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This MSc Computing offers students from diverse career and subject areas a balance of software engineering skills and technical abilities required for a career in Software Development. Read more
This MSc Computing offers students from diverse career and subject areas a balance of software engineering skills and technical abilities required for a career in Software Development.

Through this one-year programme you will get a first-hand understanding of the vital problem-solving role of software, the interdisciplinary opportunities available, and what computational systems can achieve.

Through a gentle introduction and intensive support, you will be introduced to programming skills using important languages such as Java and Python. Emphasis is placed on handling data and you will develop essential skills in SQL (Structured Query Language) for advanced database functionality using industry standard products such as Oracle™.

A choice of taught optional modules allows you to further develop skills in areas of your choice.

Graduates from these programmes will be ideally placed for employment in the computing industry or for careers requiring a combination of their graduate discipline with computing expertise.

Distinctive features:

• An opportunity to take a conversion course which is also an accredited course recognised by BCS, the Chartered Institute for IT.

• The opportunity to complement the discipline in which you graduated with the discipline of Computing.

• The facility to tailor the course to your interests by the selection of advanced option modules.

• Flexible choice of project topic, for example: associated with the research activity of the School fulfilling a business need reflecting your own interest.

Structure

You will study core modules to a total of 80 credits, with two optional modules worth a total of 40 credits. Students will also undertake an individual project and dissertation (worth 60 credits).

This course is a full-time programme undertaken over one calendar year. It is also available as a part-time programme over three years, and with placement.

Core modules:

Information Processing in Python
Web Application Development
Object-Oriented Development with Java
Software Engineering
Dissertation

Optional modules:

Computational Systems
Computer Science Topic 1: Web and Social Computing
Distributed and Cloud Computing
Human Centric Computing
Information Modelling & Database Systems
Visual Communication and Information Design
E-Commerce and Innovation

Teaching

The School of Computer Science and Informatics has a strong and active research culture which informs and directs our teaching. We are committed to providing teaching of the highest standard and received an excellent report in the most recent Quality Assurance Agency (QAA) review.

A diverse range of teaching and learning styles are used throughout the MSc in Computing and the MSc in Computing with Placement. Students will attend lectures, participate in seminars, workshops and tutorials, and carry out practical and laboratory work.

Students obtain support materials either via Learning Central (Cardiff University’s Virtual Learning Environment) or from study packs specially developed for selected modules.

Students will also undertake a project and independent study to enable them to complete their dissertation. Dissertation topics may be suggested by the student or chosen from a list of options proposed by academic staff reflecting their current interest.

Support

As a School, we pride ourselves on providing a supportive environment in which we are able to help and encourage our students.

All students are allocated a personal tutor who will monitor your progress throughout your time at university and will support you in your Personal Development Planning. You will see your Personal Tutor at least once each semester.

Outside of scheduled tutor sessions, our Senior Personal Tutor runs an open door policy, being on hand to advise and respond to any personal matters as they arise.

The School has a formal student-staff panel to discuss topics or issues of mutual interest, in addition we schedule fortnightly informal gatherings over coffee for all students and staff associated with MSc Programmes.

Feedback:

Feedback on coursework may be provided via written comments on work submitted, by provision of ‘model’ answers and/or through discussion in contact sessions.

Assessment

The taught modules within the programmes are assessed through examinations and a wide range of in-course assessments, such as written reports, extended essays, practical assignments and oral presentations.

The individual project and dissertation will enable students to demonstrate their ability to build upon and exploit knowledge and skills gained to exhibit critical and original thinking based on a period of independent study and learning.

Career prospects

Recent graduates have gained employment in roles such as software developers, systems analysts, business analysts, IT consultants, and support engineers.

MSc Computing graduates are employed by organisations of all sizes locally, nationally, and internationally. For example, recent graduates have taken up positions with local NHS Trusts, Logica, Sun Microsystems, BT, and the National Library of Medicine in the USA, as well as undertaking further doctoral study.

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The GIS (Geographical Information Science) MSc provides an education in the theoretical, scientific and practical aspects of GIS. Read more
The GIS (Geographical Information Science) MSc provides an education in the theoretical, scientific and practical aspects of GIS. It prepares students for technical and analytical GIS roles and is in high demand; we have very close links with industry and the majority of our students find employment prior to contemplating their degree.

