The Year in Data Analytics is run by Kent’s School of Mathematics, Statistics and Actuarial Science and the School of Social Policy, Sociology and Social Research for students already studying at Kent. It offers a great opportunity to develop your understanding of a subject that is revolutionising the way we work.

Why should I add a Year in Data Analytics to my degree?

Data plays a significant role in today’s world, from predicting your shopping habits and personalising your social media feeds, to determining your eligibility to buy a home and influencing our accessibility to healthcare, social care and much more.

Knowing how to understand different datasets is a key skill employers are looking for and demonstrating your knowledge and skills can open many doors for you in your chosen career.

Students who successfully complete the Data Analytics year and their home degree will graduate ‘with a Year in Data Analytics‘. The full transcript of your degree results will include your marks for the Year in Data Analytics, as evidence of your achievement for potential employers.    

Studying the Year in Data Analytics is the best decision I’ve made at uni. If you’re considering it, just go for it! It’s fab!

Scarlett Angel, Biomedical Science

The course

The Year in Data Analytics can be taken either in between Stage 2 and Stage 3 or at the end of Stage 3.

When studying the Year in Data Analytics, you will primarily be taught within the School of Mathematics, Statistics and Actuarial Science (SMSAS) with some modules taught by the School of Sociology, Social Policy and Social Research (SSPSSR). Upon completion of the year, you will return to your home School where you will complete your registered degree.

Successful completion of both the Year in Data Analytics and your registered degree will allow you to graduate with your current degree title augmented with the words ‘with a Year in Data Analytics’.

What you study

In the autumn term, you are introduced to data analytics and the statistical software and techniques used to understand datasets. You also explore the research and applications of quantitative data, and learn how to create and understand your own data.

In the spring term, you explore what Big Data is and look at methods for analysing large datasets. You continue to develop your understanding of data analysis and statistical software, focusing on presenting and communicating results. Towards the end of term, you put into practice the skills and knowledge you have gained by starting work on a project in which you collate, analyse and report on your own data. You hand in your project in the summer term. 

Modules:

This Module will give you the fundamentals of what data analytics means in the real world. You will be introduced to core statistical techniques and data handling using specialist statistical software.  

This module will give you the knowledge and skills required to interpret the results of quantitative research, and to synthesise the diversity of findings on a particular issue.  

This module will further develop your statistical skills and ability to conduct research. You will gain an understanding of how information sources such as opinion polls, research data, social media posts and administrative data are created, and you will be able to create these information sources independently.  

This module builds on the knowledge gained through studying MA5951, introducing you to new statistical models. You’ll learn how to make predictions about the future based on past data using a variety of modelling methods.  

This module focuses on Big Data and text mining. You will discover the techniques used to explore large datasets, as well as gaining key data mining skills.  

During this final taught module you will learn about the different methods for conveying your data findings, and how to tailor your communication style to specialist and non-specialist audiences.  

This module gives you the opportunity to put into practice everything you have learnt over the year. You will work independently to collate and analyse data relating to your chosen project, communicating your findings through a dissertation. A member of staff will support you throughout your project. 

Am I eligible?

Yes, if you are a University of Kent undergraduate student who: 

  • Is currently in Stage 2 or Stage 3 of their degree
  • achieved grade B or above in GCSE Mathematics (or equivalent) and
  • averaged 50% or above in their current degree programme.

Two groups of students are not eligible:

  • students from SMSAS
  • students from the School of Psychology.

If your degree is accredited with a professional body, you will need to confirm with your home Division that this can include the option of a Year in Data Analytics.

What will this cost me?

The Year in Data Analytics should be viewed simply an additional year of study, making a three-year degree into a four-year degree. If you pay your own tuition fees, then you will have to pay for an extra year. For those eligible, student loans should normally be available for all four years. However it is your responsibility to check with the Loan Authority that they will continue to give you financial support on the new programme.  

How to apply

 Applications are open, please fill in the simple application form.  

Application deadlines

For current stage 3 students  - 1st May 2022

For current stage 2 students - 30th June 2022

For more information please contact CEMSYearIn@kent.ac.uk. 

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