2020 applicants
Undergraduate Course

BSc Data Science and Analytics

(Including Foundation Year)

Now In Clearing
BSc Data Science and Analytics

Overview

The details
Data Science and Analytics (Including Foundation Year)
I1GF
October 2020
Full-time
4 years
Colchester Campus
Essex Pathways

Data is the lifeblood of our society. From medicine to government offices, and market research to the environment, the collection and analysis of data is crucial to understanding how to improve, create and guide products and services across the globe.

Harvard Business Review recently described the job of Data Scientist as “the sexiest job of the 21st century”. Data science is about doing some detective work and carrying out the investigations needed to inform important decisions and to predict new trends. Technology is growing and evolving at an incredible speed, and both the rate of growth of data we generate and the devices we use to process it can only increase.

Our BSc Data Science and Analytics (including foundation year) is open to Home and EU students. It will be suitable for you if your academic qualifications do not yet meet our entrance requirements for the three-year version of this course and you want a programme that increases your subject knowledge as well as improves your English language and academic skills.

This four-year course includes a foundation year (Year Zero), followed by a further three years of study. During your Year Zero, you study four academic subjects relevant to your chosen course as well as a compulsory English language and academic skills module.

You are an Essex student from day one, a member of our global community based at the most internationally diverse campus university in the UK.

After successful completion of Year Zero in our Essex Pathways Department, you progress to complete your course with our Department of Mathematical Sciences.

At Essex, we help you to understand how utilising the speed and processing-power of computers can assist in using data to make better decisions. You discover the new methods and the smart, unusual questions needed to make sense of both numerical and textual data. Your course balances solid theory with practical application through exploring topics including:

  • Mathematical skills
  • Computer science and programming
  • Statistics and operations research
  • Artificial intelligence, databases and information retrieval
  • Ethical issues around the use and processing of data
  • Specialist skills in the areas of big data, data analytics and data science

A successful career in data science requires you to possess truly interdisciplinary knowledge, so we ensure that you graduate with a wide-ranging yet specialised set of skills in this area. You are taught mainly within our Department of Mathematical Sciences and our School of Computer Science and Electronic Engineering, but also benefit from input from our Essex Business School, and our Essex Pathways Department.

Data scientists are required in every sector, carrying out statistical analysis or mining data on social media, so our course can open the door to almost any industry, from health, to government, to publishing.

Our Department of Mathematical Sciences is genuinely innovative and student-focused. Our research groups are working on a broad range of collaborative areas tackling real-world issues. Here are a few examples:

  • Our data scientists carefully consider how not to lie, and how not to get lied to with data. Interpreting data correctly is especially important because much of our data science research is applied directly or indirectly to social policies, including health, care and education.
  • We do practical research with financial data (for example, assessing the risk of collapse of the UK’s banking system) as well as theoretical research in financial instruments such as insurance policies or asset portfolios.
  • We also research how physical processes develop in time and space. Applications of this range from modelling epilepsy to modelling electronic cables.
  • Our optimisation experts work out how to do the same job with less resource, or how to do more with the same resource.
  • Our pure maths group are currently working on two new funded projects entitled ‘Machine learning for recognising tangled 3D objects’ and ‘Searching for gems in the landscape of cyclically presented groups’.
  • We also do research into mathematical education and use exciting technologies such as electroencephalography or eye tracking to measure exactly what a learner is feeling. Our research aims to encourage the implementation of ‘the four Cs’ of modern education, which are critical thinking, communication, collaboration, and creativity.
Why we're great.
  • You join a community of scholars leading the way in technological research and development.
  • We are home to many of the world's top scientists and engineers in their field.
  • You have access to our ultramodern facilities at our new STEM building that provide real-world experience.
THE Awards 2018 - Winner University of the Year

Our expert staff

Today’s computer scientists are creative people who are focused and committed, yet restless and experimental. We are home to many of the world’s top scientists, and our staff are driven by creativity and imagination as well as technical excellence. We conduct world-leading research in areas such as explorative data analysis, classification and clustering, evolutionary computation, data visualisation and financial forecasting. Specialist staff working on data science and analytics include:

  • Dr Luca Citi – machine learning, learning from biological signals and data (EEG, etc)
  • Dr Hongsheng Dai – computational Bayesian statistics
  • Professor Maria Fasli – machine learning, adaptation, semantic information extraction, ontologies, data exploration, recommendation technologies
  • Professor Udo Kruschwitz – natural language processing, analysis textual/unstructured data, information retrieval
  • Professor Berthold Lausen – biostatistics, classification and clustering, data science education, event time data, machine learning, predictive modelling
  • Dr Aris Perperoglou – data analysis and data visualisation, statistical modelling and smoothing, survival analysis, clinical trials
  • Professor Abdel Salhi – data mining, numerical analysis, optimisation
  • Professor Edward Tsang – applied AI, constraint satisfaction, computational finance and economics, agent-based simulations
  • Dr Spyros Vrontos – actuarial mathematics and actuarial modelling
  • Dr Xinan Yang – approximate dynamic programming, Markov decision process

Specialist facilities

By studying within our Essex Pathways Department for your foundation year, you will have access to all of the facilities that the University of Essex has to offer, as well as those provided by our department to support you:

  • We provide computer labs for internet research; classrooms with access to PowerPoint facilities for student presentations; AV facilities for teaching and access to web-based learning materials
  • Our new Student Services Hub will support you and provide information for all your needs as a student
  • Our social space is stocked with hot magazines and newspapers, and provides an informal setting to meet with your lecturers, tutors and friends

Our School of Computer Science and Electronic Engineering also offers excellent on-campus facilities:

  • We have six laboratories that are exclusively for computer science and electronic engineering students. Three are open 24/7, and you have free access to the labs except when there is a scheduled practical class in progress
  • All computers run either Windows 10 or are dual boot with Linux
  • Software includes Java, Prolog, C++, Perl, Mysql, Matlab, DB2, Microsoft Office, Visual Studio, and Project
  • Students have access to CAD tools and simulators for chip design (Xilinx) and computer networks (OPNET)
  • We also have specialist facilities for research into areas including non-invasive brain-computer interfaces, intelligent environments, robotics, optoelectronics, video, RF and MW, printed circuit milling, and semiconductors.

Your future

Demand for skilled graduates in the areas of big data and data 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. And an incredible 88% of our Department of Mathematical Sciences and 88% of our School of Computer Science and Electronic Engineering students are in professional employment or postgraduate study within six months of graduating from Essex (DLHE 2017).

Our graduates in data science have been very successful in finding employment in the public sector, consulting, technology, retail, and utilities, while a number have gone on to postgraduate study or research.

Our recent graduates have gone on to work for a wide range of high-profile companies including:

  • Aviva
  • AXA
  • BT
  • Profusion
  • EDS
  • Mondaq
  • IBM
  • Royal Bank of Scotland
  • Accenture
  • Buck Consultants
  • Google
  • Force India F1

Our Schools have a large pool of external contacts, ranging from companies providing robots for the media industry, through vehicle diagnostics, to the transforming of unstructured data to cloud-based multidimensional data cubes, who work with us and our students to provide advice, placements and eventually graduate opportunities.

We also work with our University's Student Development Team to help you find out about further work experience, internships, placements, and voluntary opportunities.

“I knew I wanted to do data science after discovering that it was the perfect subject for people who enjoy both computing and maths. I decided to study at Essex because it was one of the few universities who offered a degree in data science; it was also one of the highest rated universities in the UK. I’m currently enjoying programming the most, purely because I love problem solving, but I’ve enjoyed all of the modules I have studied so far. All of my professors and lecturers are helpful – they devote a lot of their time to us as students.

“I want to travel once I have finished university and therefore work long-distance – which in today’s modern world is definitely possible! Essex partners with a lot of businesses and companies, and gives students opportunities to gain highly useful work experience through a placement year. I think studying at Essex will put me in a great place when I graduate.”

Andreas Loucas, BSc Data Science and Analytics student

Entry requirements

Clearing entry requirements

Specific entry requirements for this course in Clearing are not published here but for most of our degree courses you will need to hold a Level 3 qualification. If you are interested in applying and have already received your results, use our Clearing application form to apply for 2020 entry and find out if you are eligible. You will be asked to provide details of your qualifications and grades.

English language requirements

English language requirements for applicants whose first language is not English: IELTS 5.5 overall. Specified component grades are also required for applicants who require a Tier 4 visa to study in the UK.

Other English language qualifications may be acceptable so please contact us for further details. If we accept the English component of an international qualification then it will be included in the information given about the academic levels required. Please note that date restrictions may apply to some English language qualifications

If you are an international student requiring a Tier 4 visa to study in the UK please see our immigration webpages for the latest Home Office guidance on English language qualifications.

