Postgraduate study

Data and Decision Analytics (Online Learning) MSc

Awards: MSc

Study modes: Part-time

Online learning

Funding opportunities

The MSc Data and Decision Analytics programme prepares you to not only be able to analyse and digest data, but also to translate this into effective decision-making in this Big Data Age.

You will learn from world-class faculty how to apply cutting-edge business analytics and computing tools to make data-driven decisions in a plethora of business areas, such as:

  • strategy
  • marketing
  • finance
  • human resources
  • technology and equipment
  • operations

The courses provide you with methodological foundations and techniques, as well as applications in business, management, and economics.

To enhance your learning experience, develop your practical skills in analytics, and prepare you for the job market, the programme uses a combination of:

  • problem-based learning
  • case study-based learning
  • hands-on experience using prominent analytics software

You will be taught through a combination of:

  • recorded lectures/videos
  • online material or handouts
  • live virtual tutorials and Q&A sessions

The live sessions will allow you to actively engage with the learning material. Tutors are also available to provide advice/support sessions.

The online MSc in Data and Decision Analytics requires you to develop a deep level of analysis and understanding of the theory and processes of organisations and the business environment. This will be assessed through the completion of:

  • coursework
  • individual and group assessments
  • several pieces of individual and wholly original research

Through a balance of academic theory, crucial soft skills and the very latest industry practice, the programme provides opportunities for you to gain experience in planning, designing, executing, and reporting findings to a critical audience of specialists and non-specialists.

You will also gain experience through research processes, such as:

  • primary data collection from individuals
  • securing their cooperation and consent
  • analysing and evaluating data
  • framing recommendations
  • other methods of field study and data collection

You will learn how to communicate complex ideas and information in a coherent and structured manner throughout the programme courses. The programme also provides opportunities for you to engage with each other through group projects, discussion forums and peer assessment.

To receive an MSc degree in Data and Decision Analytics (online learning), you must complete:

  • 5 compulsory courses (80 credits)
  • at least 4 elective courses (40 credits)
  • the dissertation (60 credits)

The specific education aims of the programme are to:

  • enable you to recognise, understand and apply the language, theory, and models of the field of business analytics
  • foster your ability to critically analyse, synthesise and solve complex unstructured business problems related to data and decision analytics
  • encourage an aptitude for business improvement, innovation, and entrepreneurial action
  • instil a sense of ethical decision-making and a commitment to the long-run welfare of both organisations and the communities that they serve

The distinguishing feature of the MSc in Data and Decision Analytics (online learning) is twofold:

  • The programme will expose you to unique and balanced courses in the two most important analytics areas, namely, predictive and prescriptive. This enables you to not only make use of state-of-art machine learning methods to predict and understand data behaviours, but also to effectively apply decision optimisation to make better informed decisions as current business managers. The programme combines a plethora of state-of-the-art elective courses that enable you to make use of the most innovative and efficient methods to solve data and decision analytics problems.
  • Different from most online learning MSc programmes that are heavily based on asynchronous activities such as pre-recorded videos, ours is a balanced combination of pre-recorded lectures/videos along with synchronous (live) sessions such as tutorials and Q&As. This not only allows you to effectively engage with the course material and engage/ learn with each other, but also it provides a unique opportunity for reflection, discussion, feedback, and refinement towards more robust and authentic learning, which helps mitigate the transactional distance involved in distance education.

The programme is delivered fully online. Courses are composed of pre-recorded lectures and live online sessions.

Pre-recorded lectures will introduce the theoretical foundation of the given subjects. Live online sessions will mostly consist of tutorials and computer labs, in which hands-on experiences will allow you to practice the concepts covered by the videos. Even though there is a certain flexibility to watch the pre-recorded videos, the live online sessions will happen only once per week for each course i.e., there will not be multiple deliveries for each live session.

We are currently planning for these sessions to take place on Mondays and Tuesdays only. You can expect that there to be a maximum of 8 hours required during these two days a week to participate in live online sessions. The sessions will be scheduled to take place between 9am-6pm GMT. Depending on your location this may mean attending before or after your usual day of work. We appreciate though for some it may mean requesting flexible working from your employers to attend these.

You will need to set aside approximately 15 hours of time per week for reading, viewing, lectures, tutorials and assignments. This is an average across the duration of the entire year and it will vary depending on the course and also when assignments are due. Thus at peak times, you may need to put aside more time for your studies.

