Data Science MSc

 

Course Code

EECT109

Location

Coventry University (Coventry)

 

Study mode

Full-time
Part-time

Duration

1 year full-time
2 years part-time

Start date

September 2022
January 2023


Course overview

Study level: Postgraduate

Data is everywhere. As the volume and complexity of data collected continues to grow, there is increasing demand for expertise in data science to support the analysis and visualisation of all this information.

  • The MSc Data Science is a conversion course for graduates from a wide range of disciplines and backgrounds looking to pursue a career, or upskill, in this new and rapidly developing field. Data Scientists are in short supply and there is high demand for data science skills across sectors including business, government, healthcare, science, finance, and marketing.
  • The aim of the MSc in Data Science is to support students with little previous experience of data analysis or computer programming and to help them to gain new skills such as working with databases; statistical thinking; programming in high-level languages; modelling; applying data science tools and packages; machine learning; information retrieval; data visualisation and addressing the challenges of big data.
  • The MSc Data Science is a conversion course for graduates from a wide range of disciplines and backgrounds looking to pursue a career, or upskill, in this new and rapidly developing field. Data Scientists are in short supply and there is high demand for data science skills across sectors including business, government, healthcare, science, finance, and marketing.
  • The aim of the MSc in Data Science is to support students with little previous experience of data analysis or computer programming and to help them to gain new skills such as working with databases; statistical thinking; programming in high-level languages; modelling; applying data science tools and packages; machine learning; information retrieval; data visualisation and addressing the challenges of big data.

#JoinYourAIFuture Data Science and Artificial Intelligence Scholarships

The MSc Data Science conversion course and MSc Artificial Intelligence and Human Factors at Coventry University are part of the #JoinYourAIFuture programme, funded by the Office for Students. #JoinYourAIFuture is a national recruitment campaign to help address the shortage of AI and data specialists in the UK. An important aim of the campaign is to increase the number of people from underrepresented groups in the AI and data science fields, and to encourage graduates from diverse backgrounds to consider a future in these occupations.

The Office for Students has made 1,000 scholarships available across a number of Universities to help achieve this aim and applicants to this course at Coventry University may apply for a scholarship of £10,000, to be paid in instalments to assist students with the financial aspects of studying this degree.

Full details available under ‘Fees and funding’ section.

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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

If you are curious about applying data to interesting questions, have an eye for data visualisation, are talented at communicating with experts or the public, or take logical approach to solving problems, then you could make a great member of a data science team in any organisation.

  • This course has been designed specifically for graduates from a diverse range of disciplines to give them an opportunity to gain expertise from across the broad field of data science to help complement their existing skills and knowledge.
  • The course aims to develop foundational skills in computer programming, data analysis, and mathematics, for those with little previous experience. These skills are developed in context alongside hands-on use of data science software tools across a range of common applications.
  • The skills gained upon successful completion of this conversion course should complement existing knowledge and skills from your undergraduate study or work experience, such as formulating questions, building arguments, writing reports, delivering presentations, creative problem solving, and a curiosity about data.
  • Features of the course include working with other students with different experiences and perspectives and having the opportunity to gain broad experience of working with a variety of types of data to address diverse and interesting questions.

Accredited by

CMI logo

Chartered Management Institute

As part of this course, you will undertake a professional development module which is currently accredited by the Chartered Management Institute for the 2022-23 intake. Upon successful completion of this module, you will gain the CMI Level 7 Certificate in Strategic Management and Leadership Practice at no additional cost. Coventry University’s accreditation with CMI is currently ongoing for the relevant modules and is regularly reviewed and monitored by the CMI through their quality systems. Whilst Coventry University anticipates that these reviews will continue to be successful, if they were to be unsuccessful, the relevant module in this course would no longer be accredited and we would notify applicants and students of this change as soon as possible.


CWLEP chair upskills with data science course

Technology entrepreneur Sarah Windrum believes Coventry University’s Data Science MSc course will help her business and aid her role as Chair of the Coventry and Warwickshire Local Enterprise Partnership (CWLEP).

