare you to work in any area of data science competently with AI, you head and shoulders above everyone else in the graduate AI job market.
- Learn how to evaluate machine learning systems - Our course teaches you how to account for both the limitations and ethical issues that they create.
- Links with industry - Our delivery partners, such as Amazon, Huawei, Cisco, IBM and Microsoft will provide training for industry-standard systems making you able to solve problems important to your future employers, straight away.
- Scholarship Opportunities - You could have your course fees paid for with the £10,000 OfS funded scholarship if you are a female, black or disabled student. Contact firstname.lastname@example.org for more details.
- Flexible learning - You will be taught through a mix of face-to-face and remote learning to fit around other commitments.
On graduation there are three main routes open to you:
- A job in industry as a data scientist; solving tomorrow’s problems using the intelligent techniques that we will provide you with
- A PhD; pushing the forefront of AI by developing new types of intelligent systems to solve the most challenging data-driven problems
- Where you started; AI is being applied everywhere so going back to your own industry on graduation isn’t taking a step back – you’ll be returning with a broad set of skills and a problem-solving outlook that will benefit any organisation
2:2 honours degree or higher in any discipline. IELTS (standard level) if degree was not delivered in English.
3+ years professional work experience(standard definition any role which has required you to work & interact with a range of people requiring a regular element of problem-solving)
On application please also provide a 250-word maximum personal statement detailing why you are ready for this course and how you want to use what you learn in your future career or in later life.
Following the application anyone meeting the above criteria will be contacted by the admissions team to arrange a short interview lasting approximately 15 minutes with the course leader or a representative. Following this you will receive one of the following:
Fees & How to Apply
- UK students
- International students
Access to computer equipment
You will require use of a laptop, and most students do prefer to have their own. However, you can borrow a laptop from the university or use one of our shared computer rooms.
You will receive £5 print credit in each year of your course, available after enrolment.
All essential field trips and associated travel costs will be included in your course fees.
Access to Microsoft Office 365
Every student at the University can download a free copy of Microsoft Office 365 to use whilst at university and for 18 months after graduation.
You will be able to download SPSS and NVivo to your home computer to support with your studies and research.
Subscriptions to key journals and websites are available through our library.
Free access to Rosetta Stone
All students can sign up to the online learning language platform for free through the Graduate+ scheme.
Media consumable items (optional)
This course requires the use of consumables.
Excess printing (optional)
Once you have spent your £5 credit, additional printing on campus costs from 5p per sheet.
All module key texts will be in the University library, but in limited numbers. You may choose to purchase a copy.
Placement expenses (optional)
If you choose to undertake a placement, you'll need to budget for accommodation and any travel costs you may incur whilst living or working away from home.
Professional Placement option*
The Professional Placement option will allow you to complete a credit bearing, 20 week Professional Placement as an integral part of your Master’s Degree. The purpose of the Professional Placement is to improve your employability skills which will, through the placement experience, allow you to evidence your professional skills, attitudes and behaviours at the point of entry to the postgraduate job market. Furthermore, by completing the Professional Placement, you will be able to develop and enhance your understanding of the professional work environment, relevant to your chosen field of study, and reflect critically on your own professional skills development within the workplace.
You will be responsible for finding and securing your own placement. The University, however, will draw on its extensive network of local, regional and national employers to support you in finding a suitable placement to complement your chosen area of study. You will also benefit from support sessions delivered by Careers+ as well as advice and guidance from your School.
Placements will only be confirmed following a competitive, employer-led selection process, therefore the University will not be able to guarantee placements for students who have registered for the ‘with Professional Placement’ course. All students who do not find a suitable placement or do not pass the competitive selection process will be automatically transferred back to the standard, non-placement version of the course.
Students are required to submit a personal statement as part of their application for this course.
Your postgraduate personal statement is going to shine a light on your personal experience, academic success, personal skills and any other factors that will support your application for further study.
Here are the key areas you’ll need to address:
Your passion and motivations
Studying a postgraduate course usually means you want to specialise in something. So what’s driving you?
Why this course?
Show that you’ve researched the course offering. What is it about this particular course that appeals to you? Is it the lecturers? The modules? Etc.
What makes you a good postgraduate candidate?
Tutors want to know that you can handle postgraduate study, so show them how your undergraduate experiences or work life has equipped you for a more advanced level of study. Key areas to address are research and group work but this can vary depending on your chosen course.
Relevant academic or work experience
Add anything relevant that relates back to your chosen course and shows how your skills will contribute towards your learning. What extra-curricular activities have you taken part in? What awards have you won? What employment or voluntary experience do you have that has helped you develop transferable skills? How do these specifically relate to the course you are applying for?