Degree information

Students gain a solid grounding in the scientific principles underpinning the computational and analytical foundations of GISc. Our staff are world-leading experts in the areas of programming location-enabled Apps, spatial and 3D databases, big spatio-temporal analytics, citizen science and and human computer interaction, and the MSc therefore is able to offer a wide range of options and specialisations.

Students undertake modules to the value of 180 credits. The programme consists of four core modules (60 credits), four optional modules (60 credits) and a research project (60 credits). A Postgraduate Diploma, four core modules (60 credits), four optional modules (60 credits), full-time nine months is offered.

Core modules - core modules introduce the theory underpinning GIS, along with programming skills (python) and the basics of spatial analysis and statistcs. You'll learn to critically engage with GIS rather than just pushing buttons - how does the way data is captured and modelled influence the results of your analysis? Do you get the same results from two different GIS packages? Knowing what is inside the 'black box' means you understand analytical results and their limitations.
-GIS Principles and Technology
-Principles of Spatial Analysis
-Mapping Science
-Representations, Structures and Algorithms

Optional modules - term two is where you start to specialise, chosing modules that fit your interests, intended career choice and/or prepare you for your dissertation. At this point you can chose a heavilty technical route (e.g. databases, programming, human computer interaction) a more analytical route (spatio-temporal data mining, network and locational analysis, databases) or a mixture of the two routes. You will need to chose four modules in total. At least 30 credits of optional modules selected from :
-Geographical Information System Design
-Spatio-Temporal Analysis and Data Mining
-Web and Mobile GIS – Apps and Programming
-Spatial Databases and Data Management

Plus no more than 30 credits of optional modules (all term two) selected from :
-Airborne Data Acquisition
-Applied Building Information Modelling
-Network and Locational Analysis
-Image Understanding
-Ocean and Coastal Zone Management
-Positioning
-Research Methods
-Terrestrial Data Acquisition

Dissertation/report
All students undertake an independent research project which culminates in a dissertation of 10,000–15,000 words. Where appropriate, this may be undertaken in conjunction with one of our many industrial partners, including Arup, Joint Research Centre, British Red Cross, Transport for London.

Teaching and learning
The programme is delivered through lectures, practical classes, demonstrations and tutorials, and is supported by a series of external speakers from industry and visits to industrial who give weekly seminars describing how GIS is used in their field as well as what they are looking for when recruiting graduate GIS students. Assessment is through unseen examinations, group and individual coursework, formal and oral presentations, and the dissertation.

Careers

There are excellent employment prospects for our graduates, with starting salaries of around £25,000. Recent GIS graduates have found openings with large engineering design firms (such as Arup or WSP), specialist consultancy firms such as Deloitte or Informed Solutions, in leading professional software companies (such as ESRI or Google), with local authorities, for organisations such as Shell, Tesco, the Environment Agency, Transport for London, NHS and the Ordnance Survey.

Employability
Students will develop specific skills including a fundamental understanding of GIS and its application to real-world problems, through theoretical lectures covering the foundations of the science – how data is captured, map creation, generalisation, spatial data management, spatial analysis, data quality and error, and spatial algorithms. Students will develop strong technical (python, R, Java, HTML, Javascript, SQL) and analytical skills (data mining, human computer interaction and usability), and in order to fully understand the principles behind GIS will make use of multiple GIS packages, both proprietary and free/open source (ArcGIS, QGIS).

Why study this degree at UCL?

This highly regarded MSc has been running for nearly 30 years and is taught by internationally recognised academics. Our specialist GIS laboratory offers the latest open source and proprietary software and our unique dual focus on the computer science and analytical aspects of GIS means that you will be able to develop your skills in multiple directions.

Our close links with industry (a strong alumni group and weekly industrial seminars) mean that you will be able to directly link your classroom learning with your future career as a GIS professional; you can also undertake your dissertation with an industrial partner.

As well as weekly industrial seminars, you will have the option to do an industry-linked project, and you will be able to attend our annual GIS careers event, which is co-organized with the UK Assocation of Geographic Infrormation.

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This MSc Computing offers students from diverse career and subject areas a balance of software engineering skills and technical abilities required for a career in Software Development. Read more
This MSc Computing offers students from diverse career and subject areas a balance of software engineering skills and technical abilities required for a career in Software Development.

Through this two-year programme you will get a first-hand understanding of the vital problem-solving role of software, the interdisciplinary opportunities available, and what computational systems can achieve.

