Data Science with Visualization MSc

Overview

Data science and data visualisation are closely linked. They're vital to understanding and sharing complex data insights.

Data science extracts insights and knowledge from large and complex datasets. It uses techniques from various fields, including statistics, computer science, and domain expertise.

Data visualisation is the graphical representation of data. It's used to share insights, patterns, and trends in a clear and visual way.

We created the Data Science and Visualization MSc with several high-profile industry leaders. It brings together students and industry practitioners to develop and translate new technologies into industry practice.

You’ll learn to analyse data and uncover patterns, trends and correlations. Topics covered include:

• data visualisation
• statistics
• machine learning
• data engineering

Important information

We've highlighted important information about your course. Please take note of any deadlines.

Your course and study experience - disclaimers and terms and conditions

Please rest assured we make all reasonable efforts to provide you with the programmes, services and facilities described. However, it may be necessary to make changes due to significant disruption, for example in response to Covid-19.

View our Academic experience page, which gives information about your Newcastle University study experience for the academic year 2024-25.

See our terms and conditions and student complaints information, which gives details of circumstances that may lead to changes to programmes, modules or University services.

 

Qualifications explained

Find out about the different qualification options for this course.

MSc - Master of Science

An MSc is a taught Master’s degree. It usually involves the study of a science-related subject.

You'll usually study an MSc full-time over 12 months.

A Master of Science is typically awarded for the successful completion of 100 credits of taught modules and an 80-credit dissertation or research project.

Find out about different types of postgraduate qualifications.

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, meaning you'll be taught two modules simultaneously.

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. You'll work in an industry organisation. They can be a regional, national or charitable organisation. You'll propose a data science project in that company, institute, or area of research.

Phase three

In your final phase, you'll work on an individual research project. It'll give you an opportunity to:

• develop your knowledge and skills
• work in a research or development team

You can develop your project:

• at the University under an academic supervisor
• by securing an industrial placement
• working with your current employer

You'll have one-to-one supervision from an experienced staff member. If needed, you'll also get supervision from industry partners.

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.

Course content changes

Module information is intended to provide an example of what you will study.

Our teaching is informed by research. Course content changes periodically to reflect developments in the discipline, the requirements of external bodies and partners, and student feedback.

Full details of the modules on offer will be published through the Programme Regulations and Specifications ahead of each academic year. This usually happens in May.

To find out more please see our terms and conditions.

Optional modules availability

Some courses have optional modules. Student demand for optional modules may affect availability.

 

Data Science with Visualization MSc modules

Compulsory Modules	Credits
Human Computer Interaction	10
Data Visualization	10
Image Informatics	10
Data Management and Exploratory Data Analysis	10
Data Science in the Wild (Group Project)	10
Machine Learning with Project	10
Complex Data Visualization	10
Project and Dissertation in Data Science	80
Statistical Foundations of Data Science	10
Statistical Learning for Data Science	10

Further compulsory module information

If you have permission from the Degree Programme Director, you can swap Advanced AI (10 credits) with Bayesian Methodology (10 credits).

How you'll learn

Delivery and teaching methods

The School of Computing and School of Mathematics, Statistics and Physics deliver this course.

You'll be taught using a range of methods, including:

• seminars
• lectures
• practical classes
• group and individual project work
• guided independent reading
• self-directed learning

Assessment methods

Depending on your modules, you'll be assessed through a combination of:

• Dissertation
• Oral presentation
• Poster
• Report
• Written examination

Additional assessment information

Our MSc in Data Science with Visualization uses both formative and summative assessments.

These assessments will:

• evaluate your overall understanding of the course content
• identify your strengths and areas for improvement
• encourage continuous learning and personal development

Formative assessments

Formative assessments are designed to provide ongoing feedback and support throughout the course. These assessments will help you identify your strengths and areas for improvement, fostering continuous development.

Examples of formative assessments include:

• Weekly quizzes: Short quizzes at the end of each module to test your understanding of the material.
• Assignments: Regular assignments that involve practical data analysis tasks and problem-solving exercises.
• Class participation: Active participation in seminars, workshops, and group discussions to enhance learning through interaction.
• Peer reviews: Opportunities to review and provide feedback on classmates' work, promoting collaborative learning.

Summative assessments

Summative assessments occur at the end of each module. They're designed to evaluate your overall comprehension and mastery of the course content.

These assessments will contribute to your final grade.

Examples of summative assessments include:

• Coursework: Projects where you apply the skills and knowledge gained throughout the course to a real-world data science problem.
• Presentations: Oral presentations of your projects and research findings to assess your communication skills and ability to articulate complex ideas clearly.

There'll be no written exams during your Data Science MSc.

Wellbeing advisor support

The School of Computing has a dedicated Wellbeing Advisor who understands the needs of our students.

