MSc Data Analytics and Technologies
MSc Data Analytics and Technologies
Award
MSc
Start Date
21/09/2026
Duration
24 months
Mode
Part-time
Location
University of Greater Manchester
Develop advanced expertise in data analytics, machine learning, and modern data technologies, preparing you for high-demand roles in data-driven organisations.
Course Overview
This MSc Data Analytics and Technologies programme is designed to develop advanced technical expertise in analysing, interpreting, and managing data within modern organisations. You will gain practical experience in areas such as data analysis, machine learning, data visualisation, and applied analytics, preparing you for roles in data science, business intelligence, and data-driven decision-making.The programme combines hands-on technical work with real-world datasets, enabling you to extract insights, build analytical models, and communicate findings effectively. You will work with industry-relevant tools and approaches, including modern data platforms, machine learning techniques, and cloud-based data processing.
Developed with input from industry, the programme equips you with both technical depth and professional skills, including problem-solving, communication, and critical thinking, enabling you to adapt to rapidly evolving technologies.
What you will learn
- Data analysis, visualisation, and statistical techniques
- Machine learning and AI methods, including NLP and GenAI
- Data engineering and modern data technologies
- Business analytics and data-driven decision-making
- Research, problem-solving, and professional practice
Would you prefer to complete your studies more quickly? We also offer this course by full-time study with a duration of 12 or 18 months. To complete your studies in 12 months, please visit our MSc Data Analytics and Technologies course search web page for details and to apply. Alternatively, to study this course full-time over 18 months, please visit our MSc Data Analytics and Technologies: Extended course search web page.
Highlights
- Hands-on experience with data analysis, machine learning, and AI techniques
- Industry-relevant modules including NLP, GenAI, and data mining
- Real-world datasets and applied project work
- Opportunities for industry engagement, hackathons, and data-focused challenges
- Strong focus on employability and practical skills development
Key Features
- Access to industry-recognised platforms and tools supporting data analytics and cloud-based data processing, including AWS resources where appropriate
- Practical experience with modern data tools, visualisation platforms, and machine learning techniques
- Opportunities to work on applied projects using real-world datasets
- Engagement with industry professionals through guest lectures and applied activities
- Supportive learning environment with strong focus on career development
Entry Requirements
- Normally, you should have successfully completed an honours degree (or equivalent) in a relevant subject and have appropriate work experience.
- The standard entry requirement for the course is a BSc (Hons) in a Computing-related area, usually with a first or upper second class classification. For applicants without a first or upper second, a lower second degree will be considered on a case-by-case basis (particularly for candidates with good relevant industrial experience).
- We'll be happy to consider your application if you have non-traditional entry qualifications and relevant experience or a suitable portfolio of work that we deem a reasonable substitute for the qualifications we typically accept for this course.
- Applicants from related disciplines with relevant technical or professional experience are encouraged to apply.
- We'll consider applications where appropriate work experience can be demonstrated in lieu of, or in addition to, the published academic qualifications in line with the University’s Recognition of Prior Experiential Learning (RPEL) procedures.
- You may be required to attend an interview and/or provide a portfolio of work.
- If English isn’t your first language, you’ll also need IELTS 6.0 with no less than 5.5 in any band (or equivalent). We also accept a range of other English language qualifications – please visit our English Language Requirements web page for more details.
Where changes are made to material information contained in this course description or a decision is taken to suspend a course between the offer of admissions and enrolment, we will inform applicants at the earliest possible opportunity and will outline the various options available to the applicant.
Career Opportunities
Graduates of this programme are well prepared for roles such as:
- Data Analyst
- Data Scientist
- Business Intelligence Analyst
- Machine Learning Engineer
- Data Engineer
The programme also provides a strong foundation for further specialist study or progression to doctoral research.
What can I do with this qualification?