The programme’s materials (access to videos, slides, briefings, etc.) and resources will be available on the online platform called Learn. Each course has its own Learn webpage. Assessment will consist of coursework. You will submit their projects, essays, etc. through Learn/Turnitin. Feedback will be also provided through the same system.

You will be able to interact and engage with other students via discussion forums, group projects, and other online tools.

The online Data and Decision Analytics MSc is delivered part-time with a start date in September each year. The programme takes 24 months to complete and combines academic study with practical application.

Please note that live sessions will be scheduled to take place on Mondays and Tuesdays during term time (c. 20 weeks each year). These live sessions will be a maximum of 8 hours per week and scheduled 9am-6pm GMT.

The programme encompasses a number of core courses and your studies will culminate with a dissertation.

Core courses

80 credits of the following core courses:

  • Applied Machine Learning (20 credits)
  • Applied Decision Optimisation (20 credits)
  • Data Analysis and Statistics for Business (20 credits)
  • Storytelling in Data and Decision Analytics (10 credits)
  • Python Programming (10 credits)

Option courses

40 credits of the following option courses:

  • Text-Mining (10 credits)
  • Deep Learning (10 credits)
  • Decision Optimisation under Uncertainty (10 credits)
  • Multicriteria Decision Analysis (10 credits)
  • Simulation (10 credits)
  • Heuristic Optimisation (10 credits)

Option courses are subject to change and demand. We cannot guarantee that all option courses will run each year and occasionally there will be last-minute amendments after this date due to unforeseen circumstances such as staff illness.

The content of individual courses and the programme for any given degree are under constant academic review in light of current circumstances and may change from time to time, with some programmes and courses being modified, discontinued, or replaced.


60 credits of the following compulsory course:

  • Dissertation in Data and Decision Analytics

Find out more about compulsory and optional courses

We link to the latest information available. Please note that this may be for a previous academic year and should be considered indicative.

AwardTitleDurationStudy mode
MScData and Decision Analytics24 MonthsPart-timeProgramme structure 2023/24

By the end of the programme, you will be able to:

  • understand and critically apply the concepts and methods of business analytics
  • identify, model, and solve decision problems in different settings
  • interpret results/solutions and identify appropriate courses of action for a given managerial situation, whether a problem or an opportunity
  • create viable solutions to decision-making problems

Organisations hold more information about their business environments than ever before. Increasingly, these organisations are recognising the role of data in gaining insights and out-thinking competitors. The worldwide big data analytics market was valued at USD 37.34 billion in 2018 and is anticipated to grow at a CAGR of 12.3% to arrive at USD 105.08 billion by 2027. This will inevitably lead to further growth of the market for employees in the area of analytics.

The MSc in Data and Decision Analytics will offer you, from a range of degree backgrounds, the opportunity to equip yourself with an artillery of concepts, methods and applications of data analytics along with hands-on and practical experience in applying them. It is not just about being able to analyse and digest the data available but to then translate this into effective decision-making.

In sum, we expect the programme to open a range of career pathways in analytics for our graduates or to allow them to progress further within their existing career. Roles we anticipate to be amongst these pathways include:

  • business consultants
  • business analysts
  • data analysts
  • business intelligence & analytics consultants
  • metrics & analytics specialists
  • analytics associates
  • solution architects
  • business process analysts
  • management consulting associates
  • operational research consultants

2023/24 and 2024/25 entry requirements

These entry requirements are for the 2023/24 and 2024/25 academic years and requirements for future academic years may differ. Entry requirements for the 2025/26 academic year will be published on 11 July 2024.

Entrance to our MSc programmes is strongly competitive. You can increase your chances of a successful application by exceeding the minimum programme requirements.

A UK 2:1 honours degree or its international equivalent in an area related to management science, operational research, statistics, econometrics, mathematics, physics, computer science, engineering, or business and management with a distinct quantitative content.

Your background should ideally include courses and/or experience gained in topics such as linear algebra, calculus, probability, statistics, and computer programming.

If you have a UK 2:1 honours degree or its international equivalent in an unrelated subject we may consider your application if you have relevant work experience.

Work experience is desirable but not mandatory.

All students are recommended to have their own laptop for this programme.

Credit transfer from the MicroMasters in Predictive Analytics*

We welcome applications from students who have successfully completed the University of Edinburgh's MicroMasters in Predictive Analytics. Learners who successfully completed the MicroMasters programme will be awarded 30 postgraduate credits towards our Data and Decision Analytics MSc (online).

