Data Science and Computational Intelligence MSc

 

Course Code

EECT044

Location

Coventry University (Coventry)

 

Study mode

Full-time
Part-time
Sandwich

Duration

1 year full-time
2 years part-time
2 years full-time with work placement

Start date

September 2022
January 2023


Course overview

Study level: Postgraduate

This master’s course aims to respond to the demand for data scientists with the skills to develop innovative computational intelligence applications, capable of analysing large amounts of complex data to inform businesses decisions and market strategies.

  • The main theme throughout this course is automatic big data processing and information retrieval through machine learning, neural network and evolutionary computing.
  • We aim to cover how to apply cutting-edge machine learning techniques to analyse big datasets, assess the statistical significance of data mining results and perform advanced data mining tasks.
  • We will introduce you to important frameworks which may include Hadoop Map Reduce, Spark, applications of relational databases and NoSQL databases in combination with easy to use and powerful development tools such as Python, R and Matlab.
  • We will look at emerging theories, practices, approaches and management of distributed and intelligent computing systems, examining a wide range of case studies to see how applications have been developed and for what purposes, such as steganography detection system for colour stego images.
  • The focus of the course is on applications of data science methods and tools, combined with computational intelligence techniques for data-driven problem solving including the analysis, interpretation and visualisation of complex data, which is in increasing demand in fields such as marketing, pharmaceutics, finance, transportation, medicine, and management.
  • You will have the option to apply for a ‘work placement’ opportunity2, designed to further develop your skills and knowledge with the aim of maximising your employability prospects. See modules for more information.
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Global ready

An international outlook, with global opportunities

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Teaching excellence

Taught by lecturers who are experts in their field

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Employability

Career ready graduates, with the skills to succeed

Why you should study this course

Big data is enabling companies to unlock previously hidden information in areas ranging from customer behaviour to how their businesses function, providing vital insight that can affect the profitability and sustainability of an organisation.

  • In a world where technology is advancing at a rapid pace, data-driven scientific discovery represents one of the most exciting developments – already making a huge impact in the social and services sectors enabled by the Internet of Things (IoT) and cloud computing.
  • This course is designed to equip you with the skills and expertise in the emerging big data mining techniques required for the analysis, interpretation and visualisation of complex, high-volume, high-dimensional, structured and unstructured data from a variety of sources.
  • We aim to provide an understanding of data science and computational intelligence, including specialist knowledge in machine learning, neural networks, evolutionary and fuzzy computing, data and web mining, and information retrieval, as well as important development tools and platforms.
  • Through practical activities, industry input and a focus on skills development, we seek to foster an informed, flexible and critical approach to problem solving, giving you the confidence, professionalism, knowledge and skills to adapt to modern technological environments.
  • Enjoying high levels of student satisfaction for our teaching, we offer modern facilities4, including specialist computing labs with high-performance hardware along with the utilisation of industry-standard software and collaboration coding platforms, such as Github.
  • You will be given the chance to work alongside staff currently conducting research in the fields of: computational intelligence; intelligent information modelling and retrieval; distributed systems and modelling; interactive worlds; digital security and forensics; and biomedical technologies.(Please note staff may be subject to change).

What you'll study

Over the course of your studies, you will study several mandatory modules.

Ultimately, you will be expected to apply the knowledge and skills you have learned by undertaking an in-depth individual project which may be industry-based or undertaken in collaboration with one of the university research groups. Guided by an expert tutor, this project helps to develop your research and practical skills while also gaining professional data science experience.

Past student projects have included analysing big data for the movie industry; helping in assessing oil wells to evaluate extraction costs; recognising customer emotion through face gestures; analysing text sentiment in a social media exchange; performing automatic scene labelling and object recognition; and designing a robotics controller for helping the elderly.

Modules

  • This module aims to provide you with an introduction to machine learning techniques, the associated concepts, and applications. Machine learning is the process whereby systems learn by identifying structures and patterns within data.

    Compulsory

  • The aim of this module is to provide you with a sound knowledge of the theoretical and practical underpinnings of data management systems in centralised and distributed environments.

    Compulsory

  • The main aim of this module is to provide you with the widely used statistical methods, and their applications, in Data Science. On successful completion of this module, you should have learned the fundamental principles of probability theory and statistics, including distribution theory.

    Compulsory

  • In this module, you will be exposed to a range of common information retrieval methods, from theory to practice. There is an emphasis on text retrieval and a brief outline of multimedia information retrieval.

    Compulsory

  • This module aims to introduce you to the current management and visualisation methods for Big Data. Cutting edge techniques will be taught which will enable you to discover patterns, relationships and associations in big data sets.

