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Data Science (with specialisation in Statistics) MSc, PGDip, PGCert

Solve real-world problems and realise data-driven insights for organisations.

You are currently viewing course information for entry year:


Start date(s):

  • September 2023
Postgraduate Open Day Wednesday 8 February 2023 register now

Overview

This course blends modern statistical methods with the computational skills to handle large quantities of unstructured data.

Data Science is revolutionising every area of science, engineering and commerce. It has potential for huge societal and economic benefits. Statistical analysis, with data analytics, is in-demand. There is an industry need for analytical skills that can interpret and extract value from complex data.

During this course you'll develop a comprehensive understanding of data science theory, and how to use it in real world scenarios. You'll also develop a combination of skills in statistics and computer science.

You’ll put your new skills into action immediately, and work with real data sets in your applied data science projects. All module assessments are based on these projects.

We focus on a wide range of application areas, including:

  • healthcare
  • transport
  • cybersecurity
  • smart cities
  • manufacturing

This data science course is part of the following suite:

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Important information

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Qualifications explained

Find out about the different qualification options for this course.

What you'll learn

The course has three phases.

Phase one

We’ll introduce you to the core knowledge and skills in statistics and computer science.

You’ll also receive introductory training in Python, alongside data science modules in:

  • data visualisation
  • machine learning
  • time series analysis
  • Bayesian inference

These modules are taught as an intensive block. This means that full-time students are taught two modules simultaneously. Teaching for part-time students is timetabled to accommodate everyone.

Phase two

Phase two consists of more advanced technical modules, as well as a group project.

We'll introduce the aspects that govern all areas of data science practice, including:

  • professionalism
  • legislation
  • ethics

During the group project, you'll develop and evaluate a data science solution to a complex, real-world problem. This is in collaboration with industry members.

Phase three

Phase three is an individual research and development project.

You'll receive personal supervision in one of our Schools research labs. This is in collaboration with industry, or with your current employer.

This MSc forms part of the following suite of data science courses:

Modules

You will study modules on this course. A module is a unit of a course with its own approved aims and outcomes and assessment methods.

How you'll learn

Quality and ranking

All professional accreditations are reviewed regularly by their professional body

Facilities

The School of Computing is based in the £58million Urban Sciences Building, a flagship development located on the £350m Newcastle Helix regeneration site in the heart of Newcastle. It brings together:

  • academia
  • the public sector
  • communities
  • business and industry

Find out more about the Urban Sciences Building

Find out more about the Newcastle Helix

Fees and funding

Tuition fees for 2023 entry (per year)

What you're paying for

Tuition fees include the costs of:

  • matriculation
  • registration
  • tuition (or supervision)
  • library access
  • examination
  • re-examination
  • graduation

Some of our degrees involve additional costs which are not covered by your tuition fees.

Find out more about:

  • additional costs
  • living costs
  • tuition fees, including how to pay them and available discounts

Search for funding

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Entry requirements

The entrance requirements below apply to 2023 entry.

Qualifications from outside the UK

English Language requirements

Admissions policy

This policy applies to all undergraduate and postgraduate admissions at Newcastle University. It is intended to provide information about our admissions policies and procedures to applicants and potential applicants, to their advisors and family members, and to staff of the University.

Download our admissions policy (PDF: 201KB)
Other policies related to admissions

Credit transfer and Recognition of Prior Learning

Recognition of Prior Learning (RPL) can allow you to convert existing relevant university-level knowledge, skills and experience into credits towards a qualification. Find out more about the RPL policy which may apply to this course

How to apply


Using the application portal

The application portal has instructions to guide you through your application. It will tell you what documents you need and how to upload them.

You can choose to start your application, save your details and come back to complete it later.

If you’re ready, you can select Apply Online and you’ll be taken directly to the application portal.

Alternatively you can find out more about applying on our applications and offers pages.


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Open days and events

You'll have a number of opportunities to meet us throughout the year including:

  • campus tours
  • on-campus open days
  • virtual open days
  • webinars

Find out about how you can visit Newcastle in person and virtually

Overseas events

We regularly travel overseas to meet with students interested in studying at Newcastle University.

Visit our events calendar for the latest events

Get in touch

Questions about this course?

If you have specific questions about this course you can contact:

Postgraduate Secretary
School of Mathematics, Statistics and Physics
Telephone: +44 (0) 191 208 6960
Email: maths.physics@ncl.ac.uk

Online

For more general enquiries you could also complete our online enquiry form.

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