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Data Science and Computational Intelligence MSc 2018/19 entry

Course code:

ECT104

Study options:

1 year full-time

 

Location:

Coventry University

Starting:

May 2019

 

Fees:
Faculty:

Get in touch

For questions regarding study and admissions please contact us:

+44 (0) 24 7765 4321


Overview

Accredited by the British Computer Society (BCS), this Master’s 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.

Multidisciplinary content covers Machine Learning, Neural Networks, Big Data Analysis, Information Retrieval, Cloud Computing, Fuzzy Systems and Evolutionary Computation. You will have opportunities to undertake practical projects, applying your learning to real-life problems in business, finance, security, industry control, engineering, natural language processing, information retrieval and bioinformatics.

Coventry offers chances to learn alongside active researchers in areas such as pervasive computing, distributed computing and application, as well as innovative applications for interactive virtual worlds. 

Why Coventry University?

An award-winning university, we are committed to providing our students with the best possible experience. We continue to invest in both our facilities and our innovative approach to education. Our students benefit from industry-relevant teaching, and resources and support designed to help them succeed. These range from our modern library and computing facilities to dedicated careers advice and our impressive Students’ Union activities.

Global ready

An international outlook, with global opportunities

Employability

Career-ready graduates, with the skills to succeed

Student experience

All the support you need, in a top student city

Accreditation & Professional Recognition

This course is accredited and recognised by the following bodies:

British Computer Society (BCS)

This degree has been accredited by British Computer Society (BCS), the Chartered Institute for IT.

Accreditation is a mark of assurance that the degree meets the standards set by BCS. It entitles you to professional membership of BCS, which is an important part of the criteria for achieving Chartered IT Professional (CITP) status through the Institute. Some employers recruit preferentially from accredited degrees and an accredited degree is likely to be recognised by other countries that are signatories to international accords.

Course information

Big data processing and information retrieval drives some of the world most successful and high-tech businesses; from well-known companies like Google and Twitter, to specialist medical informatics providers and even space exploration.

The main theme throughout this course is automatic big data processing and information retrieval through machine learning, neural network and evolutionary computing. We will 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 such as Hadoop Map Reduce and Spark, in combination with easy to use and powerful development tools such as Scala, Python, Matlab and R. 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.

Course Specification
Download PDF (287kb)

Modules

Overview

In your final semester, you will be expected to apply the knowledge and skills you have learned by undertaking an in-depth individual project, 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 and gain an experience matching that of a data scientist professional.

Past students have, for example, analysed big data for the movie industry, helped in assessing oil wells to evaluate extraction costs, recognised customer’s emotion through face gestures, analysed text sentiment in a social media exchange, and performed automatic scene labelling and object recognition as well as designed a robotics controller for helping the elderly, just to mention a few examples.

This course includes the Global Professional Development module. Each of the participating postgraduate courses have an individually tailored version of the Chartered Management Institute (CMI) Global Professional Development module.

Modules

  • Semester 1

    • Machine Learning
    • Intelligent Information retrieval
    • Cloud Computing and Distributed Technologies
    • Advanced Database Systems
  • Semester 2

    • Evolutionary and Fuzzy Systems
    • Artificial Neural Networks
    • Business Intelligence and Big Data Processing
    • Research Methods in Computing
  • Semester 3

    • Project Dissertation

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.

In more detail...

  • 90% overall student satisfaction for the teaching of computing, above the sector average of 80%, in the Postgraduate Taught Experience Survey (PTES) 2016.
  • 42% of ‘Computer Science and Informatics’ research was judged to be world leading or internationally excellent in the Research Excellence Framework (REF 2014).
  • An Engineering and Computing building that features a large range of specialised computing laboratories in computer security, communications and signal processing, electrical, electronics and microprocessors, ethical hacking and forensic computing, together with a games and multimedia studio and open access computer facilities.

Accredited by the British Computer Society (BCS), fully meets the academic requirements for registration as a Chartered IT Professional and provides partial fulfilment for Chartered Scientist and Chartered Engineer.