    Compulsory

  • This module provides an introduction to the concepts used in neural networks and their application in solving real-world problems. Neural networks have been successfully used in a wide range of applications including visual image processing, speech and natural language processing, medical diagnosis and prognosis, emotion recognition, bioinformatics and computational biology, robotics, control etc.

    Compulsory

  • The main aim of this module is to provide you with more advanced concepts in machine learning, focusing on statistical methods for supervised and unsupervised learning. The module is structured around recent developments on Gaussian processes for regression and classification, Latent Dirichlet Allocation models for unsupervised text modelling and topic modelling, and Probabilistic graphical models as a powerful framework for representing complex domains using probability distributions.

    Compulsory

  • In this preparatory module, you will identify a suitable topic of study and project supervisor. You will then exercise and extend your skills in gathering, understanding, and critically evaluating literature; assessing and acting on relevant ethical and legal issues; and applying planning processes for the undertaking of a significant piece of work.

    Compulsory

  • The project is intended to provide you with the opportunity to demonstrate competence in applying the knowledge and skills acquired during the taught part of the course. The project may be a solution to a practical industry requirement or focus on a research topic. The module will require investigation and research as core activities, leading to analysis, final summations, and insightful recommendations. The project will culminate in a comprehensive, thorough, and professional report, documenting the approach, conduct and outcomes of the project, further supported with a critical review of the project conduct and management.

    Compulsory

With work placement pathway

The ‘With work placement’ opportunity2 enables you to apply in semester 1 for an optional work placement of up to 12 months, extending the duration of your master’s to 24 months. The placement provides an opportunity for you to develop expertise and experience in your chosen field with the aim of enhancing your employability upon graduation. The work placement would take place in semesters 3, 4 and 5.

Please note that the optional placement modules will incur an additional tuition fee of £4,000. Placement opportunities may also be subject to additional costs, visa requirements being met, subject to availability and/or competitive application. Work placements are not guaranteed but you will benefit from the support of the Talent Team in trying to find and secure an opportunity. Find out more about the work placement option.

We regularly review our course content, to make it relevant and current for the benefit of our students. For these reasons, course modules may be updated.


How you'll learn

Teaching methods include:

  • Lectures
  • Seminars
  • Tutorials
  • Presentations
  • Group projects
  • Workshops
  • Practical laboratory sessions

This course can be studied on a full-time or part-time basis. Whilst we would like to give you all the information about our part-time offering here, it is tailored for each course each year depending on the number of part-time applicants. Therefore, the part-time teaching arrangements vary. Please request information about studying this course part-time.


Teaching contact hours

The number of contact hours may vary from semester to semester, however, on average, it is likely to be around 12 contact hours per week in the taught semesters.

Additionally, you will be expected to undertake significant self-directed study of approximately 35 hours each week, depending on the demands of individual modules.

Your project-based semester will be supervisor supported, self-directed study in the region of 45 hours per week as well as supervisor meetings around 0.5 hours per week.


Assessment

This course will be assessed using a variety of methods which could vary depending upon the module. Assessment methods may include coursework, essays, project, group work and formal examination.

The Coventry University assessment strategy aims to ensure that our courses are fairly assessed and allows us to monitor student progression towards achieving the intended learning outcomes.


International experience opportunities

If you have a desire to travel, it is possible to spend a period abroad for part of your studies, for as little as two weeks. We also offer you the chance to participate in field trips2 to several different overseas locations, which have previously included China, Poland, Spain and Finland.

 


Entry requirements

Applicants for this programme will normally be expected to possess a minimum of a second class honours degree in Computer science, Mathematics or other relevant discipline.

We recognise a breadth of qualifications, speak to one of our advisers today to find out how we can help you.

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Select your region to find detailed information about entry requirements:

You can view our full list of country specific entry requirements on our Entry requirements page.

Alternatively, visit our International hub for further advice and guidance on finding in-country agents and representatives, joining our in-country events and how to apply.

English language requirements

  • IELTS: 6.5 overall (with at least 5.5 in each component area)

If you don't meet the English language requirements, you can achieve the level you need by successfully completing a pre-sessional English programme before you start your course. 

For more information on our approved English language tests visit our English language requirements page.

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Fees and funding

2022/23 Tuition fees

Student Full time Part time
UK £10,600 | £4,000 (Work placement option additional fee) per year Not available
International £18,250 | £4,000 (Work placement option additional fee) per year Not available

For advice and guidance on tuition fees3 and student loans visit our Postgraduate Finance page.

