Data Analysis (T42)
Open University
UCAS Code: Not applicable | Certificate of Higher Education - CertHE
Entry requirements
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About this course
Computing and data analysis play an important role in almost all private and public sector employment. The need to understand how to use IT and data to inform business decisions has never been more important. This qualification introduces you to some basic skills in exploring and analysing data sets and solving practical problems using mathematics, statistics and computing. It forms a foundation for further study or employment in the fields of mathematics, statistics, computing or data science.
**Key features of the course**
- Introduces mathematical, statistical and computing techniques.
- Covers basic use of a range of appropriate software, including writing code in the Python language.
- Provides experience of carrying out data analysis and commenting on the results.
- Builds a solid foundation on which to continue on to a higher qualification in data science or employment in a wide range of sectors, including finance, government, health, education, the voluntary sector, business and commerce.
Modules
This certificate of higher education has one stage, comprising 120 credits:
You’ll study four 30-credit modules.
What students say
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After graduation
We don't have more detailed stats to show you in relation to this subject area at this university but read about typical employment outcomes and prospects for graduates of this subject below.
What about your long term prospects?
Looking further ahead, below is a rough guide for what graduates went on to earn.
Information systems
The graph shows median earnings of graduates who achieved a degree in this subject area one, three and five years after graduating from here.
£31k
£38k
£39k
Note: this data only looks at employees (and not those who are self-employed or also studying) and covers a broad sample of graduates and the various paths they've taken, which might not always be a direct result of their degree.
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Post-six month graduation stats:
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Graduate field commentary:
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The Longitudinal Educational Outcomes dataset combines HRMC earnings data with student records from the Higher Education Statistics Agency.
While there are lots of factors at play when it comes to your future earnings, use this as a rough timeline of what graduates in this subject area were earning on average one, three and five years later. Can you see a steady increase in salary, or did grads need some experience under their belt before seeing a nice bump up in their pay packet?
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