You should also mention your future plans and how a postgraduate qualification fits in. Try to look beyond your postgraduate study – do you plan to jump straight into a specific career or follow your studies with a research degree? Lastly, use plain, professional English and, where possible, utilise the language of your chosen industry.
Get more information on writing personal statements.
Course in Depth
In order to complete this course a student must successfully complete all the following CORE modules (totalling 180 credits):
Computing proficiency is essential in modern data science and a firm grounding is required before the more technical themes of Artificial Intelligence (AI) can be studied. This is the introductory module for the programme where no prior computational foundations are assumed. A holistic view of computing will be provided covering the important themes of data management, programming and security considerations. The module will start from principles of data structures and algorithms, using Python for implementations, which will then be applied to database structures, both SQL and NoSQL, enabling learners to construct programs using standard industrial practices.
The aim of this module is to identify, apply and design data visualisations. The module provides you with the fundamental principles and practice-based activities needed to design data visualisations for both different contexts, and different types of data. More advanced visualisation concepts and tools for analysing multi-dimensional data and large data sets will also be examined and appraised. You will learn how to employ visualisation as a tool that can help users understand large and complex data sets, conveying the outputs to a diverse audience.
Artificial Intelligence (AI) is a core component of computer science, aiming at developing intelligent agents that mimic human’s cognitive capability in learning, reasoning, and problem-solving. As a branch of AI, machine learning (ML) allows to learn and adapt (from examples), rather than being explicitly programmed for a particular outcome. This module will offer you the statistical grounding required by data scientists to construct and evaluate the effectiveness of AI systems. Probability theory and statistical evaluation will lay the foundations to be used in a range of real-world scenarios. Standard machine learning techniques for regression, clustering and classification will be covered in this module. You will develop the practical skills needed for applied machine learning including the use of existing tools and techniques needed to solve industry-standard problems based on use cases extracted from real domains.
Following a series of breakthrough developments starting in 2006 the field of Deep Learning has attracted interest from a range of fields and is now receiving billions of pounds of investment across the world. Harnessing these techniques can leverage insight into problems not previously recognised. This module will contrast the application domain-specific methods from the Applied AI module with a set of generalised Deep Learning machines to show how they are applied to unstructured data. In particular, the module will teach you how to attack image analysis, natural language and reinforcement learning problems with these models whilst critically analysing the costs and benefits of implementation.
Artificial Intelligence (AI) is expected to transform the way we humans live and work helping us to solve complex problems and live more enriched lives. From healthcare to finance, AI now impacts nearly every industry through dramatically improving the efficiencies of workplaces and expanding the capabilities of the work humans can do. When AI takes over repetitive or dangerous tasks, minimises occurrences of ‘human error’ or support decision making, it frees up the human workforce to do work they are better equipped for; tasks that involve creativity and empathy among others. This module will discuss the impact of AI with focus on AI project life cycles, horizon scanning, AI ethics and AI applications.
Modern artificial intelligence (AI) has become popular primarily because it can deal with data of various kinds. The ability to handle this data arises thanks either to the pre-processing that makes the data amenable for subsequent analysis/modelling, and/or to the nature of AI algorithm itself. Over the past half-century a range of different algorithms and approaches have been designed to handle structured data challenges in areas such as time series prediction, natural language modelling and image analysis. In this module you will be taught the targeted ways in which inferences can be made in these domains motivated with real-world projects. In addition to this you will be given a grounding in optimisation of parametric models and subsequent feature selection will be given to identify optimal tools for data analysis.
The purpose of the module is to enable you to undertake a sustained, in-depth and research-informed project exploring an area that is of personal interest to you. In agreement with your supervisor, you will decide upon your topic which will take the form of a practical outcome (artefact) with accompanying contextual material. This can be oriented towards any area of AI and there is the opportunity for an industrial project run in co-operation with one of our partner organisations.
Knowledge and understanding are acquired though a mixture of formal lectures, tutor-led seminars and practical activities, with other independent learning activities at all stages. For more information about this course please get in touch with the course leader, Iain Rice, at email@example.com.
Course Leader, Iain Rice, provides a detailed overview of the different modules covered on the course and how they will be delivered. As a conversion course, the programme is designed to ensure all students understand the fundamentals, before going on to develop highly sought after digital skills.
Enhancing your employability skills
We know that employers are looking for graduates who have a good balance between in-depth academic knowledge and technical and practical expertise, which is why our course is geared towards employability.