Through a gentle introduction and intensive support, you will be introduced to programming skills using important languages such as Java and Python. Emphasis is placed on handling data and you will develop essential skills in SQL (Structured Query Language) for advanced database functionality using industry standard products such as Oracle™.

A choice of taught optional modules allows you to further develop skills in areas of your choice.

Students may choose to apply for a paid 7-12 month professional work placement to be undertaken on completion of Spring semester and before completing the MSc course with a 60-credit dissertation. This provides valuable work experience to develop your IT Professional skills.

Graduates from these programmes will be ideally placed for employment in the computing industry or for careers requiring a combination of their graduate discipline with computing expertise.

Distinctive features

• A conversion course as well as an accredited course recognised by BCS, the Chartered Institute for IT.

• The opportunity to complement the discipline in which you graduated with the discipline of Computing.

• The facility to tailor the course to your interests by the selection of advanced option modules.

• Flexible choice of project topic, for example: associated with the research activity of the School; fulfilling a business need; reflecting your own interest.

• 7-12 month experience as an IT Professional for students who successfully find a suitable placement.

Structure

You will undertake a placement following the taught stage of the course and prior to undertaking your individual project and dissertation. Most students start their placement in the summer of Year 1. The breakdown is as follows:

Year 1: 80 credits core modules, 40 credit optional modules.

Year 2: 120 credits placement, dissertation.
This is a full-time course undertaken over two calendar years. It is also available as a full-time course over one year or a part-time course over three years, both without placement.

Year ONE core modules:

Information Processing in Python
Web Application Development
Object-Oriented Development with Java
Software Engineering

Year ONE optional modules:

Computational Systems
Computer Science Topic 1: Web and Social Computing
Distributed and Cloud Computing
Human Centric Computing
Information Modelling & Database Systems
Visual Communication and Information Design
E-Commerce and Innovation

Year TWO core modules:

Placement
Dissertation

Teaching

The School of Computer Science and Informatics has a strong and active research culture which informs and directs our teaching. We are committed to providing teaching of the highest standard and received an excellent report in the most recent Quality Assurance Agency (QAA) review.

A diverse range of teaching and learning styles are used throughout the MSc in Computing and the MSc in Computing with Placement. Students will attend lectures, participate in seminars, workshops and tutorials, and carry out practical and laboratory work.

Students obtain support materials either via Learning Central (Cardiff University’s Virtual Learning Environment) or from study packs specially developed for selected modules.

You will also undertake a project and independent study to enable you to complete a dissertation. Dissertation topics may be suggested by you or chosen from a list of options proposed by academic staff reflecting their current interest.

Support

As a School, we pride ourselves on providing a supportive environment in which we are able to help and encourage our students.

All students are allocated a personal tutor who will monitor your progress throughout your time at university and will support you in your Personal Development Planning. You will see your Personal Tutor at least once each semester.

Outside of scheduled tutor sessions, our Senior Personal Tutor runs an open door policy, being on hand to advise and respond to any personal matters as they arise.

The School has a formal student-staff panel to discuss topics or issues of mutual interest, in addition we schedule fortnightly informal gatherings over coffee for all students and staff associated with MSc Programmes.

Students are responsible for obtaining their placement. The School actively assists students on “with Placement” courses in finding a suitable placement.

Feedback:

Feedback on coursework may be provided via written comments on work submitted, by provision of ‘model’ answers and/or through discussion in contact sessions.

Assessment

The taught modules within the programmes are assessed through examinations and a wide range of in-course assessments, such as written reports, extended essays, practical assignments and oral presentations.

The placement is assessed through a reflective report that demonstrates that the student has developed skills as an IT Professional.

The individual project and dissertation will enable you to demonstrate your ability to build upon and exploit knowledge and skills gained to exhibit critical and original thinking based on a period of independent study and learning.

Career prospects

Recent graduates have gained employment in roles such as software developers, systems analysts, business analysts, IT consultants, and support engineers.

MSc Computing graduates are employed by organisations of all sizes locally, nationally, and internationally. For example, recent graduates have taken up positions with local NHS Trusts, Logica, Sun Microsystems, BT, and the National Library of Medicine in the USA, as well as undertaking further doctoral study.

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Are you interested in working with cutting-edge technology at the forefront of language processing?. This course is run by a leading research group at the University of Wolverhampton. Read more
Are you interested in working with cutting-edge technology at the forefront of language processing?

