Why this course?
In the modern world information is everywhere – from the daily stream of financial data emerging from the world’s markets to worldwide internet traffic, personal health records, or simply your local newsagent’s sales figures for the last week.
Understanding this vast array of data is one of the key challenges we currently face and requires expertise in subjects such as mathematics, statistics and computing.
Data Analytics is the science of examining raw data using advanced computing technologies. It's growing to be a fundamental part of modern business and industry.
In fact, in their recent report, The Tech Partnership and SAS UK stated that “Data is the 'new oil'" and that developing talent in data analytics will allow us to refine that oil to power the UK information economy. They also reported that the demand for graduates will skills in data analytics will surge in the coming years.
This new degree will provide you with these cutting edge skills, enabling you to tackle problems in dynamic business environments. It will make you well placed for an exciting and rewarding career in an industry that is set to expand.
What you’ll study
This joint Honours programme is taught in partnership between the Department of Mathematics & Statistics and the Department of Computer & Information Sciences.
Each year contains compulsory classes and some years include either optional classes and/or elective classes.
Years 1 & 2
Mathematics, statistics and computer science are studied. In addition to core mathematical methods, you'll study:
- probability theory
Computer science classes include:
- machines, languages & computation
- information & information systems
- programming foundations
- logic & algorithms
- user & data modelling
Years 3 & 4
Classes can be chosen focus on topics such as:
- experimental design
- risk analysis
- survey analysis
- dynamic modelling
- network analysis
- computer programming
- software engineering
- artificial intelligence
- web and mobile applications
- information access & mining
- the theory of computation
The final-year project may be carried out in either subject. We work with several companies and organisations to provide suggestions for student projects. These can be either individual or group final-year projects.
Each department has teaching rooms which provide you with access to modern teaching and computer equipment and are conducive to student learning. The undergraduate common room gives you a modern and flexible area which is used for individual and group study work and also a relaxing social space.
Many data analysis software packages will be used, including those widely used in industry.
Current students are taking the following classes, and we expect the syllabus to be similar to this in future years.
Machines, Languages & Computation
This class will help you achieve a broad knowledge of the essence of computation and computational systems, as embodied by the notions of computable functions, formal languages and recursion, logic and computability and abstract machines.
Information & Information Systems
This class will help you understand a broad knowledge of information systems and how information is created, used and disseminated within an information society.
This class will provide you with a solid foundation in the principles of computer programming. On completing this class you should have the necessary skills to be able to design, build and test a small system in a high-level language (Java in the current incarnation of the class).
Introduction to Calculus
You'll study the basic concepts and standard methods of mathematical notation and proof, polynomial equations and inequalities, sequences and series, functions, limits and continuity, differentiation and integration.
Applications of Calculus
The fundamental concepts of calculus (differentiation and integration) presented in Applications of Calculus will be examined in more detail, extended to a larger class of functions by means of more sophisticated methods, including an introduction to complex numbers and variables, all demonstrated in application to practical problems including solving basic first and second-order differential equations.
Geometry & Algebra
This class will present some basic ideas and techniques of statistics while introducing some essential study skills.
This class will highlight connections between geometry and algebra and how they inform each other. It will also include the introductory treatment of vectors and matrices, in particular to their role in linear and affine transformations in 2D and 3D.
Logic & Algorithms
This class will further your skills in object-oriented programming, provide knowledge of key abstract data types along with their implementation and usage, and to provide experience in the development of larger scale software and an introduction to design.
Your main goal is to be able to develop larger programs with specialized data structures and utilizing APIs from a specification, and being able to ensure and show how the system they developed matches the specification.
This class will equip you with the tools to model and measure computation. To build on the module Machines, Languages and Computation, and develop further understanding of the mathematical foundations of computation. To foster an analytical and empirical appreciation of the behaviour of algorithms and the use of abstract data types.
User & Data Modelling
This class will provide you with a critical appreciation and understanding of how to model user activities and the data to support them, together with how to implement systems and databases to support user activities.
Probability & Statistical Inference
Mathematical & Statistical Computing
Presentation of the basic concepts of probability theory and statistical inference will be covered to provide you with the tools to appropriately analyse a given data set and effectively communicate the results of such analysis.
