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MSc Data Science and Artificial Intelligence

  • Delivery:
    Full time according to Funding Council definitions, Part-Time, Sandwich (Thick) out of college.

Our MSc Data Science and Artificial Intelligence provides you with most advanced knowledge, methods and processes as enablers for deploying data science and artificial intelligence based solutions to real-world problems. In particular, this degree emphasises on various investigative data science and artificial intelligence based approaches, which apply to the security, environment, human behavior understanding, transport, health, smart cities domain sectors and more.  

You will specifically learn about recent advances in the fields of data analytics, big data tools and technologies, machine intelligence while concretely experimenting on machine knowledge extraction and decision-support. 

You will graduate with important skills in strategic thinking, for scientific research implementation and communication. This is in addition to the theoretical and practical skills which are needed for the efficient implementation of data science and artificial intelligence based projects.

We also have established close relationships with companies, research and government agencies that are interested in recruiting skilled graduates in data science and artificial intelligence.Through these relationships we have organised codejams/hackathons where you will have the opportunity to visit such organisations for a specific period of time and work on interesting and practical data science and artificial problems. This approach will support you for establishing an internship or placement during your course.

We use a broad range of data science tools and technologies, from those which are established in industry and academia for many years (e.g. MATLAB, R and Weka), to the new favourites which prepare you for mainstream data science jobs currently (e.g. Python, Jupyter notebook, Apache Spark and libraries such as Keras, TensorFlow, and PyTorch).

We teach a number of core units and offer modern and popular subjects as options, such as Blockchain and Digital Features, which will give you a competitive edge when entering the job market.

Key information

Next start date:

September 2020, January 2021, September 2021

Location:

Bournemouth University, Talbot Campus

Duration:

1 year full-time or 2 years with a 30-week placement (September start), 18 months full-time or 30 months with a 30-week placement (January start), 2 years part-time

Required subjects:

Computing, Technology, Maths, Physics, Engineering, Data Sciences or Data Analytics

Entry requirements:

A Bachelors Honours degree with 2:2 in a required subject, or equivalent.

International entry requirements:

If English is not your first language you'll need IELTS 6.0 (Academic), with a minimum of 5.5 in each component. For more information check out our full entry requirements.

Course details

Details of the assessment methods and contact hours for each unit of the course can be found in the programme specification.

Download the programme specification (pdf 271 kb)

Placement opportunities

An exciting and valuable part of your studies with us is the opportunity to gain valuable experience through full-time paid industrial placements, for a minimum of 30-weeks.

Find out more about placements for postgraduate students

Your application

Entry requirements

Careers

Upon completion of this course, you will possess the practical skills and theoretical knowledge necessary to enter fields within data science and artificial intelligence. 

Costs and fees

You can find full information about the deposits required and how to pay your fees in our postgraduate fees and funding section, including details of the Postgraduate Loan (subject to fee status).

All fees are quoted in pounds sterling and are per annum. Fees quoted are for tuition only unless stated otherwise. Your tuition fees will be the same for each year of your course.

Find out more about living expenses for postgraduate students

Our staff

On this course you will be taught by staff with relevant expertise and knowledge appropriate to the content of the unit. This could include senior academic staff, qualified professional practitioners and research students, many of whom are actively engaged in research and/or professional practice which is integrated into the teaching of this course. Please note that teaching staff can change.