This course is run by a leading research group at the University of Wolverhampton. As a Master's student, you will be part of our Research Institute of Information and Language Processing (RIILP) (http://www.wlv.ac.uk/research/institutes-and-centres/riilp---research-institute-in-information-and-lan/), an independent, research-driven University unit specialising in Linguistics and Natural Language Processing.

What will I learn?

Computational Linguistics (sometimes called Natural Language Processing) is the use of computers to study language. On the course, you will be able to study:
• How to use Python and the well-established NLTK library to process natural language texts;
• How to analyse real language usage;
• How to automatically translate text using computer programs;
• The use of computers to study features of language;
• Translation tools such as translation memory systems;
• Computer techniques for automatically classifying natural language texts;
• Understand how Siri, Amazon Echo and Google Home etc. work;
• How to design an experiment that will thoroughly test your research questions.

You will be mentored through this programme by experienced and leading academics from the field. Join our research group today (http://www.wlv.ac.uk/research/institutes-and-centres/riilp---research-institute-in-information-and-lan/) to become part of this team of leading researchers and academics and create your path to a career in computers and language!

What modules will I study?

When studied full-time, this course comprises of three semesters worth 60 credits each. Three modules will be studied in semesters one and two. During the third semester, students will undertake their research project and complete a 15,000 word dissertation on any aspect of Computational Linguistics.

The course covers all aspects of Computational Linguistics in line with current and leading work in research and industry, and is divided into the following taught modules:
1. Computer programming in Python
2. Corpus Linguistics in R
3. Machine translation and other natural language processing applications
4. Computational Linguistics
5. Translation tools for professional translators
6. Machine learning for language processing
7. Research methods and professional skills

Translation Tools for Professional Translators is an elective module that may be chosen in the Second Semester to replace another taught module for those students who are interested in pursuing careers in Translation.

Opportunities

- You will be taught by leading researchers in the field: our teaching staff at the Research Institute of Information and Language Processing (RIILP) (http://www.wlv.ac.uk/research/institutes-and-centres/riilp---research-institute-in-information-and-lan/) are engaged in high-quality research, as evidenced by the latest RAE 2008 and REF 2014 results.
- We offer an exciting programme of invited lectures and research seminars, attended by both students and staff;
- The institute has a wide network of contacts in academia and in the industry from which you will be able to benefit;
- Find out about Dr. Vinita Nahar’s (past group member) innovative research into technology to detect Cyberbullying online http://www.itv.com/news/central/topic/cyber-bulling/.

How will I be assessed?

Assessments will include writing assignments on given topics, reports on practical work carried out in the class, portfolios, projects, oral presentations, and tests. The culmination of the study programme will be your 15,000-word dissertation, which will allow you to carry out an in-depth study of a chosen topic within the areas of corpus linguistics, language teaching, lexicography, or translation.

What skills will I gain?

The practical sessions include working with tools and software and developing programs based on the material taught in the lectures, allowing you to apply the technical skills you are learning. Some of the tasks are group based, feeding into the collaboration aspect of blended learning which enhances team-working skills, and some are done individually. Through portfolio building, you will be able to share your learning with other students. You will also be able to enhance your employability by sharing your online portfolio with prospective employers. Some assessments will require you to present your work to the rest of the class, enabling you to develop your presentation skills, which are useful in both academia and industry. Other transferable skills are the abilities to structure your thoughts, present your ideas clearly in writing and prepare texts for a wider audience. You will acquire these skills through assessed report and essay writing, and most of all through writing your dissertation.

Career path

Graduates of this course will be well-placed to continue their academic/research careers by applying for PhD positions within RIILP or at other leading centres for language and information processing. This degree will also enable graduates to access research and development positions within the language processing and human language technology industries, as well as in related areas such as translation, software development and information and communication technologies, depending on their specific module choices and dissertation topic. It should be noted that computer programming is a skill that is increasingly sought after by many companies from technological backgrounds and skills gained from this course will place graduates in a good position to take up such posts. Past graduates from this course have also gone on to successful careers specifically within the computer programming industry.

Student comments

"This course allowed me to see all the potential of Natural Language Processing - my favourite topic was Corpus Linguistics."

"I would recommend this course to people interested in linguistics or languages in general to show them that linguistics can also be paired with Computer Science and to those interested in Computer Science, for it could show them a new application to Computer Science."

"I would recommend this course to the individuals who seek to increase their knowledge of Machine Learning and Natural Language Processing. People who want to understand how, say, SIRI works, should join this course."

