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The course responds to the growing:
- demand for highly trained research scientists to design and implement data analysis pipelines for the increasingly large and complex data sets produced by the next generation of scientific experiments;
- societal demand for data science and data analysis skills in the industry, especially when applied in strategic domains (science, health) and economic areas (finance, e-commerce);
- need to train postgraduate students with a deep understanding of data science techniques and algorithm building for modern computer architectures and utilising industry best practices for software development;
- importance of open science in research, specifically reproducibility of scientific results and the creation of public data analytic codes.
Learning Outcomes
By the end of this course, students will have:
- thorough knowledge of statistical analysis including its application to research and how it underpins modern machine learning methods;
- comprehensive understanding of data science and machine learning techniques and packages and their application to several practical research domains;
- developed advanced skills in computer programming utilising modern software development best practices created in accordance with Open Science standards;
- demonstrated abilities in the critical evaluation of data science tools and methodologies for their real-world application to scientific research problems.
Continuing
Students wishing to progress to PhD study after passing the Masters degree should apply for admission to a PhD through the University admissions website, taking the funding and application deadlines into consideration.
Open Days
The Department of Physics and other MPhil participating Departments contribute to the University of Cambridge's Postgraduate Open Day.
The University hosts and attends fairs and events throughout the year, in the UK and across the world. We also offer online events to help you explore your options:
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Discover Cambridge: Master’s and PhD study webinars - these Spring events provide practical information about applying for postgraduate study.
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Postgraduate Virtual Open Days - taking place in November each year, the Open Days focus on subject and course information.
For more information about upcoming events visit our events pages.
Departments
This course is advertised in the following departments: