Data$Science$and$Big$Data$Analytics$
Optional)Year)3)module,)Term)2)(0.5)credits))
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Overview$Data)Science)and)Big)Data)Analytics)are)exciting)new)areas)that)
combine)scientific)inquiry,)substantive)expertise,)coding,)and)statistical)
knowledge.)One)of)the)main)challenges)for)businesses)and)policy)makers)when)
using)big)data)is)to)find)people)with)the)appropriate)skills.)Data)Science)is)no)
longer)only)the)domain)of)computer)scientists)and)engineers.)Good)Data)Science)
requires)experts)that)combine)substantive)knowledge)with)data)analytical)skills,)
which)makes)it)a)prime)area)for)social)scientists)with)an)interest)in)quantitative)
methods.$)
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Course$outline$
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1.)Introduction)to)big)data)and)data)intelligence)
•! Big$data$overview;$What$is$data$science;$Big$data$analytics$in$public$and$
private$sectors;$$
•! Data$insights$and$business$intelligence;$How$can$data$analytics$improve$
business$decisions$and$policy$making;$Stages$of$a$data$project.$
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2.)Data)preparation)and)manipulation)
•! Databases:$MapReduce,$Hadoop,$SQL$and$NoSQL;$$
•! Data$cleaning;$Record$linkage;$Information$extraction.$
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3.)Statistical)Inference)
•! Probability;$Distributions;$Modelling;$$
•! Experimental$design.$
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4.)Supervised)learning)
•! Linear/Logistic$regression;$Regularisation;$$
•! Decision$trees;$Naive$Bayes;$Support$Vector$Machines.$$
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5.)Unsupervised)learning))
•! Cluster$analysis;$Principal$components,$curves$and$surfaces;$$
•! Google$PageRank$algorithm.$
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6.)Unstructured)data)analytics)
•! Technologies$and$tools;$$
•! Text$analytics;$Topic$modelling;$Web$mining.$
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7.)Social)Network)Analysis)
•! Complexity;$Social$graph$data;$$
•! Network$analysis;$Topological$data$analysis.$
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8.)Presenting)and)communicating)
•! Data$visualisation;$$
•! Visual$data$analytics;$Graph$analytics.$
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9.)Data)Insights)
•! Integrating$quantitative$evidence$into$decisionQmaking$and$policyQmaking.$
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10.)Hackathon)competition)
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