Your main study themes are:

  • Machine learning and data mining: Machine learning is the process whereby systems learn by identifying structures and patterns within data. As such, it has proved an important tool in various applications, including data mining, games design, diagnosis and natural language processing. We cover a broad field of intelligent techniques and their associated algorithms, such as data preparation and pre-processing, reinforcement learning, supervised and unsupervised learning, classification and clustering, applications of machine learning and future developments.

  • Intelligent information retrieval: You will be exposed to a range of information retrieval techniques, from theory and context to application and implementation. The techniques discussed are those used to retrieve data from large data sources, in very short time, or from non-trivial sources such as images or videos.  

  • Artificial neural networks: Introduces the concepts used in neural networks and their application to solving real-world problems. A popular machine learning approach that attempts to model how the human brain works, neural networks are used in a wide range of applications, including image processing, speech and natural language processing, medical diagnosis, bioinformatics and computational biology, emotion recognition, robotics and control. We will explore different neural network computational approaches and structure, neural network learning and teaching, convolutional neural networks, deep learning and applications of neural networks in plenty of industrial settings.

  • Advanced database systems: Covers the theoretical and the technological underpinnings of database management systems. The entity-relationship data model and the relational model will be used as foundational material for the practical investigation of database development. Topics such as transaction management and concurrency control will provide a sound basis for an understanding of the theoretical underpinning of database management.

  • Evolutionary and fuzzy systems: Introduces evolutionary algorithms and fuzzy systems from an application oriented standpoint. We study the key concepts of fuzzy sets as a methodology for handling imprecise and uncertain information. Applications of fuzzy systems and fuzzy controllers will be discussed along with coverage of their use in hybrid intelligent systems in combination with other Computational Intelligence (CI) techniques. 

  • Cloud computing and distributed technologies: Aims to develop knowledge of technologies in cloud and distributed computing, such as service-oriented architecture. You will develop the skills to designer and utilise cloud computing platform and architecture to empower a big data processing model by distributed technologies in order to help solving a variety of complex business scenarios.

  • Business intelligence and big data processing: Provides a detailed account of big data techniques, applications, tools and platforms. Cutting-edge techniques will be taught which will enable business to sift through large quantities of data to discover patterns, relationships, associations, factors and clusters. These include min hashing, associative rules, link analysis, and mining data streams. Important current applications will be covered including recommendation systems, web advertising, and social network mining. Those applications will be implemented using important current tools and platforms such as Hadoop MapReduce and Spark hosted in our brand new GPU server.

  • Research methods in computing: Provides the background in study skills and research methods to enable students to carry out applied or enquiry based research projects over the range of Master’s programmes in the Department of Computing.

  • Master Project: Covers an overarching project that will be implemented by the students under the supervision of one of our highly qualified academics. The project will cover several aspects of the studied techniques and implementation throughout the taught modules. Guided by an expert tutor, this project helps to develop your research and practical skills and gain an experience matching that of data scientist professional. Projects include analysing big data for the movie industry, oil extraction and refinement analysis, customer’s emotion recognition, speech and tone recognition, text sentiment analysis, performing automatic scene labelling and object recognition, fuzzy controllers as well as designed a neural networks robotics controller for helping the elderly.

The programme allows you to study full-time over one year or part-time over two years, starting in September. 

We stress practicality whenever appropriate and try to strike a good balance between theory and application, as well as industrial-related experience and current research topics. A variety of equipment and software are used for these purposes, including HPC clusters and a GPU server purposely built for deep machine learning and neural networks tasks.

There may be opportuntiies to attend external talks, by our academic and research staff, as well as visiting lecturers, which aim to bring you the latest issues on a wide range of topics, such as intelligent services, image processing and big data analytics.

Teaching methods include: a range of creatively designed practical tasks, projects, lectures and tutorials.

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

The Coventry University Group assessment strategy ensures that our courses are fairly assessed and allows us to monitor student progression towards the achieving the intended learning outcomes. Assessments may include exams, individual assignments or group work elements.

On successful completion, you should 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 should 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.
  • Communicate effectively 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.

