Postgraduate taught 

Data Analytics for Government MSc/PgDip/PgCert: Online distance learning

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While the amount of data being produced is proliferating at a staggering rate, the skills to extract information and the value we receive from it are both relatively scarce. Analytics and data-driven decisioning is playing an increasingly important role in the economy, society and public administration. Designed together with the Office for National Statistics, our MSc in Online Data Analytics for Government is based on our successful online MSc programme in Data Analytics and will provide you with vital skills required to develop your modelling and data handling expertise. You will gain a firm grounding in the principles of learning from data sets, whilst at the same time getting hands-on experience handling, analysing and visualising data, helping your organisation to maximise the insights and value extracted from its data.

  • MSc: usually 36 months part‑time
  • PgDip: 24 months part‑time
  • PgCert: 12 months part‑time

Register your interest for more information

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Why this programme

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  • The Statistics Group at the University of Glasgow is internationally renowned for its research excellence. Students are able to benefit from this by learning from academics whose expertise covers the analysis of data from a wide range of applications.
  • A faster study route, which lets you complete the programme in two years, and a slower study route, which lets you complete the programme in four years, is also available.
  • Designed for part-time study, this programme allows you to gain an MSc degree from a leading university while you're still in full-time employment. Plus, from day one you can start to put your new knowledge to the test at work. You won't have to wait until you've graduated to make a real difference in the workplace.
  • You will have the freedom to work at your own pace and access to a wide range of learning tools including rich interactive reading material and tutor-led videos. You will also be able to arrange tailored one-to-one sessions with our academic team.

    • Information sessions

    We run regular online information sessions for prospective students to find out more about the programme and ask questions. 

    You can also view recordings of recent information sessions on YouTube.

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    What our students say

    Jonas Dieckmann (Data & Advanced Analytics Manager at Philips)

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Programme structure

This flexible part-time programme is usually completed over three years. In the first two years, you will take two courses each trimester. If you are doing the MSc, in the third year you will undertake a project and dissertation.

Core courses (MSc / PgDip)

  • SAMPLING FUNDAMENTALS (ODL) (10 credits) 
    This course introduces students to key concepts from probability theory and provides an introduction to survey sampling with a focus on the underpinning probabilistic mechanisms.
  • STATISTICAL COMPUTING (ODL) (10 credits)
    Designed to introduce you to programming in the statistical software environment R. You’ll be introduced to basic concepts and ideas of a statistical computing environment and trained in programming tools which use the R computing environment. The course provides computational skills which will support other courses on the programme and you will learn the fundamental concepts in scientific programming.
  • DATA SCIENCE FOUNDATIONS (ODL) (10 credits)
    This course will introduce you to different approaches to learning from data, with a focus on interval estimation, hypothesis testing and frequentist and Bayesian model-based inference. You will then learn how to implement these statistical methods using R.
  • PREDICTIVE MODELLING (ODL) (10 credits)
    This course will introduce you to predictive modelling using multiple linear regression as a showcase. It will present some of the distributional theory underpinning the normal linear models and the associated methods for testing and interval estimation. You will also find out how the design matrix of a linear model can be constructed to accommodate categorical covariates or, through basis expansions, non-linear effects.
  • ADVANCED PREDICTIVE MODELS (ODL) (10 credits)
    Looking at models which can account for a non-normal distribution of the response and/or the fact that data is not independent, but correlated. You will gain an overview of different generalisations of linear regression models and become acquainted with the theory of exponential families. You’ll also be introduced to generalised linear models and the concept of a time series.
  • STATISTICS IN GOVERNMENT (ODL) (10 credits)
    The course provides an overview of issues, legal frameworks, ethical considerations, and dissemination practices of official statistics from the UK, EU, and relevant international governments, institutions, and organisations.
  • DATA PROGRAMMING IN PYTHON (ODL) (10 credits)
    This course will introduce you to object-oriented programming and Python as a generic programming language and its use for data programming and analytics. You will learn to use Python libraries that are relevant to data analytics such as scikit-learn, NumPy/SciPy and pandas.
  • UNCERTAINTY ASSESSMENT AND BAYESIAN COMPUTATION (ODL) (10 credits)
    Develops the foundations of modern Bayesian statistics and demonstrates how prior distributions are updated to posterior distributions in simple statistical models. You’ll be introduced to advanced stochastic simulation methods such as Markov-chain Monte Carlo. You’ll also find out how to fit Bayesian models using high-level software for Bayesian hierarchical modelling such as BUGS or STAN.
  • INTRODUCTION TO SURVEY RESEARCH (10 credits)
    The course, beginning January 2022, provides an introduction and overview of survey sampling and design, survey statistics, ethics, types of surveys, data processing and management.
  • DATA MINING AND MACHINE LEARNING I: SUPERVISED AND UNSUPERVISED LEARNING (ODL) (10 credits)
    An introduction to machine learning methods and modern data-mining techniques, with an emphasis on practical issues and applications. You’ll be introduced to different methods for dimension reduction and clustering (unsupervised learning), a range of classification methods beyond those covered in the Predictive Modelling course. You’ll also learn about neural networks, deep learning, kernel methods and support vector machines.
  • DATA MINING AND MACHINE LEARNING II: BIG DATA AND UNSTRUCTURED DATA (ODL) (10 credits)
    This course will provide you with a grounding in data mining and machine learning methods used in big data scenarios. You will also learn methods for analysing networks and unstructured data, as well as formal methods for social network analysis and quantitative text analysis.
  • LARGE-SCALE COMPUTING FOR DATA ANALYTICS (ODL) (10 credits) 
    The course introduces students to deep learning and convolutional neural networks and presents an overview over systems for large-scale computing and big data.
  • DATA ANALYTICS PROJECT (ODL) (60 credits) (MSc only)
    At the end of the programme you will complete a project, giving you the opportunity to put the skills you have acquired throughout the programme into practice. During the project you will solve a real-world data analytics problem using state-of-the-art data science methods.

