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Data Science course details

For those wanting some more detailed information about the structure of the Data Science degree course, this is the place to find it!

First year - Second year - Third Year - Administration

First year

The first year of the course provides the background knowledge and fundamental skills required to develop expertise in Data Science. Students cover topics in university-level mathematics and statistics, such as formal proof, mathematical reasoning and probability theory, and also take a range of modules in computer programming, algorithms and the design of information structures. In particular, students encounter programming in both Java and R. The core first-year modules (126 CATS) are:

CS118 Programming for Computer Scientists 15 CATS
CS126 Design of Information Structures 15 CATS
IB104 Mathematical Programming I 12 CATS
MA106 Linear Algebra 12 CATS
MA137 Mathematical Analysis 24 CATS
MA138 Sets and Numbers 12 CATS
ST104 Statistical Laboratory 12 CATS
ST115 Introduction to Probability 12 CATS
ST116 Mathematical Techniques 12 CATS

(MA = Mathematics, ST = Statistics, CS = Computer Science, IB = Warwick Business School)

Second year

In the second year, students further integrate the skills gained in their first year, developing their expertise in statistical inference, algorithm design and software engineering, whilst also building their communication and team working skills – thereby allowing them to operate effectively as data scientists. Core modules from Statistics and Computer Science account for 93 CATS, with students selecting at least 27 CATS of optional modules. A group project gives students practical experience of industrial software engineering. The core second-year modules are:

CS258 Database Systems 15 CATS
CS260 Algorithms 15 CATS
CS261 Software Engineering 15 CATS
ST202 Stochastic Processes 12 CATS
ST208 Mathematical Methods 12 CATS
ST218 Mathematical Statistics A 12 CATS
ST219 Mathematical Statistics B 12 CATS


A non-exhaustive list of optional modules is:

CS249 Digital Communications and Signal Processing 15 CATS
CS255 Artificial Intelligence 15 CATS
IB207 Mathematical Programming II 12 CATS
ST221 Linear Statistical Modelling 12 CATS


(ST = Statistics, CS = Computer Science, IB = Warwick Business School)

Third year

In their final year of study, students focus on applying the skills gained in a variety of problem domains, including in an individual project involving an extended analysis of a substantial data set (worth 30 CATS). They also develop a greater understanding of cutting-edge topics and issues in Data Science. In particular, students take at least 90 CATS of specialist optional modules. At least 60 CATS of these optional modules must come from Option List A, with at least 30 CATS from each of Computer Science and Statistics. The modules in Option List A are:

CS301 Complexity of Algorithms 15 CATS
CS331 Neural Computing
15 CATS
CS341 Advanced Topics in Algorithms 15 CATS
CS342 Machine Learning 15 CATS
CS346 Advanced Databases 15 CATS
ST301 Bayesian Decision Theory 15 CATS
ST323 Multivariate Statistics 15 CATS
ST333 Applied Stochastic Processes 15 CATS
ST337 Bayesian Forecasting 15 CATS
ST340 Programming for Data Science 15 CATS
ST343 Topics in Data Science 15 CATS


(ST = Statistics, CS = Computer Science)

Administration

The course is administered through the Statistics department which has a long track record of running the successful interdisciplinary MORSE degree. Students are assigned personal tutors from within the Statistics department. The new course is represented on both the Statistics and Computer Science departmental Student-Staff Liaison Committees.