In a typical teaching week, you will have up to 12 ‘contact’ hours of teaching. There are four modules in the first semester, four in the second and you will spend the third semester on your project. Teaching of each module comprises around three hours of ‘contact’ time, which consists of four hours of lectures each week and around eight hours of practical laboratory classes each week.

In addition, you will be expected to undertake a further 14 hours of self-directed study each week eg. some guided study using handouts, online activities, etc.

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 trips to a number of different overseas locations, which have previously included China, Poland, Spain and Finland. 

Global ready

Did you know we help more students travel internationally than any other UK university according to data from the experts in higher education data and analysis, HESA?

In 2016/17, we were able to provide a total of 3,482 student experiences abroad that lasted at least five days.

Much of this travel is made possible through our Global Leaders Programme, which enables students to prepare for the challenges of the global employment market, as well as strengthening and developing their broader personal and professional skills.

Explore our international experiences

1st for

international experiences

Sending more students overseas than any other UK uni (HESA 2016/17)


3,482

Student experiences

The number of student trips abroad for at least 5 days in 2016/17



12,000

and counting

The number of students we’ve helped travel internationally so far

12

global programmes

As well as trips, we offer other opportunities like language courses


Entry Requirements

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

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

English as a Foreign Language: This course requires IELTS 6.5. Alternatively, students may be admitted with IELTS 6.0 subject to successfully completing a compulsory five week pre-sessional English course

Our International Student Hub offers information on entry requirements for your country, as well as contact details for agents and representatives should you need more advice.

More detail

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

English as a Foreign Language: This course requires IELTS 6.5. Alternatively, students may be admitted with IELTS 6.0 subject to successfully completing a compulsory five week pre-sessional English course

Our International Student Hub offers information on entry requirements for your country, as well as contact details for agents and representatives should you need more advice.

More detail

Tuition Fees

We pride ourselves on offering competitive tuition fees which we review on an annual basis and offer a wide range of scholarships to support students with their studies. Course fees are calculated on the basis of what it costs to teach each course and we aim for total financial transparency.

Starts

Fee


May 2019

£7,750 (per year)


Scholarships

If you're a truly outstanding undergraduate candidate we may be able to offer you a Coventry University Scholarship. Coventry University Scholarships are awarded to recognise truly exceptional sports achievement and academic excellence.

Starts

Fee


May 2019

£7,750 (per year)


Scholarships

For the September 2017 and January 2018 intakes, we're investing £1 million into scholarships for high achieving and enterprising students.

Our scholarships are worth up to £10,000 and every student that applies will be considered. Fulfil your potential this academic year with Coventry University!

Starts

Fee


May 2019

£15,050 (per year)


Scholarships

For the September 2017 and January 2018 intakes, we're investing £1 million into scholarships for high achieving and enterprising students.

Our scholarships are worth up to £10,000 and every student that applies will be considered. Fulfil your potential this academic year with Coventry University!

Career prospects

The highly-regarded Harvard Business Review has previously declared the role of ‘data scientist’ to be the sexiest career of the 21st century.

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.

A 2014 survey by consulting firm Accenture on clients’ big-data strategies in April 2014 revealed that more than 90% planned to hire more employees with expertise in data science, yet almost half cited a lack of talent as a chief obstacle.

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.

The practical nature of our course places an emphasis on your future employability, developing a wide range of technical, analytical, design and professional skills. 

Our award-winning Faculty careers service, EC Futures, which won the ‘Best Placement Service in the UK’ award at the National Undergraduate Employability Awards in 2015 and 2016, will help you in finding work experience while you study and employment on graduation. Opportunities also exist to complete a PhD research degree upon completion of the course.

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 Careers and Employability team provide a wide range of support services to help you plan and prepare for your career.

Disclaimer

By accepting your offer of a place and enrolling with us, a Student Contract will be formed between you and the University. The Contract will detail your rights and the obligations you will be bound by during your time as a student and will contain the obligations that the University will owe to you. The 18/19 PG Contract will be published shortly.