MSc Data Science and its Applications

The MSc Data Science and its Applications is a conversion course designed for students with little prior experience of university-level mathematics and statistics. This course places students at the core of data science, with the application of theory and methods to real-world problems, including the use and exploitation of big data.

Overview

• Course: Data Science and its Applications
• Start date: October 2026, January 2027
• Study mode: Full-time, Part-time
• Duration: 1 year (full-time), 2 years (part-time)
• Location: Colchester Campus
• Based in: Mathematics, Statistics and Actuarial Science (School of)

Course Details

The course introduces students to programming with the R language and text analytics. Relational databases and SQL are developed and used for relevant applications from humanities, life sciences, linguistics, marketing, and social science. The course encourages statistical thinking by data visualisations and guides students to develop their creativity within a scientific framework.

Topics Covered

• Modelling experimental data
• Machine learning and decision making
• Applied statistics
• Combinatorial optimisation
• Statistical methods
• Stochastic processes

Expert Staff

The University of Essex is home to many of the world's top scientists, and the staff are driven by creativity and imagination as well as technical excellence. Specialist staff at Essex working on data science across departments include:

• Dr Yanchun Bao: longitudinal and survival analysis, causal methods, instrumental methods (Mendelian Randomization), covariance modelling, mediation analysis
• Professor Luca Citi: machine learning, learning from biological signals and data (EEG, etc)
• Professor Edward Codling: animal movement and dispersal, random walks and diffusion, path analysis of movement data, behaviour of animal groups, human crowd behaviour
• Dr Stella Hadjiantoni: estimation of large-scale multivariate linear models and applications, numerical methods for the development of recursive regularisation and machine learning algorithms, numerical linear algebra in statistical computing and data science, numerical methods for handling high-dimensional data sets
• Dr Andrew Harrison: bioinformatics, big data science
• Professor Berthold Lausen: biostatistics, classification and clustering, data science education, event time data, machine learning, predictive modelling
• Dr Osama Mahmoud: biostatistics, data science, machine learning, Mendelian Randomization
• Dr Yassir Rabhi: mathematical statistics, mathematical foundations of data science
• Professor Abdel Salhi: data mining, numerical analysis, optimisation
• Dr Dmitry Savostyanov: high-dimensional problems, tensor product decompositions
• Dr Alexei Vernitski: machine learning in mathematics; reinforcement learning applied to knot theory; mathematical education, and in particular, increasing motivation of learners of mathematics
• Professor Spyridon Vrontos: actuarial mathematics and actuarial modelling
• Dr Jackie Wong Siaw Tze: Bayesian estimation, MCMC methods
• Professor Xinan Yang: approximate dynamic programming, Markov decision process

Specialist Facilities

• All computers run either Windows 10 or are dual boot with Linux
• Software includes R, Python, SQL, Hadoop, and Sparc
• 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
• Collaboration with the Essex Institute of Data Analytics and Data Science (IADS) and the ESRC Business and Local Government (BLoG) Data Research Centre of the University of Essex
• The UK Data Archive and the Institute for Social and Economic Research (ISER) at Essex contribute to the internationally outstanding data science environment

Your Future

With a predicted shortage of data scientists, now is the time to future-proof your career. A successful career in data science requires you to possess truly interdisciplinary knowledge, and the staff ensure that you graduate with a wide-ranging, yet specialised, set of skills in this area. Data scientists are required in every sector, carrying out statistical analysis or mining data on social media. Graduates are highly sought after by a range of businesses and organisations and find employment in financial services, scientific computation, decision-making support, and government, risk assessment, statistics, education, and other areas.

Entry Requirements

UK Entry Requirements

• A 2.2 degree or international equivalent in one of the following subjects: Biology, Biostatistics, Chemistry, Economic Statistics, Economics, Finance, Marketing, Physics
• Or any other degree 2:2 or above which includes three modules from the list: Advanced Maths, Calculus, Engineering Maths, Maths, Probability, Statistics/Probability
• 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

The University of Essex accepts a wide range of qualifications from applicants studying in the EU and other countries.

