- Start date: October
- Accreditation: AACSB, EQUIS & AMBA
- Study mode and duration: 12 months part-time, online distance learning
Study with us
- gain a comprehensive skill set and expertise through input from three contributing departments
- use data analytics techniques within business contexts to become rounded problem-solvers
- benefit from a flexible distance learning study model
Why this course?
This distance learning course focuses on the uses of data analytics techniques within business contexts, making informed decisions about appropriate technology to extract knowledge from data and understanding the theoretical principles by which such technology operates.
The qualification is unique by bringing together essential skills from three departments across the University in order to address the needs of a fast-growing industry. It's jointly delivered by:
- Department of Management Science
- Department of Mathematics & Statistics
- Department of Computer & Information Sciences
This unique collaboration avoids the narrow interpretation of the subject offered by similar degrees and presents significant opportunities for businesses to recruit data analytics experts with high-level expertise and knowledge.
The aim of the PgCert in Data Analytics is to develop graduates who can use data analytics technology, understand the statistical principles behind the technologies and understand how to apply these technologies to solve business problems.
What you’ll study
This programme is designed to provide you with the fundamental technical analytics knowledge from all three departments. Computer & Information Sciences classes will cover core techniques including data mining and quantitative methods for data analysis as well as big data platforms. Mathematics class will ensure you gain strong computational skills while establishing a broad knowledge of statistical tools essential for analytics. Management Science classes will build the foundations of business skills including problem structuring as well as decision analysis, in addition to providing essential practical skills.
Learning & teaching
All classes are taught using material presented via the internet. Classes are supported by faculty members who also teach on our range of full-time courses. They will guide and support discussion via forums. You'll have full access to our user-friendly Virtual Learning Environment (VLE). Benefits of using the VLE include:
- anytime, anywhere learning
- access to tutors throughout your course
- continuously updated, dynamic, interactive online materials
- online group discussions
- live question & answer sessions
- live conferencing
Classes are assessed by written assignments and examinations. Examinations will take place at local centres.
Triple-accredited business school
Data Analytics in R
This class will introduce the R computing environment and enable you to import data and perform statistical tests. The class will then focus on the understanding of the least squares multiple regression model, general linear model, transformations and variable selection procedures.
Big Data Fundamentals
This class aims to endow students with an understanding of the new challenges posed by the advent for big data, as they refer to its modelling, storage, and access, along with an understanding of the key algorithms and techniques which are embodied in data analytics solutions.
Big Data Tools & Techniques
The aim of this class is to endow students with an understanding of the new challenges posed by the advent for big data, as they refer to its modelling storage, and access, and to expose them to a number of different big data technologies and techniques, showing how they can achieve efficiency and scalability, while also addressing design trade-offs and their impacts.
Business & Decision Modelling
This course will provide the fundamental business modelling skills such as generic problem-solving and basic methodological issues, as well as a good detailed overview of decision analysis techniques relevant to analytics, including decision trees and multi-criteria decision analysis.
Optimisation for Analytics
This course will provide the fundamental optimisation knowledge necessary to the students, such as network optimisation and integer programming, and develop their practical understanding by modelling challenging problems and understanding algorithmic aspects.
Pass degree, or non-UK equivalent, in mathematics, the natural sciences, engineering, or economics/finance. Applications from those with other degrees are also encouraged if you have demonstrated a good grasp of numerical/quantitative subjects.
|English language requirements|
Students whose first language is not English must have a minimum of 6.5 IELTS score, with no individual score lower than 5.5. Get more information about the English language requirements for studying at Strathclyde.
Fees & funding
All fees quoted are for part-time courses and per academic year unless stated otherwise.
Please note: the fees shown are annual and may be subject to an increase each year. Find out more about fees.
How can I fund my course?
Scottish and non-UK EU postgraduate students
Scottish and non-UK EU postgraduate students may be able to apply for support from the Student Awards Agency Scotland (SAAS). The support is in the form of a tuition fee loan and for eligible students, a living cost loan. Find out more about the support and how to apply.
Students coming from England
Students ordinarily resident in England may be to apply for postgraduate support from Student Finance England. The support is a loan of up to £10,280 which can be used for both tuition fees and living costs. Find out more about the support and how to apply.
Students coming from Wales
Students ordinarily resident in Wales may be to apply for postgraduate support from Student Finance Wales. The support is a loan of up to £10,280 which can be used for both tuition fees and living costs. Find out more about the support and how to apply.
Students coming from Northern Ireland
Postgraduate students who are ordinarily resident in Northern Ireland may be able to apply for support from Student Finance Northern Ireland. The support is a tuition fee loan of up to £5,500. Find out more about the support and how to apply.
We've a large range of scholarships available to help you fund your studies. Check our scholarship search for more help with fees and funding.
The aim of the course is to develop graduates who can use data analytics technology, understand the statistical principles behind the technologies and understand how to apply these technologies to solve business problems.
Graduates will be able to bridge the various knowledge domains that are relevant for tackling data analytics problems as well as being able to identify emerging themes and directions within data analytics. Graduates will display abilities across the three component disciplines.
Strathclyde Business School
Strathclyde Business School was founded in 1948 and is a pioneering, internationally renowned academic organisation with a reputation for research excellence.
One of four faculties forming the University of Strathclyde, SBS is a triple-accredited business school (AACSB, EQUIS and AMBA) and was the first business school in Scotland to achieve this accolade in 2004. The Business School is home to seven subject departments and a number of specialist centres, all of which collaborate to provide a dynamic, fully-rounded and varied programme of specialist and cross-disciplinary courses.
Strathclyde Business Network
As a postgraduate student at Strathclyde Business School, you may choose to join the Strathclyde Business Network, a student-led initiative that facilitates interaction with business and industry leaders.
The Network aims to foster knowledge sharing, facilitate discussion and enable networking opportunities with the very best business professional in industry. Every year the Network organises Glasgow Business Summit, which is the first-ever student-led business conference in Scotland and brings together students with leading businesses from across the UK.
Have you considered?
We've a range of postgraduate taught and Masters courses similar to this on which may also be of interest.