MSc Data Science (Human Behaviour)

Prepare for a career in data science with this interdisciplinary course investigating human behavioural data.

Year of entry: 2025 (September)

Start date

September 2025
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Length

1 year full-time

School/department

Department of Psychology

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Data science is an increasingly attractive career destination for graduates, offering lucrative and fulfilling employment opportunities in a variety of sectors.

The purpose of this course is to 'upskill' psychology graduates (and those from neighbouring disciplines) to prepare for a career in data science, with a particular emphasis on human-related data sets that are common in industry and third sector organisations.

This could include the use of social media data, large-scale customer surveys, game data, neuroimaging data, and census data to address problems relevant to businesses, charities and governments. You'll graduate with a unique set of skills that will allow you to work professionally with such data sets and any that involve human behavioural data.

Based in the Department of Psychology, the course is delivered by an interdisciplinary team of experts in the analysis of human behavioural data, and is embedded in a wider portfolio of data science courses across the institution.

Learn more about our range of data science and analytics Masters courses offered at York.

Committed to Gender Equality

We hold a Gold Athena Swan Award for our commitment to improving gender equality in the Department.

Research excellence

Ranked 8th in the UK for research and 2nd for research output quality in the Times Higher Education’s ranking of the latest REF results (2021).

Course content

Our core modules will introduce you to a wide variety of methods used in the analysis of behavioural data. You'll develop in-depth practical experience with, and knowledge of, different analytical techniques using the statistical language R, which is widely used for work of this nature. These methods will include traditional statistical techniques but also cutting-edge processes for analysing large data sets using AI. Throughout the course, you'll be provided with hands-on experience of working with diverse data sets from psychology, neuroscience, and other behavioural sciences.

You'll also develop an understanding of how to use visualisation techniques to present data in a clear and informative way across a number of professional contexts. You'll study the current thinking on key issues in data governance and ethical collection and use of data. All modules are aimed to take you from the key basics of analysis to more advanced cutting-edge techniques.

Modules
Dissertation

Modules

Core modules

Option modules

Our modules may change to reflect the latest academic thinking and expertise of our staff, and in line with Department/School academic planning.

Dissertation

You'll complete an extended dissertation project, to help build an externally-facing data science portfolio to showcase to potential employers.

MSc Project

Learning outcomes

Every course at York is built on a distinctive set of learning outcomes. These will give you a clear understanding of what you will be able to accomplish at the end of the course and help you explain what you can offer employers. Our academics identify the knowledge, skills, and experiences you'll need upon graduation and then design the course to get you there.

Learning outcomes for this course

Gain cutting-edge skills enabling them to assemble (import, clean, format, summarise) diverse human-relevant data within a contemporary statistical environment.
Design and compose informative data visualisations and dashboards, and compare and assess examples made by others.
Critically evaluate ethical issues around the use of human data, and appraise current techniques such as artificial intelligence, to ensure they are used for public good.
Design and assemble analysis pipelines for large-scale human data sets using appropriate tools, and deploy these on modern infrastructure (for example using continuous integration and continuous deployment systems).
Have a high-level understanding of a range of advanced statistical analysis and machine learning techniques, and be able to formulate data analysis plans and implement them using a modern programming language (R).
Create and project-manage their own data science projects, working independently and as part of a team, to construct professional quality reports and visualisations, and communicate their results to both specialist and non-specialist audiences.

Fees and funding

Annual tuition fees for 2025/26

Study mode	UK (home)	International and EU
Full-time (1 year)	£13,300	£31,900

Students on a Student Visa are not currently permitted to study part-time at York.

Fees information

UK (home) or international fees? The level of fee that you will be asked to pay depends on whether you're classed as a UK (home) or international student. Check your fee status.

Find out more information about tuition fees and how to pay them.

Postgraduate taught fees and expenses

Funding information

Discover your funding options to help with tuition fees and living costs.

We'll confirm more funding opportunities for students joining us in 2025/26 throughout the year.

If you've successfully completed an undergraduate degree at York you could be eligible for a 10% Masters fee discount.

Funding opportunities

Chevening Scholarships

We are pleased to work with Chevening Scholars to offer funding for our Masters programmes. Chevening Scholarships provide one year of fully-funded postgraduate study in the UK for international (including EU) students. The scholarships are open to early and mid-career professionals who have the potential to become future leaders.

