Program Overview
Our MSci Actuarial Science and Data Science is an Integrated Masters course that will teach you the art of turning risk into opportunity with the understanding of visualising data in actuarial applications and beyond. Such a skillset is crucial for the growing market for experts in data science with the collection and analysis of data being crucial to understanding how to improve, create and guide products and services across the globe.
Our MSci Actuarial Science and Data Science course covers the syllabus of many core subjects of the Institute and Faculty of Actuaries. Depending on your choice of optional modules, and upon sufficient attainment, this can lead to exemptions from the professional exams CS1, CS2, CM1, CM2, CB1 and CB2. Our attractive blend of actuarial science and data science will equip you with an understanding of real-world financial issues, efficient use of experimental design to provide fast and less expensive solutions, and computing skills essential for entering the actuarial and data science profession.
You’ll be taught theory and methods used by professional actuaries; on how to apply mathematical and statistical skills to minimise financial risk when the stakes are high, in areas such as commerce, government, insurance and finance. You’ll be provided with the crucial basis of core skills in data base programming and management, in developing data processing pipelines and in organising and analysing large and massive data sets. And you’ll be introduced to and use programming language Python and R for statistical analysis and data visualisation. In your third and fourth year, analysing data and methods in group projects will be essential capstone modules for the learning outcomes of the course.
Topics include:
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Contingencies, risk management and survival analysis
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Computer science and programming
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Statistics and operations research
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Artificial intelligence, databases and information retrieval
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Ethical issues around the use and processing of data
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Specialist skills in the areas of big data, data analytics and data science
Our Integrated Masters will give you the opportunity to fast-track your degree and complete your final year in nine months compared with a regular MSc which usually takes twelve months. Combining your undergraduate and postgraduate study in one degree will give you a strong theoretical background as well as specialist expertise through independent research. This combination makes graduates from our course attractive candidates for many employers.
Professional accreditation
This programme is accredited to meet the educational requirements of the Chartered Mathematician designation awarded by the Institute of Mathematics and its Applications.
Why we're great.
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You have access to our ultramodern facilities in our STEM Centre.
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You join a community of scholars leading the way in technological research and development.
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We have active links with industry to broaden your employment potential and placement opportunities.
Our expert staff
Many of
our academics
have won national or regional awards for lecturing, and many of them are qualified and accredited teachers – something which is very rare at a university.
Our course teachers are expert academics conducting internationally excellent multidisciplinary research, with significant multi-year experience in consulting and practicing actuarial science. Our key actuarial science staff are Professor Spyridon Vrontos (specialising in actuarial and financial data science, predictive modelling and predictability), Dr Tolulope Fadina (mathematical finance), Dr Junlei Hu (reinsurance and optimal risk transfer), Dr Peng Liu (applied probability and queueing systems), Dr Jackie Wong (Bayesian methods and survival analysis), and Dr John O’Hara (financial mathematics and machine learning in finance).
Specialist facilities
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In addition to teaching, we have a Maths Support Centre, which offers help to students on a range of mathematical problems. Throughout term-time, we can chat through mathematical problems either on a one-to-one or small group basis
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We have a dedicated social and study space for maths students in the department, which is situated in the STEM Centre
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We host regular events and seminars throughout the year
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Our students run a lively Mathematics Society, an active and social group where you can explore your interest in your subject with other students
Your future
Demand for skilled graduates in the areas of mathematics, big data, data science and actuarial science is growing rapidly in both the public and private sector, and there is a predicted shortage of data scientists with the skills to understand and make commercial decisions based on the analysis of big data. It is predicted by the US Department of Labor that the employment of actuaries is expected to grow faster than any other occupation, making it a great prospect for a graduate job.
Aside from a rewarding career as an actuary, clear thinkers are required in every profession, so the successful mathematician has an extensive choice of potential careers.
We also work with our University's Student Development Team to help you find out about further work experience, internships, placements, and voluntary opportunities.
Program Outline
Course structure
We offer a flexible course structure with a mixture of core/compulsory modules, and optional modules chosen from lists.
Our research-led teaching is continually evolving to address the latest challenges and breakthroughs in the field. The course content is therefore reviewed on an annual basis to ensure our courses remain up-to-date so modules listed are subject to change.
We understand that deciding where and what to study is a very important decision for you. We’ll make all reasonable efforts to provide you with the courses, services and facilities as described on our website. However, if we need to make material changes, for example due to significant disruption, or in response to COVID-19, we’ll let our applicants and students know as soon as possible.
Components
Components are the blocks of study that make up your course. A component may have a set module which you must study, or a number of modules from which you can choose.
Each component has a status and carries a certain number of credits towards your qualification.
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Status
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What this means
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Core
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You must take the set module for this component and you must pass. No failure can be permitted.
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Core with Options
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You can choose which module to study from the available options for this component but you must pass. No failure can be permitted.
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Compulsory
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You must take the set module for this component. There may be limited opportunities to continue on the course/be eligible for the qualification if you fail.
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Compulsory with Options
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You can choose which module to study from the available options for this component. There may be limited opportunities to continue on the course/be eligible for the qualification if you fail.
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Optional
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You can choose which module to study from the available options for this component. There may be limited opportunities to continue on the course/be eligible for the qualification if you fail.
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The modules that are available for you to choose for each component will depend on several factors, including which modules you have chosen for other components, which modules you have completed in previous years of your course, and which term the module is taught in.
Modules
Modules are the individual units of study for your course. Each module has its own set of learning outcomes and assessment criteria and also carries a certain number of credits.
In most cases you will study one module per component, but in some cases you may need to study more than one module. For example, a 30-credit component may comprise of either one 30-credit module, or two 15-credit modules, depending on the options available.
Modules may be taught at different times of the year and by a different department or school to the one your course is primarily based in. You can find this information from the
module code
. For example, the module code HR100-4-FY means:
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HR
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100
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4
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FY
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The department or school the module will be taught by.
In this example, the module would be taught by the Department of History.
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The module number.
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The
UK academic level
of the module.
A standard undergraduate course will comprise of level 4, 5 and 6 modules - increasing as you progress through the course.
A standard postgraduate taught course will comprise of level 7 modules.
A postgraduate research degree is a level 8 qualification.
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The term the module will be taught in.
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AU
: Autumn term
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SP
: Spring term
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SU
: Summer term
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FY
: Full year
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AP
: Autumn and Spring terms
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PS:
Spring and Summer terms
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AS:
Autumn and Summer terms
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Year 1
Year 2
Year 3
Final Year
This module will allow you to build your knowledge of differentiation and integration, how you can solve first and second order differential equations, Taylor Series and more.
View Calculus on our Module Directory
You'll be introduced to a range of important concepts which are used in all areas of mathematics and statistics. This module is structured in such a way that during learning sessions you'll develop good practical understanding of these concepts via discussion and exercises, and have an opportunity to ask questions. Theory is introduced via recorded videos and the corresponding notes published on Moodle, and also via recommendations of textbooks. The contact hours are dedicated to interactive activities such as lab exercises and flipped lecture quizzes; also you will have some additional formative tests in Moodle.
View Matrices and Complex Numbers on our Module Directory
How do you apply the addition rule of probability? Or construct appropriate diagrams to illustrate data sets? Learn the basics of probability (combinatorial analysis and axioms of probability), conditional probability and independence, and probability distributions. Understand how to handle data using descriptive statistics and gain experience of R software.
View Statistics I on our Module Directory
Introduction to Finance is designed to give you an introduction to the wider finance subject area ass well as firm foundation for further studies in finance. You’ll gain a overview of the financial system, instruments and markets, and ideas about finance concepts and problems. The topics covered include investment companies, return and risk, and behavioural finance.
You’ll develop and be able to transmit knowledge about the financial system, instruments and markets and ideas about finance concepts and problems at an introductory level; be aware of, at an introductory level, different ways of thinking about and analysing financial phenomena; and, reflecting the principles of how we approach Finance at Essex Business School, you’ll gain an appreciation of the role that finance plays in society as whole.
