Postgraduate Studentships - Search for funding opportunities.
Postgraduate Studentships - Search for funding opportunities.
Study Details: Online across 24 or 36 months, part-time with both September and January entry points.
Our online MSc in Applied Statistics with Data Science is a conversion course, offering the opportunity to develop skills in statistics and data analysis even if you’ve never studied statistics before. You’ll be supported through this part-time programme by members of staff who work directly with industry to develop skills which are relevant to current areas of research including population health and medicine, animal and plant health, finance and business. You’ll gain skills in:
The course is entirely delivered online. The course is ideally suited to those working full-time or with other commitments. You can study and complete the modules when it’s most convenient for you – you don’t need to be online at specific times.
Minimum second-class (2:2) Honours degree or overseas equivalent.
Mathematical training to A Level or equivalent standard.
Prospective students with relevant experience or appropriate professional qualifications are also welcome to apply.
For Australia and Canada, normal degrees in relevant disciplines are accepted.
For fees and funding options, please visit website to find out more
The online MSc in Applied Statistics with Data Science will provide graduates with skills in the statistical analysis of big data. These skills are required by many employers in sectors such as:
Compulsory classes
Foundations of Probability & Statistics
Data Analytics in R (20 credits)
Statistical Modelling & Analysis (20 credits)
Big Data Fundamentals (10 credits)
Big Data Tools & Techniques (10 credits)
Research project (60 credits)
Elective classes
You're required to take 40 credits of elective classes.
Data dashboards with Rshiny (10 credits)
Quantitative Risk Analysis
Survey Design & Analysis (10 credits)
Financial Econometrics
Financial Stochastic Processes
Medical Statistics (20 credits)
Effective Statistical Consultancy (10 credits)
Bayesian Spatial Statistics (10 credits)
Machine Learning for Data Analytics (20 Credits)
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