Discover how the course is helping Sarah
Sarah Windrum

What you'll study

Data Science is a broad multidisciplinary field encompassing everything from cleaning and managing data to data visualisation and deploying predictive models.

The course supports students from diverse backgrounds to develop the necessary foundations of data science in computer programming, data analysis and statistical thinking, before building more specialised knowledge and skills in information retrieval, data management, machine learning, and the technological challenge of dealing with big data. Throughout the course there are many opportunities for you to build on your existing knowledge and experience from your undergraduate degree or workplace, and gain experience in the analysis of data of a variety of kinds and sizes.

The course maintains a balance between hands-on technology-dependent practical skills using modern software, knowledge and understanding of specialist methods and algorithms in learning from data, mathematical language and foundations, and broader issues around data ethics, data protection and communication with stakeholders of all kinds. In particular, the course covers: programming and software development in a high-level programming languages such as Python and R; data analytics, statistical modelling and programming with data; mathematical foundations of data science such as modelling, linear algebra, and probability; data management systems for structured and unstructured data; big data management, distributed databases and data visualisation; information retrieval and analysis of textual data; machine learning algorithms for learning from data; and a range of data science applications, tools, projects and current issues.

This MSc Data Science course is composed of a combination of modules that cover a broad range of data science methods, applications, and foundations.

In the first semester, you will study two 30-credit modules which aim to introduce you to data science, provide you with an opportunity to develop skills in computer programming, build expertise in data analysis, and establish mathematical foundations. Additional one-to-one support is available through the Sigma Mathematics and Statistics Support Centre (subject to availability).

In the second semester, you will study four 15-credit modules which aim to broaden your knowledge in the application areas in information retrieval, data management systems, machine learning and big data. These modules respond to different challenges in data management and data analysis. Within these modules, a wide range of types and scales of data and data analysis methods will be introduced and applied, from supervised and unsupervised learning to the analysis of text documents.

In the final semester, you will be expected to apply the knowledge and skills you have learned in the first two semesters by undertaking an in-depth individual Data Science project. This may be on some current issue or challenging application in data science and could be industry-based or undertaken in collaboration with one of the university research groups. Guided by a university tutor, this project helps you to develop your research and practical skills while also gaining professional Data Science experience.

Modules

  • This module aims to provide a broad overview of data science and to develop essential skills in computer programming for data science applications. It will cover the nuts and bolts of procedural and object-oriented programming in a high-level programming language, including the design, development and testing of code.

    Compulsory

  • While data science tools and technologies are evolving rapidly, this module aims to build foundational knowledge and understanding of the mathematical concepts, statistical models, and data analytics skills at the heart of data science.

    Compulsory

  • Organisations and businesses are being inundated with very large volumes of data - structured and unstructured - on a daily basis. These data are too big and complex for processing and analysing them using well-known traditional methods. This module aims to introduce you to the current management and visualisation methods for Big Data. Cutting-edge techniques will be taught which should enable you to discover patterns, relationships and associations in big data sets.

    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

  • Information retrieval are among core knowledge driving some of the world’s successful and high-tech businesses including Google, Facebook, and Twitter. In this module, you will be exposed to a range of common information retrieval methods, from theory to practice.

    Compulsory

  • This module provides you with an introduction to machine learning techniques, the associated concepts, and applications.

    Compulsory

  • This module aims to provide you with a framework of knowledge and understanding of how to effectively lead and develop people in a strategic and entrepreneurial way.

    Compulsory

  • The project is intended to provide you with the opportunity to demonstrate competence in applying the concepts and skills acquired during the taught part of the course. You will apply a level of intellectual rigor which is commensurate with the standard of your master’s level programme of study.

    Compulsory

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

Taught modules will be delivered in a block teaching style. This means that all teaching for each module will be consolidated into a condensed number of weeks.