View Introduction to Finance on our Module Directory
This module introduces students to the core economic principles and how these can be used in a business environment to help decision making and behaviour.
In the first half of the module, it provides the fundamental concepts of microeconomics that explain how economic agents make decisions and how these decisions interact. In the second half, the module explores the principles underlying macroeconomics that explain how the economic system works, where it fails and how decisions taken by economic agents affect the economic system.
This module covers 100% of required material in the Business Economics (CB2) syllabus accredited by the Institute and Faculty of Actuaries (IFoA ).
View Economics for Actuaries on our Module Directory
This module introduces you to programming skills in the context of a range of mathematical modelling topics. Mathematical modelling skills will be an important focus alongside learning how to structure and implement codes in both Matlab and R. A key part of the module will be investigative open-ended computational modelling studies at both the group and individual level.
View Mathematical and Computational Modelling on our Module Directory
What skills do you need to succeed during your studies? And what about after university? How will you realise your career goals? Develop your transferable skills and experiences to create your personal profile. Reflect on and plan your ongoing personal development, with guidance from your personal advisor within the department.
View Mathematics Careers and Employability on our Module Directory
What instruments are used by companies to raise finance and manage financial risk? What is the role of financial institutions operating in financial markets? What are the techniques of financial accounting? How do you use spreadsheets in financial analysis? Examine and develop the concepts and elements of corporate finance.
View Finance and Financial Reporting on our Module Directory
How do you compare different income streams? You will be able to answer the question after studying this module which is critical in any financial decision making. In this module, all payments are assumed to be guaranteed and we will focus on the concept of valuing future monetary payments in terms of present. This module covers part of the CM1 course of the IFoA.
View Financial Mathematics on our Module Directory
In this module you'll be introduced to the basics of probability and random variables. Topics you will discuss include distribution theory, estimation and Maximum Likelihood estimators, hypothesis testing, basic linear regression and multiple linear regression implemented in R.
View Statistics II on our Module Directory
What are the principles of actuarial modelling? And what are survival models? Examine how calculations in clinical trials, pensions, and life and health insurance require reliable estimates of transition intensities/survival rates. Learn how to estimate these intensities. Build your understanding of estimation procedures for lifetime distributions.
View Survival Analysis on our Module Directory
How do you define simple assurance contracts? What practical methods are required to evaluate expected values from a contract? How can you calculate gross premiums and reserves of assurance and reserves? Understand the mathematical techniques that can calculate, model and value cashflows dependent on death, survival or other uncertain risks.
View Contingencies I on our Module Directory
How do you prove simple properties of linear space from axioms? Can you check whether a set of vectors is a basis? How do you change a basis and recalculate the coordinates of vectors and the matrices of mapping? Study abstract linear algebra, learning to understand advanced abstract mathematical definitions.
View Linear Algebra on our Module Directory
The subject of ordinary differential equations is a very important branch of Applied Mathematics. Many phenomena from Physics, Biology, Engineering, Chemistry, Finance, among others, may be described using ordinary differential equations. To understand the underlying processes, we have to find and interpret the solutions to these equations. The last part of the module is devoted to the study of nonlinear differential equations and stability. This module provides an overview of standard methods for solving single ordinary differential equations and systems of ordinary differential equations, with an introduction to the underlying theory.
View Ordinary Differential Equations on our Module Directory
Are you able to solve a small linear programming problem using an appropriate version of the Simplex Algorithm? Learn to formulate an appropriate linear programming model and use the MATLAB computer package to solve linear programming problems. Understand the methods of linear programming, including both theoretical and computational aspects.
View Optimisation (Linear Programming) on our Module Directory
What skills do you need to succeed during your studies? And what about after university? How will you realise your career goals? Develop your transferable skills and experiences to create your personal profile. Reflect on and plan your ongoing personal development, with guidance from your personal advisor within the department.
View Mathematics Careers and Employability on our Module Directory
This module will enable you to expand your knowledge on multiple statistical methods. You will learn the concepts of decision theory and how to apply them, have the chance to explore “Monte Carlo” simulation, and develop an understanding of Bayesian inference, and the basic concepts of a generalised linear model.