PgCert

Students studying for the PgCert only will take the following courses: (see above for course descriptions)

Core courses

Optional courses

Choose two from the following:

As part of the framework agreement with the Office of National Statistics, learners sponsored by UK public sector bodies can also enrol for individual courses.

Programme alteration or discontinuation
The University of Glasgow endeavours to run all programmes as advertised. In exceptional circumstances, however, the University may withdraw or alter a programme. For more information, please see: Student contract.

Career prospects

The programme equips you with key data and analytical skills required to master the challenges and make the most of the opportunities in today's technology-driven world. The programme is specifically designed for employees in the public sector and will help you accelerate your career and progress to senior roles in data science and analytics.

Fees & funding

Tuition fees for 2023-24

MSc

UK / EU / International

  • £15,000 (total cost, incremental payment schedule available)
  • Part-time fees: £1,667 per 20 credits
  • Fee for public sector employees sponsored by UK government body: £10,000 (total cost, official sponsorship letter required)

PgDip

UK / EU / International

  • £10,000 (total cost, incremental payment schedule available)
  • Part-time fees: £1,667 per 20 credits
  • Fee for public sector employees sponsored by UK government body: £6,667 (total cost, official sponsorship letter required)

PgCert

UK / EU / International

  • £5,000 (total cost, incremental payment schedule available)
  • Part-time fees: £1,667 per 20 credits
  • Fee for public sector employees sponsored by UK government body: £3,334 (total cost, official sponsorship letter required)

Additional fees

  • Fee for re-assessment of a dissertation (PGT programme): £370
  • Submission of thesis after deadline lapsed: £350
  • Registration/exam only fee: £170

Bespoke pricing arrangements apply to students sponsored by UK public sector bodies as part of the framework agreement with the Office for National Statistics.

Funding opportunities

UK Study Online Scholarship

The UK Study Online scholarship is open to UK, EU and international students taking online undergraduate and postgraduate courses. 

Please see UK Study Online for more details.

Postgraduate Student Loan (Scotland and EU)

Eligible full-time and part-time students, undertaking an eligible postgraduate course, can apply for a tuition fee loan up to a maximum of £5,500 towards their course. Eligible full-time postgraduate students can apply for a living-cost loan of up to £4,500.  

This support extends to online Masters or Postgraduate Diplomas, and not to the online Postgraduate Certificate courses.

For more information visit the SAAS website.