Data analysts are in high demand across all sectors, and data analytics roles are diverse. You may be involved in looking for trends and patterns to help companies make business decisions, predict demand for goods or services, or check quality control standards in areas like food and drug testing. There are also many roles in marketing and marketing research; for instance, in opinion poll design and analysis, analysing trends in consumer feedback and search engine optimisation for websites.
Organisations in areas such as finance, consulting, manufacturing, pharmaceuticals, government and education all need professionals to help mine and analyse large datasets, draw conclusions and present these insights to managers so that they can drive the business forward. Big data has intensified the need for analysts who can create data dashboards, graphs and visualisations to communicate trends to business leaders and other stakeholders. Conversely, small and medium-sized enterprises need consultants to help them make business decisions based on their data on an ad hoc basis, so you could consider starting your own business to support their needs.
Completing this course will open a multitude of doors, and you'll be well prepared to seek employment or promotion, or become self-employed using the enterprise and innovation skills you've developed as part of the course. You'll also be invited to continue your education via the MPhil and PhD degrees available at the University of Greater Manchester.
Alternative career options
Graduates may also progress into related roles. Some of these roles may require relevant experience and/or postgraduate study. Some possibilities include:
- Data-driven consultancy
- Information systems management
- Technology and analytics project management
- Data governance and policy
- Teaching and academic research (with further study)
Fees & Funding
Home/EU Fees
No fee information is currently available, please contact the University of Greater Manchester’s Academic Fees team by emailing AcademicFees@greatermanchester.ac.uk for more information.
International Fees
No fee information is currently available, please contact the University of Greater Manchester’s Academic Fees team by emailing AcademicFees@greatermanchester.ac.uk for more information.
Bursaries
Click here for more information on our Master's Bursaries.
Important note regarding tuition fees: EU nationals who meet residency requirements (have settled or pre-settled status) may be eligible for 'Home' fee status. If you do not meet these residency requirements, overseas fees will apply. Irish citizens living in the UK or Ireland will be eligible for 'Home' fee status under the Common Travel Area arrangement. Please read the student finance for EU students web page on www.gov.uk for information.
Home Undergraduate Tuition Fee Adjustment
The tuition fee applicable to the first year of your programme of study is confirmed in your offer letter. The tuition fee set is based on the regulations and guidance in force at the time of offer but remains subject to adjustment in accordance with any government-approved inflationary increase. The University reserves the right to amend tuition fees for all years of study, including the first year, by no more than the maximum increase permitted under legislation and regulatory guidance issued by the UK Government and the Office for Students.
Where such increases are approved, they will not exceed the rate of inflation, as measured by an appropriate index such as the Consumer Prices Index (CPI), or any successor measure specified by government. The University will apply any adjustment consistently across affected student cohorts and will give reasonable notice to students of any confirmed change to the published fee before the start of the relevant academic year.
This approach ensures that tuition fees remain compliant with applicable legislation, proportionate to inflationary changes, and consistent with government policy linking permitted fee uplifts to the maintenance of high-quality education and outcomes. For more information, please refer to the government guidance at: gov.uk – Universities to deliver better outcomes in return for full fees.
Postgraduate and International Tuition Fee Adjustment
The tuition fee applicable to the first year of your programme of study is confirmed in your offer letter. The University reserves the right to amend tuition fees for subsequent years of study in accordance with its Course Fees Policy. Where such increases are approved, they will not exceed the rate of inflation, as measured by an appropriate index such as the Consumer Prices Index (CPI), or any successor measure specified by government. The University will apply any adjustment consistently across affected student cohorts and will give reasonable notice to students of any confirmed change to the published fee before the start of the relevant academic year.
How to apply
Home Applicants
You may apply directly to the University using the University's online application form. Please select your chosen start date from the list below:
You should have to hand:
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Details of the educational establishments you attended and dates
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Your certificates for the qualifications you are using to gain entry to the course – you will need to enter the completion date and upload copies
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Details of any employment history including name, address, dates and role
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Personal statement – this can be either input into the relevant field or uploaded separately
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Details including e-mail addresses of two referees, at least one of which should be someone who can provide an academic reference
Please make sure any documents you wish to upload in support of your application are in pdf or jpeg format. Personal statements may be word documents.
