Overview
The Data Intensive Science course from University of Cambridge 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.
Programme Structure
Courses include:
- The taught element comprises two module types; major modules which cover all essential aspects required for scientific data analysis, and minor modules which demonstrate the application of these data science skills to real-world scientific research areas. Candidates will be required to take seven modules in total for assessment comprising 5 major and 2 minor modules.
- The data analysis project will focus on investigating the reproducibility of a key scientific data analysis in the literature. Students will select their project from a pre-approved list in Michaelmas term and will work on it over Lent and Easter terms with submission at the end of the course. The projects will be designed to be open-ended so students can improve or extend what is already published in the literature.
Key information
Duration
- Full-time
- 10 months
Start dates & application deadlines
- Starting
- Apply before
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Language
Credits
Delivered
Disciplines
Data Science & Big Data View 403 other Masters in Data Science & Big Data in United KingdomWhat students do after studying
Academic requirements
English requirements
Student insurance
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- Additional medical costs (i.e. dental)
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- Accidents
- Legal aid
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Other requirements
General requirements
- Applicant’s degree should be in science or a technology discipline, and applicants are expected to demonstrate abilities at an adequate level in mathematics especially in the domain of linear algebra, statistics and probability. Candidates should also demonstrate sufficient training to engage with the scientific content of at least 2 minor modules.
Tuition Fee
-
International
35526 GBP/yearTuition FeeBased on the tuition of 35526 GBP per year during 10 months. -
National
13554 GBP/yearTuition FeeBased on the tuition of 13554 GBP per year during 10 months.
Living costs for Cambridge
The living costs include the total expenses per month, covering accommodation, public transportation, utilities (electricity, internet), books and groceries.
Funding
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Scholarships Information
Below you will find Master's scholarship opportunities for Data Intensive Science.
Available Scholarships
You are eligible to apply for these scholarships but a selection process will still be applied by the provider.
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