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Data Science with Visualization MSc

Our Data Science with Visualization MSc gives you the knowledge, experience and expertise to solve real-world problems and realise data-driven insights for organisations.

You are currently viewing course information for entry year:


Start date(s):

  • September 2024
PG virtual open day. Wednesday 15 May, 13:00-18:00 (BST). Book your spot

Overview

Data visualisation is an increasingly important part of data science. It aims to bridge the gap between the human and data. It supports human perception and cognition to make sense of data analytics outputs.

We created the Data Science with Visualisation MSc in collaboration with several high-profile industry leaders. It aims to address the skills shortage in data analytics.

Our master's in data science brings together students and industry practitioners to develop and translate new technologies into industry practice.

You'll receive a comprehensive grounding in the theory and application of data science. You'll also be able to apply these skills to real problems in a given application area.

Through project work, you'll experience the full lifecycle from the design of interactive visualization to the experimental evaluation of an advanced visualization approach.

Topics covered in the course include:

  • cloud computing
  • Bayesian statistics
  • machine learning

You'll benefit from our substantial expertise in data science. 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

This Data Science with Visualization MSc has three phases.

Phase one

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

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 school research labs. This is in collaboration with industry, or with your current employer.

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

Fees and funding

Tuition fees for 2024 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

Find out more about:

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Entry requirements

The entrance requirements below apply to 2024 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:

Dr Alma Cantu
Degree Programme Director
Email: computing.datascience@ncl.ac.uk
School of Computing

Online

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

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