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+995 596 96 11 22
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University of Bradford
Applied Artificial Intelligence and Data Analytics
Study detals
: Master's degree : MSc (Hons) Applied Artificial Intelligence and Data Analytics : Full time : 12 MonthRequirements
Entry requirements
The entry requirement for a postgraduate taught course is typically equivalent to a UK Second Class Honours Second Division (2:2).
The table below shows how the University equates qualifications from your country to UK degree classifications
| Qualification | UK 1st Class | UK 2:1 | UK 2:2 |
|---|---|---|---|
| Bachelor degree | 4.5/5.0 or 81% |
4.0/5.0 or 71% |
3.5/5.0 or 66% |
| Specialist Diploma |
4.5/5.0 |
4.0/5.0 or 71% |
3.5/5.0 or 66% |
Speciality
Sandwich course fees - charged during the placement year away from the University of Bradford for students on thick sandwich courses, or during the year in which the second placement falls for students on thin sandwich courses. Students charged at 10% of the equivalent full-time fee.
If a placement year is to be undertaken abroad and supported by University funding through the University’s exchange programmes, fees will increase to 15% of standard fees to cover additional support, advice and administration costs.
Additional information
Degree Overview
This MSc course has been designed in response to the shortage of Artificial Intelligence (AI) and Data Analytics (DA) specialists in the UK. It will give you the skills and professional insight you need to launch a career in these diverse and fast-growing sectors.
This course will provide you with an applied understanding of Artificial Intelligence and Data Analytics. And suitable for applicants from all backgrounds and no prior technical knowledge is required. You will develop the relevant technical skills you need as part of the course.
Technical skills you will develop include knowledge in applications such as, Python, R, AWS, MS Azure, SAS, SPSS, and Excel. Non-technical soft skills, the development of which are key to your long-term success in any industry, include data-driven decision-making, critical thinking, business acumen and entrepreneurship, and communication, teamwork and leadership skills.
You will graduate as a confident, creative, enterprising, independent data modeller and interpreter, able to select appropriate AI and DS tools for a given practical problem and perform empirical analysis that feeds into data-driven decision-making.
