Computer Science for Artificial Intelligence (with Integrated Foundation Year)
University of Bradford
UCAS Code: I182 | Bachelor of Science (with Honours) - BSc (Hons)
University of Bradford
UCAS Code: I182 | Bachelor of Science (with Honours) - BSc (Hons)
Entry requirements
A level
To include GCSE Mathematics at grade C/grade 4, plus GCSE English at grade D/grade 3 or equivalent English qualification
Pearson BTEC Level 3 National Extended Diploma (first teaching from September 2016)
To include GCSE Mathematics at grade C/grade 4 OR BTEC Extended Diploma (2010-2016) Any Engineering subject to include Mathematics for Engineering Technicians (Unit 4) at Pass OR BTEC Extended Diploma (2010-2016) Construction and the Built Environment to include Mathematics in Construction and the Built Environment (Unit 3) at Pass OR BTEC Extended Diploma (2010-2016) Applied Science to include Mathematical Calculations for Science (Unit 7) and Using Statistics in Science (Unit 8) OR BTEC Nationals Level 3 (from 2016) Any Engineering subject to include Calculus to Solve Engineering Problems (Unit 7) at Pass AND GCSE English at grade D/grade 3 or equivalent
72 UCAS tariff points to include SQA National 5 grade C in Mathematics and grade D in English
UCAS Tariff
72 UCAS tariff points to include 1 GCE Advanced Level or an equivalent qualification and GCSE Mathematics at grade C/grade 4, plus GCSE English at grade D/grade 3 or equivalent English qualification
About this course
Artificial Intelligence is an exciting and world-changing subject with applications and impact that can affect the day to day lives of billions of people. From human-like AI bots that can understand our language to provide support and information instantly, to autonomous robots and software agents that can perform repetitive or hazardous tasks in both the physical and digital worlds. Artificial Intelligence is built around a backbone of Computer Science topics, combining problem solving skills, practical approaches like programming and domain specific expertise such as predictive modelling and natural language processing.
On this course you will benefit from our more than 50 years of experience in teaching Computer Science. You will learn how to combine a diverse set of skills from a variety of topics into real-world applications through our industry focussed curriculum, and benefit from a fully BCS accredited course to graduate with CITP status (subject to application and approval from BCS, The Chartered Institute for IT).
You will study topics such as computer programming, web technologies, databases, software development, as well as a variety of exciting and specialised topics in artificial intelligence, machine learning, natural language processing, intelligent systems and more. Our degree course will challenge you to apply these topics to meaningful real world problems, helping you to launch your future career through practical experience and the knowledge that industry is demanding.
**Professional Accreditation**
The BSc (Hons) in Computer Science is accredited by BCS, The Chartered Institute for IT for the purposes of fully meeting the academic requirement for registration as a Chartered IT Professional.
Modules
Foundation Year: Foundation Mathematics 1 (core) Foundation Mathematics 2 (core) Foundation Mechanics (core) Foundation Physics (core) Fundamentals of Materials (core) Information and Communication Technology (core)
Assessment methods
Most modules use a mixture of formal lectures, practical lab sessions, tutorials and seminars. Some modules involve supervised group work, usually with an assigned academic staff member for each group. All modules require students to undertake independent study, supported through distance learning technologies such as our Virtual Learning Environment. Reading lists and suggested resources for independent study provide further direction for students to undertake this work, and regular contact hours and informal feedback throughout the courses provide opportunities for further guidance for learners. Assessments for modules mostly take the form of practical coursework, lab tests and written exams, with all forms being well represented throughout all years of the course across all modules
Tuition fees
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The Uni
University of Bradford
School of Computer Science, AI and Electronics
What students say
How do students rate their degree experience?
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Artificial intelligence
Sorry, no information to show
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Who studies this subject and how do they get on?
Most popular A-Levels studied (and grade achieved)
After graduation
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Artificial intelligence
What are graduates doing after six months?
This is what graduates told us they were doing (and earning), shortly after completing their course. We've crunched the numbers to show you if these immediate prospects are high, medium or low, compared to those studying this subject/s at other universities.
Top job areas of graduates
Artificial intelligence is a very specialist subject taken by less than 100 people a year at the moment, so there is little reliable information available on graduate prospects - bear that in mind when you review the stats above. Graduates taking this type of subject are more likely than other computing graduates to go into further research. However, if you want to find out more specifically about the potential graduate outcomes of a specific course, it's a good idea to go on open days and talk to tutors about what previous graduates have gone on to do.
What about your long term prospects?
Looking further ahead, below is a rough guide for what graduates went on to earn.
Artificial intelligence
The graph shows median earnings of graduates who achieved a degree in this subject area one, three and five years after graduating from here.
£22k
£23k
£29k
Note: this data only looks at employees (and not those who are self-employed or also studying) and covers a broad sample of graduates and the various paths they've taken, which might not always be a direct result of their degree.
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You can use this to get an idea of who you might share a lecture with and how they progressed in this subject, here. It's also worth comparing typical A-level subjects and grades students achieved with the current course entry requirements; similarities or differences here could indicate how flexible (or not) a university might be.
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Post-six month graduation stats:
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It offers a snapshot of what grads went on to do six months later, what they were earning on average, and whether they felt their degree helped them obtain a 'graduate role'. We calculate a mean rating to indicate if this is high, medium or low compared to other universities.
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Graduate field commentary:
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The Longitudinal Educational Outcomes dataset combines HRMC earnings data with student records from the Higher Education Statistics Agency.
While there are lots of factors at play when it comes to your future earnings, use this as a rough timeline of what graduates in this subject area were earning on average one, three and five years later. Can you see a steady increase in salary, or did grads need some experience under their belt before seeing a nice bump up in their pay packet?
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