What is the MSc Data Science with Professional Placement?
The MSc Data Science with Professional Placement is a two-year degree studied at our Colchester Campus, started in October or January.
You will learn the techniques needed to model and manipulate data in order to guide the political, financial and social decisions that shape our modern society, economy growth and business success.
If you don’t want to complete a year on placement in industry, view our MSc Data Science, which you can also start in either October or January.
Why this course
The MSc Data Science with Professional Placement is an industry-focused degree aimed at meeting demand for graduates skilled in data science and analytics for the both private and public sectors, from government to health and from business to finance.
In your First Year, you will study a balance of solid theory and practical application to real-world problems at the core of data science, with a focus on exploiting Big Data.
In your Second Year, you will complete a placement with one of our industry partners, gaining crucial work experience and broadening your employability potential.
You will develop skills to use smart devices efficiently and apply statistical techniques and methods to interpret data in any context or industry.
Who should apply
Future data scientists and analysts
Graduates with a background in a mathematical or computational discipline
Those considering careers that can be revolutionised with data
Practical, analytic thinkers
What you’ll learn
Data: Learn how to visualise and analyse data
Applied: Explore applied regression, statistics and experimental data analysis
Professional practice: Gain the research and business skills needed for your research and professional career
Specialise: Tailor your degree through your choice of optional modules**,** including programming and machine learning
Your learning experience
Expert teaching: Learn from active researchers in data science and analytics, and award-winning lecturers qualified and accredited in mathematics education
Specialist facilities: Consult our Maths Support Centre one-to-one or in a group, and study in a dedicated social and study spaces for maths students in the STEM Centre
Research centres: Collaborate with the campus-based Essex Institute of Data Analytics and Data Science (IADS), the ESRC Business and Local Government (BLoG) Research Centre, the UK Data Archive and the Institute for Social and Economics Research (ISER)
Careers and outcomes
An MSc Data Science prepares for a future-proofed career as a data scientist or data analyst in a range of sectors, and in specialties such as:
Financial services
Scientific computation
Decision-making support
Risk assessment
Statistics
Education
Graduates also continue into postgraduate research through a PhD or MPhil.
Why we're great.
We are committed to developing the data scientists of the future.
Our interdisciplinary Institute for Data Analytics (IADS) researches data issues from the scientific and technological, to the sociological and legal.
We have active links with industry to broaden your employment potential and placement opportunities.
Our research-led teaching is continually evolving to address the latest challenges and breakthroughs in the field. The following modules are based on the current course structure and may change in response to new curriculum developments and innovation.
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 and in line with your contract with us. However, if we need to make material changes, for example due to significant disruption, we'll let our applicants and students know as soon as possible.
Components and modules explained
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.
Status
What this means
Core
You must take the set module for this component and you must pass. No failure can be permitted.
Core with Options
You can choose which module to study from the available options for this component but you must pass. No failure can be permitted.
Compulsory
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.
Compulsory with Options
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.
Optional
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.
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:
HR
100
4
FY
The department or school the module will be taught by.
In this example, the module would be taught by the Department of History.
This module is concerned with the application of regression models to the analysis of data. The underlying assumptions will be discussed and general results are obtained using matrices. You will be introduced to the standard approach to the analysis of normally distributed data using ANOVA, as well as the methods for the design and analysis of efficient experiments. The general methodology is extended to nonlinear regression, generalised regression and the analysis of multidimensional contingency tables.
In this module, you will study three application areas of statistics - multivariate methods, demography and epidemiology, and sampling, and how to apply and assess these methods in a variety of situations.
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.
In a world increasingly driven by data, the need for analysis and visualisation is more important than ever. In this module you will look at data through the eyes of a numerical detective. You will work on the lost art of exploratory data analysis, reviewing appropriate methods for data summaries with the aim to summarise, understand, extract hidden patterns and identify relationships. You will then work on graphical data analysis, using simple graphs to understand the data, but also advanced complex methods to scrutinise data and interactive plots to communicate data information to a wider audience.
For data analysis and visualisations you will use R-studio, and a combination of R-shiny applications and google visualisations for interactive plotting.
What skills do you need to succeed during your studies? What about after university? How will you harness your knowledge and soft skills to realise your career goals? This module helps you take an active role in developing transferrable skills and capitalising on your unique background. As well as broad reflection on your professional development, this module will help you explore different career directions and prepare you for the application process, supported by an advisor from within the department.
This module enables you to undertake a placement with an external Placement Provider. You will acquire effective work-based skills specific to your chosen field, and gain a detailed understanding of work processes. It’s an opportunity to put taught skills into practice and develop a network of industry professionals. Your placement is a sought-after contribution to your employability, giving you the tools employers look for in skilled graduates.
