BSc Artificial Intelligence with Industrial Experience / Course details

One of the challenges in computing is to make computers demonstrate intelligent behaviour, so that they can solve new problems or cope with the unknown. Current achievements include image and voice recognition, and NASA's Mars Rovers. By combining the study of artificial intelligence and traditional computing techniques with an understanding from psychology of how humans learn, these degree programmes prepare you for a career applying computing in challenging applications.

Artificial intelligence related topics covered include techniques for representing and reasoning about knowledge, including approaches in machine learning in which general patterns are learned from examples. These programmes give you the opportunity to study these techniques, and their application in areas such as computer vision, games, natural language processing and the semantic web.

This is a four year programme and involves you undertaking a one year work placement in industry between the second and third years of your study at Manchester. Besides the money that you earn during this year, you also gain practical experience that can be invaluable both in your final year project and when competing for graduate jobs. Students with industrial experience not only tend to improve their final degree performance but also tend to develop clearer ideas about their future career path.

Detailed programme and course unit information is available here

• Ability to get relevant industrial/business experience as part of the degree programme.
• Allows you to design and develop all aspects of artificial intelligence systems
•  Students can make course unit choices that allow them to change between the Computer Science, Software Engineering, Artificial Intelligence and Distributed Computing programmes at the end of the first year.

At Manchester you will be taught by academic staff who are leading experts in computer science, in a diverse and inclusive learning environment. Teaching and Learning will be delivered using a variety of methods, including: 

• Lectures
• Tutorial classes 
• Practical laboratory sessions
• Group activities
• PASS sessions and peer mentoring 

Some activities will be delivered face-to-face and others online, following a blended learning approach.

The course contains strong practical elements: a year-long group project focused on the design and development of a web application in Year 1; development of software engineering skills through engagement with industrial mentors in Year 2; and a year-long individual project in Year 4. Each year aims to progressively build your skills, knowledge, and confidence in practical computer science.

A typical week in your first year of study will comprise 40 hours of activity, of which approximately 20 hours will be timetabled study and 20 hours will be independent or self-directed study. The timetabled study is a mix of practical and theoretical sessions.

As you progress through the course an increasing emphasis will be placed on independent study, and this reflects you applying your knowledge and skills in substantial individual and group projects. In your third year of study, between 25 and 30 hours each week will typically be independent study. You will be supported by staff through all of your independent study, and this transition to being able to explore your own ideas through project work is an important attribute of a graduate¿computer scientist. 

PASS (Peer Assisted Study Sessions) and Peer Mentoring  

We're proud of our innovative PASS (Peer Assisted Study Sessions) and Peer Mentoring scheme. The PASS scheme provides additional support around the current week's tutorial. It's entirely voluntary and consists of second, third and fourth-year current students helping first years to tackle problems defined by the content of the current tutorial. The emphasis is on showing students how to think about the problems, how to develop problem-solving skills and how to get the most from the educational resources available.   

More about blended learning  

Some of your activity will be synchronous, where you learn live with your lecturer / peers and can interact as appropriate, helping you get support and feel part of a community. At other times it will be asynchronous, where you access materials like presentations, video content, online discussion boards or collaborative documents in your own time (within a framework provided by your programme).   

We believe this blended approach will help each individual study in a way that works best for them and will ensure students receive the best student-experience. 

The course is assessed by a variety of methods, each appropriate to the topic being assessed. These methods include practical exercises, presentations, practical demonstrations, and written and online examinations. You will also have opportunities to monitor your progress using online quizzes and tutorial exercises. 

Todd Davies, BSc Computer Science

I always has the mind-set in my degree that I was learning how to learn. I feel like the BSc in Computer Science gives you a very holistic view of the subject, all the way from logic gates to high-level modules like Computer Vision.

Seb Masaru, BSc Computer Science

The community, the Department, the University, and the city itself are so vibrant in Manchester. You get the sensation that the people here are all extremely approachable.

As you would expect from leaders in the field, we offer some of the most up to date facilities in the world. Amongst the wide range of facilities available to you are:

• Newly refurbished computing labs furnished with modern desktop computers, available with Linux and Windows
• Access to world leading academic staff
• Collaborative working labs complete with specialist computing and audio visual equipment to support group working.
• Over 300 Computers in the Department dedicated exclusively for the use of our students.
• Access to a hardware library, with top of the range equipment, including drones, robots and oculus rifts.