If you do not meet our IELTS requirements then you may be able to complete a pre-sessional English pathway that enables you to start your course without retaking IELTS.

Additional Notes

Our Year 0 courses are only open to UK and EU applicants. If you’re an international student, but do not meet the English language or academic requirements for direct admission to your chosen degree, you could prepare and gain entry through a pathway course. Find out more about opportunities available to you at the University of Essex International College.

Structure

Example structure

We offer a flexible course structure with a mixture of compulsory modules and options chosen from lists. Below is just one example of a combination of modules you could take. For a full list of optional modules you can look at the course’s Programme Specification.

Our research-led teaching is continually evolving to address the latest challenges and breakthroughs in the field, therefore all modules listed are subject to change.

Please note that depending on your entry grades you will take either Mathematics for Data Science or Linear Mathematics in your first year, but not both.

Essential Mathematics

Want to know the basic mathematical techniques of algebra? To understand calculus? To apply methods of differentiation and integration to a range of functions? Build the basic, then more advanced, mathematical skills needed for future study. Learn to solve relevant problems, choosing the most suitable method for solution.

View Essential Mathematics on our Module Directory

Mathematical Methods and Statistics

Develop your problem solving skills in this module, as you are introduced to Statistical and Mathematical concepts with a particular focus on mechanics. You become familiar with R software, one of the most widely used statistical analysis software in the world, and learn how to use it to analyse and interpret data. You study simple concepts and techniques like data description and distribution; before moving on to more complex topics and theories including Newton’s laws of motion and the concepts of Mechanical energy. While also covering everything from probability rules and hypothesis testing to advanced algebra – you will be well equipped to present your solutions and findings to an audience with no specialist knowledge of Statistics and Mechanics.

View Mathematical Methods and Statistics on our Module Directory

Computer Programming

How do you test and evaluate the operation of simple computer programs? Or develop a program using tools in the Python programming language? Study the principles of procedural computing programming. Examine basic programming concepts, structures and methodologies. Understand good program design, learn to correct coding and practice debugging techniques.

View Computer Programming on our Module Directory

Team Project Challenge

Our Team Project Challenge gives you the opportunity to develop a range of professional skills by working as part of a small student team on a specific project. The projects are research-based and incorporate the concepts of specifications, design, and implementation. You’ll learn about sustainability, project and time management, design, legal issues, health and safety, data analysis and presentation, team reporting, and self-evaluation. You’ll also develop skills such as critical thinking and problem solving, agility, leadership, collaboration across networks, and effective oral and written communication, as well as curiosity and imagination, all of which will enhance your knowledge, confidence and social skills necessary to innovate and succeed in a competitive global environment.

View Team Project Challenge on our Module Directory

Discrete Mathematics

This module will provide you with a foundation of knowledge on the mathematics of sets and relations. You will develop an appreciation of mathematical proof techniques, including proof by induction.

View Discrete Mathematics on our Module Directory

Statistics I

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 Programming

The aim of this module is to provide an introduction to the fundamental concepts of computer programming. After completing this module, students will be expected to be able to demonstrate an understanding of the basic principles and concepts that underlie the procedural programming model, explain and make use of high-level programming language features that support control, data and procedural abstraction. Also, they will be able to analyse and explain the behaviour of simple programs that incorporate standard control structures, parameterised functions, arrays, structures and I/O.

View Introduction to Programming on our Module Directory

Object-Oriented Programming

Want to become a Java programmer? Topics covered in this module include control structures, classes, objects, inheritance, polymorphism, interfaces, file I/O, event handling, graphical components, and more. You will develop your programming skills in supervised lab sessions where help will be at hand should you require it.

View Object-Oriented Programming on our Module Directory

Introduction to Databases

Databases are everywhere. They are employed in banking, production control and the stock market, as well as in scientific and engineering applications. For example, the Human Genome Project had the goal of mapping the sequence of chemical base pairs which make up human DNA. The result is a genome database. This module introduces the underlying principles of databases, database design and database systems. It covers the fundamental concepts of databases, and prepares the student for their use in commerce, science and engineering.

View Introduction to Databases on our Module Directory

Calculus

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

Statistics II

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

Optimisation (Linear Programming)

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

Survival Analysis

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

Matrices and Complex Numbers

Can you perform simple operations on complex numbers? How do you solve systems of linear equations using row operations? Can you calculate the determinant and inverse of a matrix? Understand the basics of linear algebra, with an emphasis on vectors and matrices.