View Statistical Methods on our Module Directory
How do you formulate financial decision problems mathematically? And how do you identify an appropriate method of solution? Understand the basic models and mathematical methods underlying modern portfolio management. Assess the limitations of these models and learn to correctly interpret your results from calculations.
View Mathematics of Portfolios on our Module Directory
Why are arbitrage arguments important in modern finance? How can a binomial model evaluate derivatives? What are the main models for interest rates? Understand the mathematical techniques underlying the modelling of derivative pricing. Acquire skills in the development of pricing and risk management. Explore stochastic methods and credit risk.
View Financial Derivatives on our Module Directory
Ever considered becoming an Actuary? This module covers the required material for the Institute and Faculty of Actuaries CT4 and CT6 syllabus. It explores the stochastic process and principles of actuarial modelling alongside time series models and analysis.
View Stochastic Processes on our Module Directory
What methods are available to model cashflows that are contingent on competing risk? What techniques for discounted emerging costs can be used in pricing, reserving and assessing profitability? Study the methods and techniques used in pricing and valuation of insurance policies and products, putting emphasis on those involving multiple lives.
View Contingencies II on our Module Directory
Can you calculate confidence intervals for parameters and prediction intervals for future observations? Represent a linear model in matrix form? Or adapt a model to fit growth curves? Learn to apply linear models to analyse data. Discuss underlying assumptions and standard approaches. Understand methods to design and analyse experiments.
View Linear Regression Analysis on our Module Directory
This module will allow you to step out of the classroom and gain real experience in your selected branch of Mathematics that you could not gain from a lecture. You will be able to develop your ability to work independently on research and produce a project report on your topic of interest.
View Capstone Project: Mathematics on our Module Directory
What do you understand about Bayes’ theorem and Bayesian statistical modelling? Or about Markov chain Monte Carlo simulation? Focus on Bayesian and computational statistics. Understand the statistical modelling and methods available. Learn to develop a Monte Carlo simulation algorithm for simple probability distributions.
View Bayesian Computational Statistics on our Module Directory
What skills do you need to succeed during your studies? And what about after university? How will you realise your career goals? Develop your transferable skills and experiences to create your personal profile. Reflect on and plan your ongoing personal development, with guidance from your personal advisor within the department.
View Mathematics Careers and Employability on our Module Directory
Our Advanced Capstone Projects are opportunities for students to study independently a topic in mathematics, statistics and related areas (such as mathematical physics, data science, modelling and so on) and develop skills such as writing reports and giving presentations. You will be monitored by a supervisor, who will periodically set tasks and discuss the progress of the work.
The key purpose of Advanced Capstone Projects is that you should be given the opportunity to show your strengths and be allowed a certain amount of freedom and leeway in how you complete the project. It will also provide opportunities for you to develop transferable communication, time- and task-management skills, through researching the topic and organising and producing the written and oral reports.
View Advanced Capstone Project: Actuarial Science, Data Science or Mathematics on our Module Directory
Humans can often perform a task extremely well (e.g., telling cats from dogs) but are unable to understand and describe the decision process followed. Without this explicit knowledge, we cannot write computer programs that can be used by machines to perform the same task. “Machine learning” is the study and application of methods to learn such algorithms automatically from sets of examples, just like babies can learn to tell cats from dogs simply by being shown examples of dogs and cats by their parents. Machine learning has proven particularly suited to cases such as optical character recognition, dictation software, language translators, fraud detection in financial transactions, and many others.
View Machine Learning on our Module Directory
COMPONENT 03: OPTIOL
Option(s) from list
(45 CREDITS)
COMPONENT 04: OPTIOL
Option(s) from list
(30 CREDITS)
Teaching
Courses are taught by a combination of lectures, laboratory work, assignments, and individual and group project activities
Group work
A significant amount of practical lab work will need to be undertaken for written assignments and as part of your learning
Assessment
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You are assessed through a combination of written examinations and coursework
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All our modules include a significant coursework element
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You receive regular feedback on your progress through in-term tests
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Courses are assessed on the results of your written examinations, together with continual assessments of your practical work and coursework
