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Statistics with Machine Learning (Taught)

1 Study option Ā· PostgraduateUniversity Park Campus

Course summary

Are you considering a career as a professional statistician in industry? Do you want to follow a career in machine learning?

This course will provide you with the necessary advanced knowledge and skills. This masters course differs from the Statistics MSc, by providing a particular focus on statistical machine learning to help you understand and build methods that are used in everyday life. For instance, machine learning algorithms are used in mobile phones, self-driving cars, digital health, protein engineering, adaptive clinical trials and lifelong learning in robotics.

Well-qualified statisticians and data scientists are in demand world-wide as the amount of digital data we generate increases. Employment opportunities are broad in sectors such as:

  • pharmaceuticals

  • finance

  • computing and AI

  • business analytics

  • healthcare

  • government policy

  • social media and technology

Course structure

In the Autumn semester you will study the core fundamentals of statistics and data science. This will provide the basis for the optional modules. This will provide a firm foundation in statistical machine learning for the Spring semester which includes optional modules covering topics in time series and multivariate statistics.

You will develop advanced statistical techniques. This will enable you to test theories, learn how to interpret large and complex data, and to extract relevant insights from it. The masters will enable you to develop computing skills in using R too. The course can lead to careers in data science, healthcare and the digital economy.

In the summer you'll complete a dissertation. This will be in collaboration with staff from the school's internationally recognised Statistics and Probability Section, or one of our industry partners, such as Capital One.

Please note: this is the proposed course structure for 2025, the modules are currently being finalised so please check here or contact the Course Director before submitting your application.

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