Get essential training in probability, statistics, mathematics and computing tools for the visualization and analysis of large datasets. It will enable you to become a competent and confident data modeller and interpreter, assisting management to make data-driven decisions. Data Science is for the student who wants to grasp the required IT and modeling skills to analyse data. It can also prepare you for future postgraduate study in the field. By pursuing study in data science, graduates will be highly sought-after by employers as the race to gain a competitive edge in the data arena intensifies. From asset management to pharmaceuticals, retail to insurance, the future is bright for any aspiring data scientist. The degree has been designed by the LSE (London School of Economics and Political Science).
Graduate Diploma STRUCTURE
Two core/compulsory courses
IS2184 Information systems management
ST3189 Machine learning
Two full courses (or the equivalent), no more than one of which may have the prefix IS, chosen from:
EC2020 Elements of econometrics
MT2116 Abstract mathematics
MT2175 Further linear algebra (half course)
MT2176 Further calculus (half course)
MT3040 Game theory (half course)
MT3041 Advanced mathematical analysis (half course)
MT3042 Optimisation theory (half course)
MT3043 Mathematics of finance and valuation (half course)
MT3170 Discrete mathematics and algebra
ST2133 Advanced statistics: distribution theory (half course)
ST2134 Advanced statistics: statistical inference (half course)
ST2187 Business analytics, applied modelling and prediction
ST3188 Statistical methods for market research
IS2182 Innovating digital systems and services
IS3159 Research project in digital innovation
IS3167 Management and innovation of e-business
IS3183 Management and social media
Students wishing to take Graduate Diplomas in subjects including Economics, Finance and Management will be taking courses which assume familiarity with introductory economics, mathematics and statistics. Students without this background are advised to undertake some preliminary study, which can often be most effectively achieved through taking a course in those subjects
Weekday Programme Duration – 1 year
1-5 years (Graduate Diploma)
Programme intensity indicators for a Graduate Diploma
Students need to ensure that they are sufficiently qualified to undertake the programme of their choice, given that some of the material covered within the programmes require subject specific knowledge. For ease of reference programmes have been categorised in to three groups.
|Standard||Requires only the general standard of an undergraduate degree or equivalent||Digital Innovation|
|Standard +||Familiarity of specific core subjects at the standard of first-year undergraduate required||Business Analytics|
|Technical*||Strong background in mathematics/statistics beyond A/L’s required||Data Science|
What is a Graduate Diploma?
Graduate Diplomas are bachelor’s, or undergraduate level qualifications that have been specifically designed for graduates who would like an additional bachelor’s level qualification but do not want to commit to a full second degree.
What is the value add in following a Graduate Diploma?
Graduate Diploma’s are highly valued by students who want to acquire a university level education in a subject that is unrelated to their first degree, either to enhance employment prospects or proceed to a postgraduate or other advanced qualification.
What is the duration of a Graduate Diploma?
Graduate Diploma programmes are designed so that they can be completed and examined in a single year of full time study.
How many modules does a Graduate Diploma in Data Science consist of?
Four complete modules must be successfully completed in order to be awarded with a Graduate Diploma, which will be classified as Distinction, Merit or Pass. (no more than 1 resit of a full or half module)
What is the subject-specific knowledge required to follow a Graduate Diploma in Data Science?
This Graduate Diploma requires a strong background in mathematics/statistics, going beyond A-level, is required. Thus applicants for these diplomas are expected to have strong understanding of mathematics and are advised also to have some familiarity with economics. Level: Technical*
What is the acceptable Quantitative Degree/Award title/s when considering applicable Technical Qualifications in following a Graduate Diploma in Data Science?
Computer Science, Economics, Engineering, Finance, Mathematics, Medicine, Physics, Psychology, Quantitative Management, Quantitative Finance, Social Sciences with Quantitative Methods or Statistics.
What are the mathematical skills considered to be sufficient in following a Graduate Diploma in Data Science?
Algebra, Algorithms, Business Mathematics, Business Statistics, Calculus, Computer Mathematics, Differentials, Engineering Mathematics, Geometry, Mathematics, Quantitative Methods, Quantitative Techniques, Statistics or Trigonometry.