This class will introduce you to the R computing environment. It'll enable you to use R to import data and perform statistical tests, allow you to understand the concept of an algorithm and what makes a good algorithm and will equip you for implementing simple algorithms in R.
This class will give an introduction to the basic ideas of linear algebra, such as matrices and determinants, vector spaces, bases, eigenvalues and eigenvectors.
The class will present the basic ideas, techniques and results for differentiation of two and three variables, and differentiation along curves, surfaces and volumes of both scalar and vector fields.
Building Software Systems
Inference & Regression Modelling
This class will extend and deepen your understanding of the analysis, design and implementation of software systems; to provide further experience in the activity of designing and implementing non-trivial systems; and to enable you to demonstrate practical competence in a group environment.
Your goal is the development in a group setting of significant systems from scratch aiming not just at any solution but a good solution, and to be introduced to more general Software Engineering topics.
Stochastics & Financial Econometrics
This class will:
- review the concepts of probability distributions and how to work with these
- present approaches to parameter estimation, focusing on maximum likelihood estimation, bootstrap estimation, and properties of estimators
- present hypothesis testing procedures, including classical likelihood ratio tests and computer-based methods for testing parameter values, and goodness-of-fit tests.
- introduce and provide understanding of the least squares multiple regression model, general linear model, transformations and variable selection procedures
- present use of R functions for regression and interpretation of R output
You'll be introduced to the basic concepts of random phenomena evolving in time, from two complementary points of view: probabilistic modelling and data-driven analysis. Presentation of underlying ideas of simple stochastic processes, time series models, and the associated probability theory and statistical techniques will be covered. In addition to applications of the methods to financial and economic systems, including modelling, data analysis, and forecasting.
You're required to take 20 credits of optional classes from those listed below.
Foundations of Artificial Intelligence
Programming Language Definition & Implementation
Pre-requisites: Advanced Programming, Logic & Algorithms.
This class will help to give you a broad appreciation of the scale and nature of the problems within Artificial Intelligence and to a detailed understanding of some of the fundamental techniques used to address those problems.
Web Applications Development
The class will provide familiarisation with the definition of programming language syntax and semantics, and the translation of these definitions into an implementation of a programming language.
Pre-requisites: Advanced Programming, User & Data Modelling.
This class will give you an understanding of the technologies used in the development of N-tier Internet-based applications.
Mobile App Development
Pre-requisites: Basic programming skills, as might be gained by taking the class Programming Foundations or a similar introductory programming class.
To aim is to provide you with skills in basic functional programming and experience in integrated deployment of those skills.
Pre-requisites: Advanced Programming
You should gain a good understanding of the issues in developing for mobile environments, approaches to handling these issues and skills in developing for a widespread mobile platform.
Communicating Mathematics & Statistics
This class provides you with experience of the skills required to undertake project work, and to communicate the findings in written and oral form using a variety of sources, such as books, journals and the internet.
This class will allow you to demonstrate practical and documentary competence. You'll also be expected to give a demonstration of your work.
You're required to take optional classes from those listed below to ensure that the curriculum contains no fewer than 40 credits in each subject. Students should refer to relevant programme regulations in the University Calendar regarding class selection requirements and credits in order to meet the programme requirements.
Please note that not all classes will be available every year.
List AStatistical Modelling & Analysis
Applied Statistics in Society
This class will provide you with a range of applied statistical techniques that can be used in professional life.
Mathematical Introduction to Networks
You'll be introduced to a range of modern statistical methods and practices used in industry, commerce and research, and will develop skills in your application and presentation.
This class will demonstrate the central role network theory plays in mathematical modelling. It'll also show the intimate connection between linear algebra and graph theory and how to use this connection to develop a sound theoretical understanding of network theory. Finally, it'll apply this theory as a tool for revealing structure in networks.
Students will learn new statistical methodology and apply it to real data from medical research studies, with an emphasis on the interpretation of the statistical results in the context of the medical problem being investigated. This skill is necessary for the application of statistics to medical data and differs from the traditional, standard interpretation of statistical textbook problems.
