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Personal statement - reason to take the specialization: boost my career vs problem to solve



evita126 1 / -  
May 30, 2021   #1
Hi there! I am planning to apply to some universities in the UK for a master's degree in data science. So, I start preparing for my personal statement.

Uk university application



I want to start the statement with my reason to take data science. But I am not sure which one that I should emphasize more, the fact that a master's degree will boost my career or how data science can solve some of the problems in my work.

Currently, I am working in the digital marketing department and I don't have any experience in data science before. My past working experience and educational background are computer science.

Holt  Educational Consultant - / 15386  
May 31, 2021   #2
the fact that a master's degree will boost my career or how data science can solve some of the problems in my work.

Neither. For the personal statement, you should show the progression of your interest leading into data science. The writing consideration you mentioned is used in the motivation letter. A personal statement will consider:

- Your undergraduate course as the foundation of your interest
- Your introduction to data science both academically and professionally
- Facets of your work that further exposed you to data science
- Why you became interested in data science
- How you were convinced that you may have a future in this field
- Why you think the course and university can help you retrain.

Now, these are the basic content for a personal statement. Some universities look for specific information and specify there for your writing. Prioritize the university personal statement instructions at all times. Remember to provide the writing instructions for my reference should you opt to have me review your personal statement or other application papers.

You should be able to make simple exposure references based on your college studies and work experience. Data collection is presentin marketing jobs, you just have to frame the experience as relevant to data science.


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