Postgraduate Tuition Fee Loans England only (PTFL)

If you’re an English student looking to study a taught Masters programme in Glasgow then you can apply for a student loan. Students from England are able to apply for a non-means tested Postgraduate Master’s Loan of up to £11,570 to help with course fees and living costs. You have to repay your Postgraduate Master’s Loan at the same time as any other student loans you have. You’ll be charged interest from the day you get the first payment.

If you’re studying by distance learning, you can also apply.

Postgraduate Loans for Welsh Students

If you are a Welsh student looking to study a postgraduate programme* in Glasgow then you can apply for a student loan in exactly the same way as you would for a Welsh University.

* does not apply to Erasmus Mundus programmes

Postgraduate Master's Finance

If you’re starting a full-time or part-time Postgraduate Master’s course (taught or research based) from 1 August 2019, you can apply for Postgraduate Master's Finance and receive up to £17,000 as a combination of grant and loan:

  • a maximum grant of £6,885 and loan of £10,115 if your household income is £18,370 and below
  • a grant of £1,000 and loan of £16,000 if your household income is not taken into account or is above £59,200.

For more information visit Student Finance Wales

Postgraduate Doctoral Loan

If you’re starting a full-time or part-time postgraduate Doctoral course (such as a PhD) from 1 August 2019 you can apply for a Postgraduate Doctoral Loan of up to £25,700.

For more information visit Student Finance Wales

Alumni Discount

In response to the current unprecedented economic climate, the University is offering a 20% discount on all Postgraduate Research and full Postgraduate Taught Masters programmes to its alumni, commencing study in Academic session 2023/24. This includes University of Glasgow graduates and those who have completed a Study Abroad programme or the Erasmus Programme at the University of Glasgow. The discount applies to all full-time, part-time and online programmes. This discount can be awarded alongside most University scholarships.

Postgraduate Student Loan (NI)

If you are a Northern Irish student looking to study a taught Masters programme* in Glasgow then you can apply for a student loan in exactly the same way as you would for a University in Northern Ireland.

Northern Irish students are able to apply for non-means-tested tuition fee loans of up to £5,500, to help with the costs of funding.

For more information visit www.studentfinanceni.co.uk/types-of-finance/postgraduate .

* does not apply to Erasmus Mundus programmes

The scholarships above are specific to this programme. For more funding opportunities search the scholarships database

Entry requirements

  1. A first degree equivalent to a UK upper second class honours degree, normally with a substantial mathematics component (at least equivalent to Level-1 courses in Mathematics and Level-2 courses in Calculus and Linear Algebra at the University of Glasgow). Graduates who only have A-Level or Higher Mathematics, or equivalent, may also be admitted to the programme. However students on the programme must successfully complete a mathematical skills course.
  2. Graduates who achieved a degree classification equivalent to a UK lower second class honours degree, or similar, but who have at least two years' relevant professional experience which involved a significant amount of programming, data management, data analysis or mathematical modelling may also be admitted to the programme. Such applicants may be required to complete an interview.
  3. Previous study of Statistics or Computing Science is not required.

English language requirements exemption

We may consider a minimum of three years' working experience within a majority-English speaking business, subject to review of your role and a satisfactory employment reference. To be considered for exemption, please upload a document detailing your experience and an employment reference on company letterhead to the applicant self-service portal.

English language requirements

For applicants whose first language is not English, the University sets a minimum English Language proficiency level.

International English Language Testing System (IELTS) Academic module (not General Training)

  • 6.5 with no subtests under 6.0.
  • Tests must have been taken within 2 years 5 months of start date. Applicants must meet the overall and subtest requirements using a single test.

Common equivalent English language qualifications

All stated English tests are acceptable for admission to this programme:

TOEFL (ibt, mybest or athome)

  • 90 with minimum of R 20, L 19, S 19, W 23.
  • Tests must have been taken within 2 years 5 months of start date. Applicants must meet the overall and subtest requirements using a single test, this includes TOEFL mybest.

PTE (Academic or Academic Online)

  • 60 with minimum of 59 in all subtests.
  • Tests must have been taken within 2 years 5 months of start date.Applicants must meet the overall and subtest requirements using a single test.