List BSoftware Architecture & Design
Theory of Computation
This class aims to:
- enable you to understand the challenges of advanced software design and the issues associated with large-scale software architectures, frameworks, patterns and components
- develop your understanding of the tools and techniques that may be used for the automatic analysis and evaluation of software
Building on the previous material in software development, you'll extend and formalise your abilities in the area of computational complexity.
Information Access & Mining
This class will allow you to understand the fundamentals of information access and information mining. The class will cover a range of techniques for extracting information from textual and non-textual resources, modelling the information content of resources, detecting patterns within information resources and making use of these patterns.
Advanced Functional Programming
Understanding the mathematical structures arising in advanced functional programs as mediated by the following concepts: type classes and constructor classes, monoids, functors, applicative functors, monads and monad transformers, arrows, comonads, inductive and coinductive types, recursion patterns including folds and unfolds, continuations, and generalised algebraic data types.
Learning & teaching
Several lecturers also work for Government organisations. Through these links you'll have the opportunity to work on real-life problems and analyse real data from these organisations.
Required subjects are indicated following minimum accepted grades.
Year 1 entry: AABB or ABBBC (Maths A, Advanced Higher Maths recommended)
Year 2 entry: AB (Maths A, Computing Science B, involving an appropriate programming language)
Year 1 entry: BBB (Maths B)
Typical entry requirements: ABB
Year 2 entry: ABB (Maths A, Computer Science, involving an appropriate programming language)
Typical entry requirements: AAA
32 (Maths HL6, Computer Science, involving an appropriate programming language)
Year 1 entry: relevant HNC with strong mathematical content, B in Graded Unit
Year 2 entry: not offered
Deferred entry is accepted.
We want to increase opportunities for people from every background. Strathclyde selects our students based on merit, potential and the ability to benefit from the education we offer. We look for more than just your grades. We consider the circumstances of your education and will make lower offers to certain applicants as a result.
Find out if you can benefit from this type of offer.
Fees & funding
How much will my course cost?
Rest of UK
Assuming no change in Rest of UK fees policy over the period, the total amount payable by undergraduate students will be capped. For students commencing study in 2017/18, this is capped at £27,750 (with the exception of the MPharm and Integrated Masters courses); MPharm students pay £9,250 for each of the four years. Students studying on Integrated Masters degree programmes pay an additional £9,250 for the Masters year with the exception of those undertaking a full-year industrial placement where a separate placement fee will apply.
Course materials & costs
Class materials (lecture notes and exercise sheets) for the majority of Mathematics & Statistics classes are available free to download. For some classes, students may need access to a textbook. Textbook costs are typically in the £20-60 price range. These prices are dependent on format (e-book, soft or hardback) and whether bought new or second hand.
PVG scheme (Protection of Vulnerable Groups)
Third-year Maths and Teaching students will need to pay for the full price of a PVG membership scheme.
£40 returnable deposit for PRS handsets.
Please note: All fees shown are annual and may be subject to an increase each year. Find out more about fees.
How can I fund my studies?
Students from Scotland and the EU
If you're a Scottish or EU student, you may be able to apply to the Student Award Agency Scotland (SAAS) to have your tuition fees paid by the Scottish government. Scottish students may also be eligible for a bursary and loan to help cover living costs while at University.
For more information on funding your studies have a look at our University Funding page.
Students from England, Wales & Northern Ireland
We have a generous package of bursaries on offer for students from England, Northern Ireland and Wales
You don’t need to make a separate application for these. When your place is confirmed at Strathclyde, we’ll assess your eligibility.
Have a look at our scholarship search for any more funding opportunities.
International Students (Non UK, EEA)
We have a number of scholarships available to international students. Take a look at our scholarship search to find out more.
We have a wide range of scholarships available. Have a look at our scholarship search to find a scholarship.
Graduates with skills in data analytics are in huge demand across all sectors, both nationally and internationally. This demand is predicted to increase in future. The Tech Partnership and SAS UK report forecasted demand to increase by 160% between 2013 and 2020.
Graduates will be well placed for a high-powered career as a data analyst, or data scientist, for example, in online information providers such as Google and Yahoo, social media, banking, insurance and retail industries – both online and high-street.