They can be a confidential listening ear and provide guidance on a range of wellbeing issues.

Student support

Your teaching and learning is also supported by Canvas. Canvas is a Virtual Learning Environment. You'll use Canvas to submit your assignments and access your:

• module handbooks
• course materials
• groups
• course announcements and notifications
• written feedback

Throughout your studies, you’ll have access to support from:

• peers
• academics
• personal tutors
• our University Student Services Team
• student representatives

You'll also be assigned an academic member of staff. They will be your personal tutor throughout your time with us. They can help with academic and personal issues.

Our staff

The staff delivering this course are internationally recognised for their contributions to data science. Many of them have extensive experience working in industry and academia.

Search our academic staff in the School of Computing

Your development

Improve your research skills through an extended research project. The project can include:

• a literature review
• problem specifications
• design
• implementation
• analysis

You'll also develop your practical skills in:

• data collection
• data cleaning
• data visualisation
• machine learning
• big data technologies

You'll improve your communication, problem-solving, teamwork and project management skills. You'll also grow as a leader and learn to make ethical decisions.

Your future

Careers

The course prepares you for a wide range of careers, in roles such as:

• Data Scientist
• Data Analyst
• Business Intelligence Analyst
• Research Data Scientist
• Quantitative Analyst

Graduates from this course have undertaken various roles including:

• Senior Software Engineer at Sage
• Data Analyst at Vodafone
• Data Engineer at Virgin Atlantic
• Data Scientist at Stanley Black & Decker, Inc.

Further study

This course provides a route into PhD level study, offering a robust foundation in both theoretical and applied aspects of Data Science. As a graduate, you'll be prepared to pursue advanced research opportunities and contribute to the academic community through doctoral programs.

Data science careers support

Our dedicated careers support team offers specialised guidance tailored to data science students. This includes:

• career planning
• workshops on resume-building and interview techniques
• networking events with industry leaders
• job fairs focused on data science and analytics
• access to an extensive alumni network for mentorship and job referrals
• support for start-ups

Our Careers Service

Our award-winning Careers Service is one of the largest and best in the country, and we have strong links with employers. We provide an extensive range of opportunities to all students through our ncl+ initiative.

Visit our Careers Service website

Quality and ranking

All professional accreditations are reviewed regularly by their professional body

Recognition of professional qualifications outside of the UK

From 1 January 2021 there is an update to the way professional qualifications are recognised by countries outside of the UK

Check the government’s website for more information.

Facilities

Data visualisation technology

The School of Computing has cutting-edge technology to support research in data visualisation such as:

• a stereoscopic wall display
• a large touchscreen display
• eye trackers
• hand-tracking devices
• VR headsets

National Innovation Centre for Data

The Newcastle Helix campus is home to the UK’s National Innovation Centre for Data (NICD). NICD runs projects with organisations to help them acquire new skills and innovate through data.

Urban Sciences Building

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

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

Postgraduate student facilities

As a Master's student, you'll have access to specialist teaching spaces and facilities in the USB. These are only available to postgraduate students.

Wellbeing and inclusivity are at the heart of our School. The USB has several wellbeing spaces for students, including:

• The Retreat: A sensory space with relaxing stimuli to distract from busy student life.
• Wellbeing room: Designed for relaxation and quiet time. Here you can take a moment to breathe and unwind. It can also be used by students with special medical requirements.
• Prayer room: For all faiths and none, this space can be used for prayer or quiet reflection.

Fees and funding

Tuition fees for 2025 entry (per year)

Tuition fee increases

As a general principle, you should expect the tuition fee to increase in each subsequent academic year of your course, subject to government regulations on fee increases and in line with inflation.

EU, other EEA and Swiss nationals - tuition fee status

Depending on your residency history, if you’re a student from the EU, other EEA or a Swiss national, with settled or pre-settled status under the EU Settlement Scheme, you’ll normally pay the ‘Home’ tuition fee rate and may be eligible for Student Finance England support.

EU students without settled or pre-settled status will normally be charged fees at the ‘International’ rate and will not be eligible for Student Finance England support.

If you are unsure of your fee status, check out the latest guidance here.

Scholarships

We support our EU and international students by providing a generous range of Vice-Chancellor's automatic and merit-based scholarships. See our searchable postgraduate funding page for more information. 

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:

• living costs
• tuition fees

Deposit

If you are an international student or a student from the EU, EEA or Switzerland and you need a visa to study in the UK, you may have to pay a deposit.

You can check this in the How to apply section.

Funding deadlines

If you're applying for funding, always check the funding application deadline. This deadline may be earlier than the application deadline for your course.

For some funding schemes, you need to have received an offer of a place on a course before you can apply for the funding.

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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.

Apply Online  

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