MSc Mathematics and Data ScienceUniversity of Stirling
MSc Mathematics and Data Science
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MSc Mathematics and Data Science
The field of Data Science has seen rapid growth in recent years, with vast amounts of data now being generated by major companies and service providers.
At the same time, it’s recognised that there’s a shortage of qualified analysts, both in the UK and globally, to make the most of this data. Crucially, there’s now a shortage of mathematics graduates with the data analysis skills needed to meet the demands of industry.
Yet, there is a recognised shortage of qualified analysts, both in the UK and globally, to make the most of this data. In particular, the demand is for graduates who can both manage the data (the computing skills), and analyse the data to extract patterns, build models and make predictions (the mathematics skills). It is only with these analytical skills can the full value of data be extracted.
The COVID-19 pandemic has shown the importance of combining Data Science and Mathematics, with governments around the world being guided by predictions from mathematical models. Our MSc is one of the first courses to link these two key areas, making it uniquely positioned to help you meet this demand.
The course will provide you with a strong foundation in the mathematical analysis of data-driven systems and help you develop your computing skills, including Artificial Intelligence and Machine Learning, to apply the techniques you learn on a large scale. You’ll learn the techniques used to approach data using computational analysis and understand the mathematics underpinning these techniques. The key outcome of this course is to ensure you are confident in your skills before you contunue your career.
Stirling is a member of The Data Lab, an Innovation Centre that aims to develop the data science talent and skills required by industry in Scotland. It facilitates industry involvement and collaboration, and provides funding and resources for students.
A minimum of a second class Honours degree, or equivalent, in a numerate subject, e.g. mathematics,physics, engineering, economics; along with some evidence of a mathematical background, such ashaving taken and passed mathematics modules in at least some of calculus, algebra, statistics andnumerical analysis.
Applicants with a mathematics degree (including a joint mathematics degree) will beaccepted.
English language requirements
If English is not your first language you must have one of the following qualifications as evidence of your English language skills:
- IELTS Indicator 6.0 with a minimum of 5.5 in each sub-skill
- Cambridge C1 Advanced (CAE) 169 overall with a minimum of 162 in each sub-skill
- Cambridge C2 Proficiency (CPE) 180 overall with a minimum of 162 in each sub-skill
- Pearson Test of English (Academic) 60 overall with a minimum of 59 in each sub-skill
- IBT TOEFL 78 overall with a minimum of 17 in listening, 18 in reading, 20 in speaking and 17 in writing
- IBT TOEFL Special Home Edition Test 78 overall with a minimum of 17 in listening, 18 in reading, 20 in speaking and 17 in writing
- TOEFL ITP Plus for China minimum 543 overall, 54 in listening, 53 in structure and written expression, 56 in reading and B2 in speaking
- Trinity ISE II Pass overall with a Pass in each sub-skill, ISE III Pass overall and in all sub-skills, ISE IV Pass overall and in all sub-skills
- Aptis (4 skills) CEFR B2 overall and B2 in all sub-skills
- Duolingo 95 overall with a minimum of 90 in all sub-skills
- LanguageCert International ESOL B2 Communicator - Pass with minimum 33 in each sub-skill
For more information about admission requirements, please visit the university website.
Does this course require proof of English proficiency?
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The course covers:
- statistical analysis techniques for small and large datasets
- data analysis and modelling using R, Matlab and Python
- building and analysis of mathematical models of real-life systems
- mathematical analysis of data networks, e.g. social media networks
- analytical optimisation and computer-based search algorithms, including Artificial Intelligence
- data analytics and machine learning
- relational and non-relational databases
- cluster computing
Scholarships & funding
Several scholarship options are available. Please check the university website for more information.
Mode of study: part-time, full-time, campus based, stand-alone modules
- Course fee for UK students: £9,350
- Course fee for EU students: £20,845
- Course fee for Overseas students: £20,845
Award: Masters / MSc, Postgraduate Diploma, Postgraduate Certificate
On successful completion of the MSc Mathematics and Data Science, you'll be able to:
- analyse and solve real-world problems using different mathematical and computational approaches
- expand mathematical methods to approach more complex problems
- be competant in industry-relevent programming languages, including R, Python and Matlab
- demonstrate skills in data analytics, machine learning and Artificial Intelligence (AI)
- analyse small and large-scale data sets using mathematical and computational approaches
- be confident in your own research and data science skills through real-life based projects
Graduates from a data science course find employment as:
- R&D data scientist
- digital analytics engineer
- data engineer
- data scientist
- machine learning engineer
- machine learning data scientist
- data solution architect
- machine learning developer
- data scientist in a research field such as genomic, cognitive, clinical and healthcare
About this institute
University of Stirling
The University of Stirling is an international university committed to helping students make a difference in the world. We’re passionate about creating impact in everything we do - addressing real societal issues, providing solutions, and helping to shape communities. Based...
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