Living costs

You can use our living costs guide to help plan your budget. It covers additional costs that are not included in your tuition fee such as expenses for accommodation and study materials.

Teaching and assessment

You’ll work with world‐leading academics who’ll challenge you to think independently and excel in all that you do. Our approach to teaching will provide you with the knowledge, opportunities, and support you need to grow and succeed in a global workplace.

Teaching format

Teaching will consist of lectures, seminars, self directed learning, and group tasks. Real-world case examples will be blended with key theoretical and practical skills practice.

As the course progresses, you'll have greater independence with the emphasis being on choice, specialisation, and independent study, all supported by supervisors.

Seminars focus on small group work, discussions and presentations. You will gain knowledge in all aspects of research, from designing and carrying out experiments to analysing, critically evaluating and interpreting results. This experience will equip you with valuable skills that you will apply in your final empirical project.

Through the Virtual Learning Environment, you will have access to teaching materials, including lecture slides and recordings, practical demonstrations and supporting materials.

Facilities

Our Department is purpose-built with superb teaching and research facilities. We have strong links with the Smart Data Donation Service (SDDS), which holds large-scale human behavioural data about online interactions and behaviour. Some examples include content exposure on video sharing platforms such as TikTok and YouTube, gaming data, and fitness trackers which could be linked to information on people's mental health or psychometrics.

You'll engage with the SDDS within a specialised module on Big Human Data, putting you at the forefront of research and policy surrounding online harms and benefits.

Teaching location

The Department of Psychology is located on Campus West.

Most tutorials, seminars, practical work, staff offices and laboratories are in our bespoke psychology building.

About our campus

Our beautiful green campus offers a student-friendly setting in which to live and study, within easy reach of the action in the city centre. It's easy to get around campus - everything is within walking or pedalling distance, or you can always use the fast and frequent bus service.

Assessment and feedback

Assessments will be in a range of formats, including those aimed at experts: an empirical dissertation, mock case reports, a 'plan' or 'preregistration' for a hypothetical research study, and reflective reports considering your understanding and changing views on issues you have learned about. You will also communicate to a lay audience in the form of a blog on an important research study linked to the understanding and or treatment of mental health issues.

Careers and skills

You'll acquire skills and experience critical to contemporary data science practice, using human-relevant data. You'll build a portfolio of outputs to showcase to potential employers, demonstrating your programming and analysis skills.

You'll have access to the University’s careers service, which includes provision from dedicated careers advisors. On completion of the course, you'll be competitive applicants for a wide variety of data science roles, across industry, government and third sector organisations.

Career opportunities

Data scientist
Research scientist
Research software engineer
Science policy advisor
Data analyst
Informatician

Transferable skills

Team working
Self-management
Application of IT and numeracy
Problem-solving
Communication and literacy
Consultancy skills

Entry requirements

Qualification	Typical offer
Undergraduate degree	2:2 or equivalent in an undergraduate degree in Psychology, or cognate discipline such as a Social Science with a statistical element.
Other international qualifications	Equivalent qualifications from your country

English language

If English isn't your first language you may need to provide evidence of your English language ability. We accept the following qualifications:

Qualification	Minimum requirement
IELTS (Academic and Indicator)	6.5, minimum 6.0 in each component
Cambridge CEFR	B2 First: 176, with 169 in each component
Oxford ELLT	7, minimum of 6 in each component
Oxford Test of English Advanced	136, minimum 126 in each component
Duolingo	120, minimum 105 in all other components
LanguageCert SELT	B2 with 33/50 in each component
LanguageCert Academic	70 with a minimum of 65 in each component
Kaplan Test of English Language	478-509, with 444-477 in all other components
Skills for English	B2: Merit overall, with Pass with Merit in each component
PTE Academic	61, minimum 55 in each component
TOEFL	87, minimum 21 in each component
Trinity ISE III	Merit in all requirements

For more information see our postgraduate English language requirements.

If you haven't met our English language requirements

You may be eligible for one of our pre-sessional English language courses. These courses will provide you with the level of English needed to meet the conditions of your offer.

The length of course you need to take depends on your current English language test scores and how much you need to improve to reach our English language requirements.

After you've accepted your offer to study at York, we'll confirm which pre-sessional course you should apply to via You@York.

Applying

You can apply and send all your documentation online. You don’t need to complete your application all at once: you can start it, save it and finish it later.