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A Guide to Data Science Courses

Data science as a subject is multi-disciplinary, and covers more than one area. As a data scientist, you will use scientific and mathematical methods, algorithms, processes and systems to extract, organise and analyse data. Data sets come in all sizes, and can be both structured and unstructured, and you will be responsible for understanding how to work with that data. Data scientists can help to solve problems, make predictions, and aid growth in business.

Coursework

Undergraduate

An undergraduate degree in data science will give you a good foundation of knowledge in the main areas of the subject. You will cover the basic theoretical and practical aspects of data science. Modules you study might include an introduction to programming, maths statistics, data analysis and statistical methods.

Your degree will be delivered in a mixture of modes. These will include lectures and seminars, as well as practical and computer laboratory based sessions. You may be presented with the opportunity to take part in a placement module, which would allow you to gain real-world experience as a data scientist.

Postgraduate

A postgraduate degree in data science will allow you to build on the knowledge you gained at undergraduate level. The modules you study will cover more specialist and complex areas of data science. These modules could include advanced programming, databases, data management, web application development and software development.

Your degree will be delivered through lectures and seminars, as well as incorporating practical sessions. Your course will likely be focused on preparing you for your final dissertation or data science project, as well as equipping you with skills to help develop your career.

Specialisations

Depending on where you choose to study, you may be able to specialise throughout your degree. The specialisations you choose could influence the area in which you wish to work after you have graduated. It can also help you to decide which area you wish to focus your final project on. Common specialisations include:

  • Machine Learning
  • Big Data
  • Statistical and Computational Data Science
  • Artificial Intelligence
  • Stochastic Processes

Accreditation and certification

The accreditation of your degree will depend on where you choose to study. It will also be influenced by your level of study. At undergraduate level, you can expect to be awarded a Bachelor of Science (BSc), or a Bachelor of Computing (BComp). At postgraduate level, you can expect to be awarded a Master of Science (MSc), or a Master of Computing (MComp). If you choose to study for a postgraduate research degree, you can expect to be awarded a Master of Research (MRes), a Master of Philosophy (MPhil), or a Doctor of Philosophy (PhD).

Timeframe and further studies

Generally, an undergraduate degree will take three to four years to complete. Foundation degrees, diplomas and certificates can last up to two years, when studied full-time. A postgraduate degree will normally take one to two years. If your course includes a placement, this will normally add another year onto your studies.

Some institutions might offer part-time study options. Studying for a degree part-time normally means that your course will last anywhere between three and eight years, with some universities offering more flexible study options.

Entry requirements

Undergraduate

The entry requirements for an undergraduate data science degree will depend on where you choose to study. Normally, you will be required to have previously studied a subject related to data science, such as IT or computing. Other quantitative subjects such as maths or statistics may also be accepted. If you do not have a strong background in these areas, but can prove that you are passionate about data science, some institutions may still consider your application.

Some universities might require you to sit an entrance exam, where others may rely on previous exam results. Other universities might consider relevant work experience. If your first language is not English, it is likely that you will be required to provide evidence that your English language skills are to a high enough standard.

Postgraduate

The entry requirements for a postgraduate degree in data science will depend on your institution of choice. They will also depend on what sort of postgraduate degree you are applying for. Typically, you will be expected to have completed an undergraduate degree in data science, or a closely related subject.

You should check each institution to see what entry requirements they have for their data science programmes.

  • UK – 6.0 IELTS, 2:2 or higher
  • US – 6.0 IELTS, 3.5 GPA

Funding your studies

Tuition fees for international students are not fixed. This means that they can vary greatly from institution to institution. Fees for postgraduate degree courses tend to be higher than undergraduate courses. Exact tuition fees are displayed on institution course pages.

You may be eligible for a scholarship or funding. This could be awarded by your institution, or by a separate funding body. For more information, visit our scholarships and funding section.

Career options

Graduates of a data science degree will find that there are a wide variety of career opportunities available to them. If you choose to work in a role directly related to your degree, jobs could include a data scientist, data analyst, or data engineer. If you choose to work in a role not directly related to your degree, jobs could include business analyst, applied mathematician, or statistician.

Degrees in Data Science Masters in Data Science

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Data Science, AI & Digital Business MSc

Gisma University of Applied Sciences Germany

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EU Business School, Geneva Switzerland

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Harbour.Space University Spain

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Data Science MSc

University of Europe for Applied Sciences Germany

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Graduate Diploma in Data Science GradDip

Western Sydney University Australia

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