Teaching methods may include a combination of:

  • Lectures
  • Problem-solving workshops
  • Supervised computer laboratory sessions
  • In-class discussions and presentations
  • Directed reading
  • Formative assessments

A 15-credit module will typically have approximately 30 hours of contact time associated with it, while a 30-credit module will have approximately 60 hours of contact time. This may include a combination of, but may not be limited to, lectures, small-group sessions, laboratory session and support sessions. In addition, you will be expected to undertake significant self-study each week depending on the demands of individual modules.

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.


Assessment

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

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


Entry requirements

An applicant will normally be expected to possess at least one of the following:

  • A good honours degree or equivalent qualification.
  • An unclassified degree in a relevant field plus professional experience.

In addition, applicants will need a little knowledge of computer programming. Applicants from non-programming backgrounds are encouraged to take part in a free online course* with the aim of bringing their knowledge of programming and basic data science topics up to the required level for successful application.

Each application will be considered on its merits and the final decision will be made by the Course Director.

*The Get ready for a master’s in Data Science and AI course is available on our FutureLearn platform (please note, this online Platform Provider may be subject to change).

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 no component lower than 5.5.

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 per year Not available
International £18,250 per year Not available

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

#JoinYourAIFuture Data Science and Artificial Intelligence Scholarships

The MSc Data Science conversion course and MSc Artificial Intelligence and Human Factors at Coventry University are part of the #JoinYourAIFuture programme, funded by the Office for Students. #JoinYourAIFuture is a national recruitment campaign to help address the shortage of AI and data specialists in the UK. An important aim of the campaign is to increase the number of people from underrepresented groups in the AI and data science fields, and to encourage graduates from diverse backgrounds to consider a future in these occupations.

The Office for Students has made 1,000 scholarships available across a number of Universities to help achieve this aim and applicants to this course at Coventry University may apply for a scholarship of £10,000, to be paid in instalments to assist students with the financial aspects of studying this degree.

Applications for scholarships will initially be reviewed using a points-based system. Priority for these awards will be given to applicants in the following categories:

  • Female students
  • Black students (as defined by HESA codes: 21; 22; 29; 41; 42)
  • Disabled students Consideration will also be given to applicants who meet other underrepresented criteria in the following secondary categories:
  • Students from POLAR Q1 and Q2
  • Care experienced students
  • Estranged students
  • Gypsy, Roma, Traveller students
  • Refugees
  • Children from military families, veterans and partners of military personnel.

Download the scholarship application form.

Download the scholarship application guidance notes for full details of the eligibility requirements and the terms and conditions.

Application deadline of Sunday 20th November 2022


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

Upon successful completion of this course, you should be able to:

  • Demonstrate systematic knowledge and critical understanding of core and advanced topics in data science and its theoretical foundations.
  • Design and evaluate computer systems for the storage, organisation, management, retrieval and processing of different types of information and sizes of datasets, including distributed systems.
  • Use an analytical approach, statistical thinking and a comprehensive understanding of appropriate models, methods, algorithms and software tools to analyse data of a variety of types, and identify the limitations of any analysis.
  • Demonstrate practical skills and capabilities related to employment, including working effectively and constructively as part of a team, leading a team, motivating and communicating complex ideas accurately to experts and non-experts, and technical expertise with modern data science tools and technologies.
  • Identify and apply appropriate practices within a professional, legal, social, cultural and ethical framework, including complex, inter-related, multi-faceted issues that can be found in a variety of organisations and professional contexts.
  • Apply research skills such as planning research, and critical analysis of information from appropriate sources, demonstrate awareness of current issues and show originality in the application of knowledge where appropriate.

Data Scientists are in short supply and there is high demand for data science skills across business, government, healthcare, science, finance, and marketing (to name a few).

Successful graduates of this course should be well prepared to join a team in an organisation related to their undergraduate discipline (contributing data analytics skills alongside their subject knowledge) or a specialist data science team in a more general organisation or consultancy.

Coventry University is committed to preparing you for your future career and giving you a competitive edge in the graduate job market. The university's Talent Team provide a wide range of support services to help you plan and prepare for your career. 


How to apply

  • 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. A copy of the 2022/23 contract can be found here.  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.

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