We offer a range of International scholarships to students all over the world. For more information, visit our International Scholarships page.


Facilities

Our aim is to offer you sector-leading facilities4:

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Cisco lab

The Cisco lab is used for working with general networking and towards accreditation by Cisco. Optional modules allow students to work in the lab to develop skills in preparation for the Cisco certification exam.

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Virtual labs

Our virtual labs provide a cutting-edge environment to create entire virtual networks, complete with services, users and even attackers. Students can access this environment from anywhere on or off campus.

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Games Technology lab

This lab contains high-end gaming PCs with the capacity to run industry standard games engines and programming environments. It also supports Virtual Reality (VR) game development.
 


Careers and opportunities

On successful completion, you will have knowledge of:

  • The fundamental principles and techniques of data science and computational intelligence.
  • Analysing complex, high-volume, high-dimensional, structured/unstructured data from varying sources.
  • The combination of theory and practical application of data science and computational intelligence methods and techniques.
  • Professional, legal, social, cultural and ethical issues related to data science, computational intelligence and an awareness of societal and environmental impact.

On successful completion, you will be able to:

  • Critically evaluate current research problems and apply cutting-edge developments of data science and to computational intelligence areas.
  • Critically evaluate a range of possible options solutions or architectures to address a sizeable data application and present a soundly reasoned justification for the final solution.
  • Demonstrate competence, creativity, and innovation in solving unfamiliar problems.
  • Effectively communicate outcomes from major projects to technical and non-technical audiences. Select and apply relevant knowledge and skills in big data applications using relevant tools and technologies.
  • Identify and make effective and systematic use of a range of suitable techniques for developing solutions to complex data and analytical problems.

The explosion in the amount of available data now available to businesses, coupled with its potential value to improve competitive advantage, is driving the continued strong demand for data scientists throughout the world. In the UK alone, a 2019 Royal Society report found that demand for workers with specialist data skills like data scientists and data engineers had more than tripled over five years.

Opportunities following successful completion of this course could include careers as data scientists, data professionals and data analysts in variety of sectors including financial services, retail, marketing, customer and business intelligence.

Where our graduates work

This master’s course aims to provide students with the analytical tools to construct more desirable technical solutions using advanced computational methods, with an emphasis on rigorous statistical reasoning. As a result, graduates should gain the skills for roles in a wide range of sectors including; finance, marketing, academia, scientific research, health and medicine, the retail market, information technology, government, ecommerce, energy, transportation, telecommunications, biotechnology and pharmaceutical companies.


How to apply

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  • 1Accreditations

    The majority of our courses have been formally recognised by professional bodies, which means the courses have been reviewed and tested to ensure they reach a set standard. In some instances, studying on an accredited course can give you additional benefits such as exemptions from professional exams (subject to availability, fees may apply). Accreditations, partnerships, exemptions and memberships shall be renewed in accordance with the relevant bodies’ standard review process and subject to the university maintaining the same high standards of course delivery.

    2UK and international opportunities

    Please note that we are unable to guarantee any UK or International opportunities (whether required or optional) such as internships, work experience, field trips, conferences, placements or study abroad opportunities and that all such opportunities may be subject to additional costs (which could include, but is not limited to, equipment, materials, bench fees, studio or facilities hire, travel, accommodation and visas), competitive application, availability and/or meeting any applicable travel COVID and visa requirements. To ensure that you fully understand the visa requirements, please contact the International Office.

    3Tuition fees

    The University will charge the tuition fees that are stated in the above table for the first Academic Year of study. The University will review tuition fees each year. For Home Students, if Parliament permit an increase in tuition fees, the University may increase fees for each subsequent year of study in line with any such changes. Note that any increase is expected to be in line with inflation.

    For International Students, we may increase fees each year but such increases will be no more than 5% above inflation. If you defer your course start date or have to extend your studies beyond the normal duration of the course (e.g. to repeat a year or resit examinations) the University reserves the right to charge you fees at a higher rate and/or in accordance with any legislative changes during the additional period of study.

    4Facilities

    Facilities are subject to availability. Due to the ongoing restrictions relating to COVID-19, some facilities (including some teaching and learning spaces) may vary from those advertised and may have reduced availability or restrictions on their use.

    Student Contract

    By accepting your offer of a place and enrolling with us, a Student Contract will be formed between you and the university. The 2022/23 Contract is currently being updated so please revisit this page before submitting your application. The Contract details your rights and the obligations you will be bound by during your time as a student and contains the obligations that the university will owe to you. You should read the Contract before you accept an offer of a place and before you enrol at the university.