What you learn on our course will help you to stand out when you look for your first professional role. Because you will know how to use sophisticated, industry-standard software, you will be able to demonstrate that you can put into practice your deep theoretical knowledge.
We will also prepare you for a career by equipping you with a range of transferable skills, such as complex problem-solving expertise, the ability to analyse in a careful and considered manner, and working as a team member. We aim to have you employer-ready by the time you graduate and, as part of your Advanced Computer Science course, we will invite guest speakers to underpin the subjects taught.
Thanks to our excellent partnerships and working relationships with some of the UK’s leading companies, you have the chance to network with leading organisations such as IBM, Dignity plc, Mortgage Brain and Griffiths Waite. In addition, our specialist industry links with the Linux Professional Institute, the Oracle Academy, Cisco, and Microsoft, plus our world-class facilities, will mark you out as a highly employable graduate.
This is why our graduates have gone on to pursue computing and software development and designer careers in a wide range of industries, from SME software companies, to industry, government, banking and healthcare. Furthermore, many graduates continue their studies to Doctorate level.
OpportUNIty: Student Jobs on Campus ensures that our students are given a first opportunity to fill many part-time temporary positions within the University. This allows you to work while you study with us, fitting the job around your course commitments. By taking part in the scheme, you will gain valuable experiences and employability skills, enhancing your prospects in the job market.
It will also allow you to become more involved in University life by delivering, leading and supporting many aspects of the learning experience, from administration to research and mentoring roles.
Birmingham City University is a vibrant and multicultural university in the heart of a modern and diverse city. We welcome many international students every year – there are currently students from more than 80 countries among our student community.
The University is conveniently placed, with Birmingham International Airport nearby and first-rate transport connections to London and the rest of the UK.
Our international pages contain a wealth of information for international students who are considering applying to study here, including:
Facilities and Staff
We are constantly investing in our estate and are currently in the process of spending £340 million on new learning facilities. This course will be taught at Millennium Point at the City Centre Campus.
As a student at the School of Computing and Digital Technology, you have access to networked laboratories equipped to industry standards and running the latest software, giving you the best possible introduction to the technologies you will encounter in the world of work.
Dedicated facilities are provided for systems analysis, computer networks, programming in a wide range of languages, artificial intelligence, modelling and visual programming, e-commerce and .net environments, and business intelligence, as well as supporting the application areas of mechatronics, games technology, electronics and computer forensics.
The laboratories are well-equipped for all our computer networking courses, as well as specialist areas for practical work such as voice-over internet protocol (VoIP), forensic and ethical hacking technologies, wireless and mobile technologies and radio frequency identification technologies to name but a few.
Software development and computer programming
There are a number of open access, software development and computer programming
laboratories that can be used to develop systems and programmes, including database management systems such as MySQL, to name but a few.
Our embedded systems laboratories are used to develop real-time systems, such as specialist hardware training and development resources, and industrial-standard software development and simulation tools. These include microcontroller software and robotics design and development, to name but a few.
Electronic systemsTo underpin the basic principles of electronic systems, we have a well-equipped laboratory of general and specialist test and measurement kits, including powered prototyping development boards, dual power supplies, frequency generators and counters and digital multi-meters to name but a few.
Our successful development of forensic computing has led to a specialist forensics laboratory that is fully equipped with essential hardware and software for this sensitive area of study. The laboratory includes high-spec PC’s with built-in multi interface Tableau write blockers, EnCase and FTK computer forensic software and steganography detection and analysis software, to name but a few.
Dr Iain Rice
Dr Rice is a specialist in Machine Learning and Signal Processing with several years of experience applying AI models to a wide range of real-world problems. As the head data scientist for The RAPID Project Iain created algorithms allowing for up to 12 hours advanced prediction of cardiac arrest in children.
Iain has taught on several computational and mathematical programmes at both traditional and distance learning universities. As the course leader for the MSc Artificial Intelligence he is passionate about seeing everyone learn more about AI and mathematics, especially those from a non-computing background.
Iain’s PhD was in the area of applied mathematics where he worked with Thales (UK) Ltd, a defence contractor, to analyse SONAR data. He created visual informatics capable of inferring anomalies in a complex environment. Whilst working on this problem he created a novel computational architecture capable of outperforming standard Deep Learning models and is a self-proclaimed ‘deep learning sceptic’.
Dr Rice is open for applications of self-funded PhD projects, MSc research projects, industry collaborations and general academic partnerships pertaining to applied Machine Learning and data-driven challenges.More about Iain