Learners who meet all the entry requirements and are successfully admitted onto the MSc Data and Decision Analytics can expect that their MicroMasters coursework will count towards their degree, comprising 20 credits of the total 180 credits of the masters programme. 10 credits would be recognised for the course in Python Programming where there is a strong equivalence between the course content and the other 10 credits would act as a discount towards the elective courses on the programme.

The MicroMasters must have been completed within two years of starting on the Data and Decision Analytics MSc, with September 2024 the last entry date when the credits will be accepted. Completing the MicroMasters will not guarantee acceptance and the standard University admissions process and criteria will apply. Decisions on admission to the programme lie solely with the University.

If you would like the 20 credits to count towards recognised prior learning, when applying you should upload your MicroMasters certificate to your application.

Students from China

This degree is Band B.

(*Revised 12 January 2022 to add details of credit transfer from MicroMasters.)

International qualifications

Check whether your international qualifications meet our general entry requirements:

English language requirements

You must demonstrate a level of English language competency at a level that will enable you to succeed in your studies, regardless of your nationality or country of residence.

English language tests

We accept the following English language qualifications at the grades specified:

  • IELTS Academic: total 7.0 with at least 6.0 in each component.
  • TOEFL-iBT (including Home Edition): total 100 with at least 20 in each component. We do not accept TOEFL MyBest Score to meet our English language requirements.
  • C1 Advanced (CAE) / C2 Proficiency (CPE): total 185 with at least 169 in each component.
  • Trinity ISE: ISE III with passes in all four components.
  • PTE Academic: total 70 with at least 59 in each component.

Your English language qualification must be no more than three and a half years old from the start date of the programme you are applying to study, unless you are using IELTS, TOEFL, Trinity ISE or PTE, in which case it must be no more than two years old.

Degrees taught and assessed in English

We also accept an undergraduate or postgraduate degree that has been taught and assessed in English in a majority English speaking country, as defined by UK Visas and Immigration:

We also accept a degree that has been taught and assessed in English from a university on our list of approved universities in non-majority English speaking countries (non-MESC).

If you are not a national of a majority English speaking country, then your degree must be no more than three and a half years old at the beginning of your programme of study.

Find out more about our language requirements:


If you receive an offer of admission, either unconditional or conditional, you will be asked to pay a tuition fee deposit within 28 days to secure your place on the programme:

  • £1,500 (this contributes towards your tuition fees)

The fee does not include the cost of textbooks for core and option courses so you should budget an additional amount for this required expenditure.

As this is an online programme, you will also require, and need to budget for, relevant IT equipment and broadband internet in order to pursue your studies.

See the programme website for more information on fees and deposits.

AwardTitleDurationStudy mode
MScData and Decision Analytics24 MonthsPart-timeTuition fees

UK government postgraduate loans

If you live in the UK, you may be able to apply for a postgraduate loan from one of the UK’s government loan schemes.

The type and amount of financial support you are eligible for will depend on:

  • your programme
  • the duration of your studies
  • your tuition fee status

Programmes studied on a part-time intermittent basis are not eligible.

Other funding opportunities

Search for scholarships and funding opportunities:

Tuition fee discounts

We offer a 10% discount on postgraduate tuition fees for alumni who have graduated with an undergraduate degree from the University of Edinburgh.

We also offer a 10% discount on postgraduate tuition fees for students who have previously matriculated on a "Visiting Programme" as an undergraduate student and completed a minimum of one semester of study at the University of Edinburgh.

The Scholarship and Student Funding site provides a list of programmes not covered by the discount scheme.

Search for scholarships and funding opportunities:

  • University of Edinburgh Business School
  • 29 Buccleuch Place
  • Edinburgh
  • EH8 9JS

If the programme is not full by the final application deadline, we may be able to consider applications submitted after that date. If we are still accepting applications following the final deadline, we will clearly indicate that on the programme's application page.

You must submit one reference with your application.

You will be required to supply a number of documents as part of your application. This includes:

  • an official transcript
  • degree certificate
  • one reference
  • personal statement
  • English language qualification

Find out more about the general application process for postgraduate programmes:

Further information

  • University of Edinburgh Business School
  • 29 Buccleuch Place
  • Edinburgh
  • EH8 9JS