Please ensure your data is correct at each stage of the application before you proceed to the next page. If you use the back button at any time during the application, you should check the validity of the data you have already input.
If you experience difficulties during the application process, contact the Admissions Team on 01204 903394 or admissions-team@greatermanchester.ac.uk
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Apply online: University of Greater Manchester MSc Data Analytics and Technologies - 21 September 2026
International Applicants
International applications are not possible for this course
As an international student you are not allowed to study this course because of the restrictions on your visa.
We offer a wide range of full-time courses in lots of different subjects, many of our courses start in September and January. If you would like to see what courses are available please visit our Course Search.
Teaching & Assessment
Teaching is delivered on campus through a combination of lectures, seminars, and practical sessions, supported by digital learning resources. You can expect practice-based enquiry, self-directed study, lectures, seminars, tutorials, presentations and work-based learning. Scheduled sessions will be held in the evening, allowing full-time and part-time students to study together and offering opportunities for those working in professional/industrial environments to present live case studies.
It's important to realise that the time spent with a tutor during formally scheduled activities is only a small part of the learning time identified for a module. You'll also be expected to spend significant time in guided independent study, such as general background reading, preparing for seminar activities and working on assignments. We're committed to supporting you throughout your learning journey. Over time, our guidance will purposefully become less structured and prescriptive. This will encourage you to develop confidence and independence in your studies and take responsibility for managing your learning time as you increase autonomy.
The assessment strategy for the programme is designed to help you achieve the overall aims of the curriculum, as well as the learning outcomes for individual modules. As well as assessing your achievement, it helps to organise and develop your learning. Assessment feedback can help you build your skills and an understanding of your strengths and weaknesses.
The types of assessment you'll be required to complete fall into two general categories: formative and summative. Formative assessments help in learning and developing knowledge and skills. Summative assessments, on which grades are allocated, reflect the quality of the learning that has been achieved. Formative assessment will occur via tutorial discussion, group workshops including peer and tutor review, and guidance on work in progress. Formative feedback will be provided face-to-face via discussion, online or in written form. Summative assessments consist of both practical and applied theoretical work. These will include a range of assessments, including practical projects, written work, presentations and portfolios.
This programme adopts a blended learning and teaching style, including online delivery and engagement where appropriate.
Modules
The modules listed below may be a mixture of compulsory and optional. You may not have the opportunity to study all the modules shown as part of the course.
- Research Methods
- Project
- Professional Practice
- Data Analysis and Visualisation
- NLP and GenAI
- Data Mining and Machine Learning
- Business Analytics
- Health Informatics
- Marketing Analytics
Assessment methods
| Level | Assessment method |
|---|---|
| Level 1 | Coursework 100% |
Learning Activities
| Level | Activity |
|---|---|
| Level 1 | Guided independent study 83% Scheduled learning and teaching activities 17% |
The university will use all reasonable endeavours to deliver your course as described in its published material and the programme specification for the academic year in which you begin your course. The university considers changes to courses very carefully and the university will minimise any changes. Please be aware that our courses are subject to review on an ongoing basis and changes may be necessary due to legitimate staffing, financial, regulatory and academic reasons. The content of course modules and mode of associated assessments may be updated on an annual basis. This is to ensure that all modules are up-to-date and responsive to employment and sector needs. The published course material and the programme specification contain indicative ‘optional modules’ that may be subject to change due to circumstances outside of our control. For this reason, we cannot guarantee to run any specific optional module.
Related Courses
Programme Contacts
Disclaimer: The “Greater Manchester Way” represents our preferred teaching and learning approach; however, not all courses follow a block-teaching model. While course structures and delivery patterns may vary to meet Professional, Statutory and Regulatory Body (PSRB) requirements, all courses benefit from the GM Way approach to curriculum design and assessment. Applicants and students should refer to individual course specifications for the most accurate and up-to-date information.