This module enables you to undertake a placement with an external Placement Provider. You will acquire effective work-based skills specific to your chosen field, and gain a detailed understanding of work processes. It’s an opportunity to put taught skills into practice and develop a network of industry professionals. Your placement is a sought-after contribution to your employability, giving you the tools employers look for in skilled graduates.
This is a dissertation module for MSc students. Students will be provided with a list of dissertation titles or may suggest their own, provided this is agreed with the dissertation supervisor.
You will complete a professional placement between the taught part of the course and the individual project. This professional placement allows you to gain work experience during your postgraduate studies.
Teaching
Postgraduate taught students in the School of Mathematics, Statistics and Actuarial Science typically attend two hours of lectures and one class or lab every week, but this will vary by module.
Core components can be combined with optional modules to gain either in-depth specialisation or a broad understanding.
Learn to use LATEX to produce a document as close as possible to those produced by professional mathematicians in terms of organisation, layout, and type-setting.
Our postgraduates are encouraged to attend conferences and seminars.
Assessment
Courses are assessed on the results of your written examinations, together with continual assessments of your practical work and coursework.
Dissertation
You will be provided with a list of dissertation titles or topics proposed by staff, though it may be possible to propose a project of your own.
Most dissertations are between 10,000 and 30,000 words in length. However, these are guidelines rather than mandatory word counts.
Study with close supervision by our academic staff.
Entry requirements
UK entry requirements
A 2:2 degree or international equivalent in one of the following subjects:
Applied Mathematics
Biostatistics
Computer Science
Economic Statistics
Economics
Mathematics
Operational Research
Pure Mathematics
Statistics
OR
Any other 2:2 degree in any subject which includes three modules from the below lists:
One module, from:
Advanced Maths (I/II/III)
Calculus (I/II/III) - AKA Mathematical Analysis
Engineering Maths (I/II/III)
Maths (I/II/III)
And
One module, from:
Advanced Maths (I/II/III)
Engineering Maths (I/II/III)
Maths (I/II/III)
Statistics or Probability
And
One additional relevant module, from:
Advanced Maths (I/II/III)
Algebra
Analysis
Complex Numbers
Differential Equations
Engineering Maths (I/II/III)
Maths (I/II/III)
Numerical Methods
Optimisation (Linear Programming)
Programming Language (R or MATLAB or Python)
Regression
Another module in Probability or Statistics
Stochastic Process
Applicants with a degree below 2:2 or equivalent will be considered dependent on any relevant professional or voluntary experience and previous modules studied.
International & EU entry requirements
We accept a wide range of qualifications from applicants studying in the EU and other countries. Get in touch with any questions you may have about the qualifications we accept. Remember to tell us about the qualifications you have already completed or are currently taking.
Sorry, the entry requirements for the country that you have selected are not available here. Please contact our Graduate Admissions team at pgquery@essex.ac.uk to request the entry requirements for this country.
English language requirements
If English is not your first language, we require IELTS 6.0 overall with a minimum
component score of 5.5 in all components.
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
The University uses academic selection criteria to determine an applicant’s ability to successfully complete a course at the University of Essex. Where appropriate, we may ask for specific information relating to previous modules studied or work experience.
Fees and funding
Home/UK fee
£11,025 per year
Year 2 fee is currently calculated at 20% of the Year 1 fee for the year in which the placement occurs.
International fee
£23,875 per year
Year 2 fee is currently calculated at 20% of the Year 1 fee for the year in which the placement occurs.
Fees will increase for each academic year of study.
We hold Open Days for all our applicants throughout the year. Our Colchester Campus events are a great way to find out more about studying at Essex, and give you 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
If the dates of our organised events aren’t suitable for you, feel free to get in touch by emailing tours@essex.ac.uk and we’ll arrange an individual campus tour for you.
We aim to respond to applications within two weeks. If we are able to offer you a place, you will be contacted via email.
For information on our deadline to apply for this course, please see our ‘how to apply' information.
Applicants with an undergraduate degree from our School of Mathematics, Statistics and Actuarial Science, or who are working towards one, should first contact our admissions staff: maths@essex.ac.uk.
Visit Colchester Campus
Set within 200 acres of award-winning parkland - Wivenhoe Park and located two miles from the historic city centre of Colchester – England's oldest recorded development. Our Colchester Campus is also easily reached from London and Stansted Airport in under one hour.
If you live too far away to come to Essex (or have a busy lifestyle), no problem. Our 360-degree virtual tour allows you to explore our University from the comfort of your home. Check out our Colchester virtual tour to see accommodation options, facilities and social spaces.
Chat to us
Got a question about this course? Chat with one of our academics in the School of Mathematics, Statistics and Actuarial Science.
At Essex we pride ourselves on being a welcoming and inclusive student community. We offer a wide range of support to individuals and groups of student members who may have specific requirements, interests or responsibilities.
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. The University would inform and engage with you if your course was to be discontinued, and would provide you with options, where appropriate, in line with our Compensation and Refund Policy.
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