View Matrices and Complex Numbers on our Module Directory

Data Structures and Algorithms

Data structures and algorithms lie at the heart of Computer Science as they are the basis for the efficient solution of programming tasks. In this module, students will study core algorithms and data structures, as well as being given an introduction to algorithm analysis and basic computability.

View Data Structures and Algorithms on our Module Directory

Databases and Information Retrieval

The aim of this module is to build on the foundations of data and information systems laid down in the first year, learn how to design and manage fully structured data repositories and explore the rather different principles and techniques involved in representing, organising and displaying unstructured information.

View Databases and Information Retrieval on our Module Directory

Artificial Intelligence

Artificial intelligence will be a great driver of change in the coming decades. This module provides an introduction to three fundamental areas of artificial intelligence: search, knowledge representation, and machine learning. These underpin all more advanced areas of artificial intelligence and are of central importance to related fields such as computer games and robotics. Within each area, a range of methodologies and techniques are presented, with emphasis being placed on understanding their strengths and weaknesses and hence on assessing which is most suited to a particular task.

View Artificial Intelligence on our Module Directory

Mathematics Careers and Employability

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

Modelling Experimental Data

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 Modelling Experimental Data on our Module Directory

Applied Statistics

How do you apply multivariate methods? Or demographical and epidemiological methods? And how do you apply sampling methods? Study three application areas of statistics – multivariate methods, demography and epidemiology, and sampling. Understand how to apply and assess these methods in a variety of situations.

View Applied Statistics on our Module Directory

Mathematics Careers and Employability

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

Information Retrieval

This module offers you an understanding of standard IR models, of their merits and limitations, and teaches you how to design and implement a standard information retrieval system. Discover the essential foundations of information retrieval and gain solid, applicable knowledge of state-of-the-art search technology. Explore advanced concepts of search applications such as personalisation, profiling and contextual search.

View Information Retrieval on our Module Directory

Exploratory Data Analysis and Data Visualisation (optional)
Nonlinear Programming (optional)

How do you apply an algorithm or numerical method to a problem? What are the advantages? And the limitations? Understand the theory and application of nonlinear programming. Learn the principles of good modelling and know how to design algorithms and numerical methods. Critically assess issues regarding computational algorithms.

View Nonlinear Programming (optional) on our Module Directory

Teaching

  • Our classes are run in small groups, so you receive a lot of individual attention
  • 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

  • In Year Zero, your assessed coursework will generally consist of essays, reports, in-class tests, individual or group oral presentations

Fees and funding

Home/EU fee

£9,250

International fee

£16,050

Fees will increase for each academic year of study.

Home and EU fee information

International fee information

What's next

Open Days

Our events are a great way to find out more about studying at Essex. We run a number of Open Days throughout the year which enable you to discover what our campus has to offer. You have the chance to:

  • tour our campus and accommodation
  • find out answers to your questions about our courses, student finance, graduate employability, student support and more
  • meet our students and staff

Check out our Visit Us pages to find out more information about booking onto one of our events. And if the dates aren’t suitable for you, feel free to book a campus tour here.

How to apply during Clearing

Once you’ve checked that we have the right course for you, applying couldn’t be simpler. Fill in our quick and easy Clearing application form with as much detail as you can. We’ll then take a look and get back to you with a decision. There’s no need to call us to apply; just do it all online.

Find out more about Clearing

Interviews

We don’t interview all applicants during Clearing, however, we will only make offers for the following course after a successful interview:

  • BA Multimedia Journalism
  • BSc Nursing (Adult)
  • BSc Nursing (Mental Health)
  • BA Social Work

The interview allows our academics to find out more about you, and in turn you’ll be able to ask us any questions you might have. Further details will be emailed to you if you are shortlisted for interview.


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The University makes every effort to ensure that this information on its programme specification is accurate and up-to-date. Exceptionally it can be necessary to make changes, for example to courses, facilities or fees. Examples of such reasons might include, but are not limited to: strikes, other industrial action, staff illness, severe weather, fire, civil commotion, riot, invasion, terrorist attack or threat of terrorist attack (whether declared or not), natural disaster, restrictions imposed by government or public authorities, epidemic or pandemic disease, failure of public utilities or transport systems or the withdrawal/reduction of funding. Changes to courses may for example consist of variations to the content and method of delivery of programmes, courses and other services, to discontinue programmes, courses and other services and to merge or combine programmes or courses. The University will endeavour to keep such changes to a minimum, and will also keep students informed appropriately by updating our programme specifications.

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