Cambridge Proficiency in English (CPE) and Cambridge Advanced English (CAE) 

  • 176 overall, no subtest less than 169
  • Tests must have been taken within 2 years 5 months of start date. Applicants must meet the overall and subtest requirements using a single test.

Glasgow International College English Language (and other foundation providers)

  • 65%.
  • Tests are accepted for academic year following sitting.

University of Glasgow Pre-sessional courses

  • Tests are accepted for 2 years following date of successful completion.

Alternatives to English Language qualification

  • Degree from majority-English speaking country (as defined by the UKVI including Canada if taught in English)
    • students must have studied for a minimum of 2 years at Undergraduate level, or 9 months at Master's level, and must have complete their degree in that majority-English speaking country and within the last 6 years
  • Undergraduate 2+2 degree from majority-English speaking country (as defined by the UKVI including Canada if taught in English)
    • students must have completed their final two years study in that majority-English speaking country and within the last 6 years

For international students, the Home Office has confirmed that the University can choose to use these tests to make its own assessment of English language ability for visa applications to degree level programmes. The University is also able to accept UKVI approved Secure English Language Tests (SELT) but we do not require a specific UKVI SELT for degree level programmes. We therefore still accept any of the English tests listed for admission to this programme.

Pre-sessional courses

The University of Glasgow accepts evidence of the required language level from the English for Academic Study Unit Pre-sessional courses. We also consider other BALEAP accredited pre-sessional courses:

 

For further information about English language requirements, please contact the Recruitment and International Office using our enquiry form

How to apply

To apply for a postgraduate taught degree you must apply online. We cannot accept applications any other way.

Please check you meet the Entry requirements for this programme before you begin your application.

Documents

As part of your online application, you also need to submit the following supporting documents:

  • A copy (or copies) of your official degree certificate(s) (if you have already completed your degree)
  • A copy (or copies) of your official academic transcript(s), showing full details of subjects studied and grades/marks obtained
  • Official English translations of the certificate(s) and transcript(s)
  • One reference letter on headed paper
  • Evidence of your English language ability (if your first language is not English)
  • Any additional documents required for this programme (see Entry requirements for this programme)
  • A copy of the photo page of your passport (Non-EU students only)

You have 42 days to submit your application once you begin the process.

You may save and return to your application as many times as you wish to update information, complete sections or upload supporting documents such as your final transcript or your language test.

For more information about submitting documents or other topics related to applying to a postgraduate taught programme, check Frequently Asked Questions

Guidance notes for using the online application

These notes are intended to help you complete the online application form accurately; they are also available within the help section of the online application form. 

If you experience any difficulties accessing the online application then you should visit the Application Troubleshooting/FAQs page.

  • Name and Date of birth: must appear exactly as they do on your passport. Please take time to check the spelling and lay-out.
  • Contact Details: Correspondence address. All contact relevant to your application will be sent to this address including the offer letter(s). If your address changes, please contact us as soon as possible.
  • Choice of course: Please select carefully the course you want to study. As your application will be sent to the admissions committee for each course you select it is important to consider at this stage why you are interested in the course and that it is reflected in your application.
  • Proposed date of entry: Please state your preferred start date including the month and the year. Taught masters degrees tend to begin in September. Research degrees may start in any month.
  • Education and Qualifications: Please complete this section as fully as possible indicating any relevant Higher Education qualifications starting with the most recent. Complete the name of the Institution (s) as it appears on the degree certificate or transcript.
  • English Language Proficiency: Please state the date of any English language test taken (or to be taken) and the award date (or expected award date if known).
  • Employment and Experience: Please complete this section as fully as possible with all employments relevant to your course. Additional details may be attached in your personal statement/proposal where appropriate.

Reference: Please provide one reference. This should typically be an academic reference but in cases where this is not possible then a reference from a current employer may be accepted instead. Certain programmes, such as the MBA programme, may also accept an employer reference. If you already have a copy of a reference on letter headed paper then please upload this to your application. If you do not already have a reference to upload then please enter your referee’s name and contact details on the online application and we will contact your referee directly.

Application deadlines

  • Applicants who meet all the published entry requirements should apply by 11 September 2023
  • Applicants who do not yet meet the published entry requirements should apply by 17 August 2023
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