University of Strathclyde
Our MSc in data analytics is designed to create rounded data analytics problem-solvers.
This 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.
You'll gain a comprehensive skill set that will enable you to work in a variety of sectors using a blended learning approach that combines theory, intensive practice and industrial engagement.
Strathclyde's MSc in data analytics is unique by bringing together essential skills from three departments, Management Science, Mathematics & Statistics, and Computer & Information Sciences (CIS), in order to address the needs of a fast-growing industry.
This collaboration avoids the narrow interpretation of this subject offered by competitor institutions and presents significant opportunities for businesses to recruit data analytics experts with a high-level expertise and knowledge.
Second-class Honours degree, or 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
If you’re a national of an English speaking country recognised by UK Border Agency (please check most up-to-date list) or you have successfully completed an academic qualification (at least equivalent to a UK bachelor's degree) in any of these countries, then you do not need to present any additional evidence.
For others, the department requires a minimum overall IELTS score of 6.5 (with no individual component below 5.5 (or equivalent)). Pre-sessional courses in English are available.
If you're from a country not recognised as an English speaking country by the United Kingdom Border Agency (UKBA), please check English requirements before making your application.
The course will have a duration of 1 year, with two semesters of classes (120 credits in total) followed by an MSc dissertation project (60 credits) during the summer.
The class Data Analytics in Practice (20 credits) will be run over both semesters to provide you with a practical environment to apply methodological learnings from other classes into challenging projects from industry.
Semester 1 will additionally consist of five 10-credit core modules as listed under 'Course Content' which will provide the technical background to students. The contributions in Semester 1 will be split evenly between three departments.
This semester is designed to provide you with the fundamental technical analytics knowledge from all three departments.
- Computer & Information Sciences courses will cover core techniques including machine learning and data mining as well as data visualisation and big data platforms
- Mathematics courses will ensure you gain strong computational skills while establishing a broad knowledge of statistical tools essential for analytics
- Management Science courses will build the foundations of business skills including problem structuring as well as decision analysis, in addition to providing essential practical skills.
Semester 2 will additionally consist of a 10-credit core module as well as 40 credits worth of elective modules. To ensure breadth of knowledge, you'll be required to choose electives from at least two departments. This semester is designed to extend your core skills and provide you with opportunities through a broad range of electives to specialise in areas that you are particularly interested to excel.
The only technical core class will provide you with a thorough theoretical and practical understanding of optimisation techniques essential for data analytics, whereas each of the three departments will offer four to five elective courses, the majority of which are accessible to everyone on the course without any prerequisites. The final component of the MSc course will be a summer dissertation project, which can be completed either through a client-based project or a desk-based research project, depending on your interests. You will submit your dissertation in September to complete your degree requirements (pending any resits).
You will have optional opportunities to complete your MSc summer dissertation projects in client-based projects, where a number of host organisations will be arranged by the department. These projects will be normally unpaid, however, all costs such as travel and accommodation will be covered by the host organisation if out of town.
The taught modules on the programme introduce you to a variety of tools, techniques, methods and models. However, the practical reality of applying analytical methods in business is often far removed from the classroom. Working with decision-makers on real issues presents a variety of challenges.
For example, data may well be ambiguous and hard to come by, it may be far from obvious which data analytics methods can be applied and managers will need to be convinced of the business merits of any suggested solutions. While traditional teaching can alert students to such issues, understanding needs to be reinforced by experience.
This is primarily addressed by the core module ‘Data Analytics in Practice’, which takes place over both semesters. Every year, case studies and challenging projects are presented to our students by various organisations.
|Qualification||Study mode||Start month||Fee||Course duration|
|MSc||Full-time||September 2017||£ 9,500 per (home fees)||12 months|
|MSc||Full-time||September 2017||£ 18,000 per (International)||12 months|
|Campus name||Town||Postcode||Region||Main campus||Campus||Partner|
|University of Strathclyde||Glasgow||G1 1XQ||Scotland|
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