Structure

Course Structure

The course is research-led, and the teaching is continually evolving to address the latest challenges and breakthroughs in the field. The structure below is representative of this course if taken full-time. If you choose to study part-time, the modules will be split across two years.

Components and Modules

• COMPONENT 01: CORE WITH OPTIONS (MA981-7-FY or MA983-7-SU) (60 credits)
• COMPONENT 02: COMPULSORY - Data Visualisation (15 credits)
• COMPONENT 03: COMPULSORY - Data analysis and statistics with R (15 credits)
• COMPONENT 04: COMPULSORY - Programming and Text Analytics with R (15 credits)
• COMPONENT 05: COMPULSORY - Databases and data processing with SQL (15 credits)
• COMPONENT 06: COMPULSORY - Modelling experimental and observational data (15 credits)
• COMPONENT 07: COMPULSORY WITH OPTIONS (CE156-7-AU or MA214-7-SP) (15 credits)
• COMPONENT 08: COMPULSORY WITH OPTIONS (MA336-7-SP or CE802-7-AU) (15 credits)
• COMPONENT 09: OPTIONAL - Option from list (15 credits)
• COMPONENT 10: COMPULSORY - Research Skills and Employability (0 credits)

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
• 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

Assessment

• On this course, you are assessed mostly by coursework and projects, but this does vary from module to module
• Some modules may also incorporate written examinations

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
• Study with close supervision by academic staff

Fees and Funding

Home/UK Fee

• Ł11,025

International Fee

• Ł23,875

Scholarships and Financial Support

There may be scholarships, bursaries, or discounts available to help with the cost of this course.

Fees and Funding Guide

Masters fees and funding information, Research (e.g., PhD) fees and funding information.

University of Essex

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Overview:

The University of Essex is a public research university located in Colchester, Essex, England. It is known for its strong academic reputation, particularly in the fields of social sciences, humanities, and law. The university offers a wide range of undergraduate and postgraduate programs, as well as short courses and apprenticeships.

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Services Offered:

The university provides a comprehensive range of services to its students, including:

Accommodation:

Guaranteed, affordable accommodation for new undergraduate and postgraduate students.

Student Support:

A variety of support services are available to students, including academic advising, career counseling, and mental health support.

Careers and Employability:

The university offers resources and programs to help students develop their career skills and find employment.

Essex Sport:

A wide range of sports facilities and activities are available to students, including fitness classes, performance sport, and scholarships.

Faith:

The university provides support for students of all faiths.

Cost of Living Support:

The university offers financial assistance to students who are struggling with the cost of living.

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Student Life and Campus Experience:

Students at the University of Essex can expect a vibrant and diverse campus experience. The university has a strong sense of community, with a variety of clubs, societies, and events to get involved in. The university also has a beautiful campus, with green spaces, lakes, and modern facilities.

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Key Reasons to Study There:

Strong Academic Reputation:

The university is consistently ranked highly in national and international rankings.

Excellent Research:

The university is a leading research institution, with a strong focus on innovation and impact.

Diverse and Inclusive Community:

The university is committed to creating a welcoming and inclusive environment for all students.

Excellent Student Support:

The university provides a wide range of support services to help students succeed.

Beautiful Campus:

The university has a beautiful campus, with green spaces, lakes, and modern facilities.

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Academic Programs:

The University of Essex offers a wide range of academic programs, including:

Undergraduate Programs:

The university offers a wide range of undergraduate programs in the arts, humanities, social sciences, law, business, and science.

Postgraduate Programs:

The university offers a wide range of postgraduate programs, including master's degrees, PhDs, and professional qualifications.

Short Courses and CPD:

The university offers a variety of short courses and continuing professional development programs.

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Other:

The university has three campuses: Colchester, Southend, and Loughton. The Colchester campus is the main campus and is located in a beautiful parkland setting. The Southend campus is located on the seafront and offers a more urban experience. The Loughton campus is home to the university's drama school, East 15 Acting School.

The university is also home to a number of research centers and institutes, including the Centre for Research in Entrepreneurship, Innovation and Management (REIMI) and the Human Rights Centre.