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The basics
Study abroad : Subject Guides

Why study data science?

The importance of data in problem-solving, decision-making and strategy has gained prominence over the last decade. We put the spotlight on data science and why studying for a degree in the subject might suit you.

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We live in a world of big data. Many of our everyday actions, from watching videos on our phones to purchasing a product online create data. Since the advent of the technological revolution, data has played an increasingly important role in many fields and spheres of life. That’s why interpreting and understanding data has become such a valuable skill. We profile what it’s like to study a degree in data science, what the benefits are, and what sort of careers you could have after graduation.

 

What is data science?

 

Data science is the study and examination of data with the purpose of understanding patterns. Data science uses tools, techniques, and theories to produce a meaningful interpretation of data for decision-making and development. It is categorised as a STEM subject and professional degree by most universities

 

You’ve probably heard of algorithms in the context of computer science, and perhaps you won’t be surprised to hear that they’re also used in data science to record, process, and analyse information. Data science is used in many industries, from business to healthcare, helping to improve outcomes and efficiency.

 

Data science has several areas of focus, sometimes referred to as a cycle or phases. It’s possible to develop expertise in one specific area, or all when studying for a degree in the subject. The phases usually associated with data science are:

 

  • Collecting data
  • Storing and maintaining data
  • Processing data
  • Analysing, testing, and interpreting data
  • Communicating results and conclusions

 

As you can see, there are numerous areas of specialisation within the data cycle, making data science both a challenging and stimulating subject.

 

Discover more about the best degrees for the future.

 

What are the entry requirements for a data science degree?

 

If you are considering data science at university, you will need to have both an interest and ability in mathematics. For entry onto an undergraduate BSc Data Science degree, you will require:

 

  • Minimum of A-Level results at ABB; an SAT score of 1,290 in Reasoning and 650 in three subject tests; Associate degree 3.2; International baccalaureate 34 points; or equivalent.
  • IELTS score of 6.0 with no band score lower than 5.5.
  • Mathematics / physics / statistics as a subject.

 

If you’re interested in studying for an MSc in data science, some of the entry requirements include:

 

 

Read more about how you can qualify to study for a master’s degree.

 

What will I study in a data science qualification?

 

While the curriculum for a data science qualification will differ between different universities, there are several fundamental areas that you will learn. Data science courses aim to introduce you to specialist knowledge and skills for understanding data. For example, you will learn about databases while at the same time engaging with concepts in machine learning and artificial intelligence. Further, you’ll learn how to apply these skills in different fields and environments.

 

If you choose to study for an undergraduate degree in data science, then some of the modules that you’ll take can include:

 

  • Programming fundamentals
  • Data architecture and infrastructure
  • Operating systems
  • Computing
  • Database development
  • Data algorithms
  • Machine learning
  • Software engineering
  • Cloud computing
  • Business analytics
  • System security
  • Data privacy

 

The assessment methods used in a data science degree do vary. However, course evaluation will include assignments, examinations, practical projects, and final year dissertation/project. Some undergraduate programmes may also include a work placement or internship component as part of your curriculum.

 

Find out more about how you can map your career and study path.

 

What are the benefits of studying data science?

 

One of the primary benefits of studying data science is that your employment prospects are considered good. With an increasing reliance on data across many industries, the need for those with specialist skills continues to grow. Some of the other plus points of studying data science include:

 

  • You’ll be equipped with a set of skills that are transferable across roles, fields, and sectors.
  • Data science draws on many disciplines including, computer science, mathematics, statistics, business, and engineering. This makes it a dynamic and engaging study option.
  • Data science is an evolving discipline. It provides great growth and development potential for the future.
  • Data science can allow you to make a positive contribution to society by providing insights or designing systems that successfully help people improve their lives.
  • You’ll develop excellent collaborative, communication, analytical, and numerical skills.
  • You’ll fine-tune your agile thinking and problem-solving abilities.

 

Remember that it’s also important to evaluate your personality and abilities when considering what you would like to study.

 

What can you do with a degree in data science?

 

As we’ve mentioned, the career options for data science graduates are generally very positive. It’s a growing field, and the demand for qualified graduates will continue to develop and grow in the next five to 10 years. As a graduate data scientist, you can expect to earn between GBP 23,000 and GBP 30,000 per year. This can rise to GBP 40,000 with five or more years of experience, and if you reach senior management, this can be over GBP 60,000.

 

Because of the versatility and wide applicability of a data science degree, you could find yourself working in industries including:

 

  • Business
  • Education
  • Healthcare
  • Finance
  • Retail
  • Manufacturing
  • Engineering
  • Research
  • Insurance
  • Advertising

 

You could work as a data analyst, business analyst, systems analyst or even a database manager, to name a few roles. Some of the work that you may do can include:

 

  • Policy and strategy development
  • Process development and management
  • Reporting
  • Data automation
  • Data visualisation
  • Data mining
  • Auditing

 

Don’t forget that if you’re unsure about the type of career you would like and what you may want to study, you can speak to an education counsellor or even the careers service at a university.

 

With your new knowledge of data science, you’re well placed to decide if the field interests you. If you’d like to do more research you can read our guide to the top 10 reasons to study abroad, the ultimate study abroad preparation checklist, and a guide to university application.

 

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