"Thanks to this course, I know what I want to do in the future; I want to be a Professor of Corpus Linguistics. I have several opportunities for a PhD in the US. I also learnt how to use a few programming languages, which is of great importance nowadays if one wants to find a job."

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The MSc in Data Science & Analytics, jointly offered by the Department of Computer Science and the Department of Statistics, provides an education in the key principles of this rapidly expanding area. Read more
The MSc in Data Science & Analytics, jointly offered by the Department of Computer Science and the Department of Statistics, provides an education in the key principles of this rapidly expanding area. The combination of sophisticated computing and statistics modules will develop skills in database management, programming, summarisation, modelling and interpretation of data. The programme provides graduates with an opportunity, through development of a research project, to investigate the more applied elements of the disciplines.

Visit the website: http://www.ucc.ie/en/ckr49/

Course Details

The MSc in Data Science and Analytics is a significant collaboration between the Departments of Computer Science and Statistics; designed to provide graduates with the skills and knowledge required to help companies and public bodies deal with ever increasing and complex data. The programme emphasises the application of Computer Science and Statistics methodologies helping transform data into useful information that can support decision making.

Format

A typical 5 credit module:
• 2 lecture hours per week
• 1–2 hours of practicals per week
• Outside these regular hours students are required to study independently by reading and by working in the laboratories and on exercises.

Structure

Students must attain 90 credits through a combination of:

- Core Modules (30 credits)
- Elective Modules (30 credits)
- Dissertation (30 credits)

Part 1 (60 credits)

- Core Modules (30 credits) -

CS6405 Data Mining (5 credits) - Dr. Marc Van Dongen
ST6030 Foundations of Statistical Data Analytics (10 credits)
ST6033 Generalised Linear Modelling Techniques (5 credits)

- Database Modules -

Students who have adequate database experience take:

CS6408 Database Technology (5 credits) - Mr. Humphrey Sorensen
CS6409 Information Storage and Retrieval (5 credits) - Mr. Humphrey Sorensen

- Students who have not studied databases take:

CS6503 Introduction to Relational Databases (5 credits)
CS6505 Database Design and Administration (5 credits)

Elective Modules (30 credits)

Students must take at least 10 credits of CS (Computer Science) modules and at least 10 credits of ST (Statistics) modules from those listed below:

CS6322 Optimisation (5 credits) - Dr. Steve Prestwich
CS6323 Analysis of Networks and Complex Systems (5 credits) - Prof. Gregory Provan
CS6509 Internet Computing for Data Science (5 credits)
ST6032 Stochastic Modelling Techniques (5 credits)
ST6034 Multivariate Methods for Data Analysis (10 credits)
ST6035 Operations Research (5 credits)
ST6036 Stochastic Decision Science (5 credits)

- Programming Modules -

Students who have adequate programming experience take:

CS6406 Large-Scale Application Development and Integration l (5 credits) - Professor Gregory Provan
CS4607 Large-Scale Application Development and Integration ll (5 credits) - Professor Gregory Provan

- Students who have not studied programming take:

CS6506 Programming in Python (5 credits)
CS6507 Programme in Python with Data Science and Applications (5 credits) - Dr. Kieran Herley

Part 2 (30 credits)

Students select one of the following modules:

CS6500 Dissertation in Data Analytics (30 credits)
ST6090 Dissertation in Data Analytics (30 credits)

Assessment

Full details and regulations governing Examinations for each programme will be contained in the Marks and Standards 2015 Book and for each module in the Book of Modules 2015/2016 - http://www.ucc.ie/modules/

Postgraduate Diploma in Data Science and Analytics

Students who pass each of the taught modules may opt to exit the programme and be conferred with a Postgraduate Diploma in Data Science and Analytics.

Careers

This programme aims to prepare students to manage, analyse and interpret large heterogeneous data sources. Graduates will design, compare and select appropriate data analytic techniques, using software tools for data storage/management and analysis, machine learning, as well as probabilistic and statistical methods. Such abilities are at the core of companies that constantly face the need to deal with large data sets.

Companies currently seeking graduates with data analytics skills include: firms specialising in analytics, financial services and consulting, or governmental agencies.

Companies actively recruiting Computer Science graduates in 2014-15 include:

Accenture, Aer Lingus, Amazon, Apple, Bank of America Merrill Lynch, Bank of Ireland, BT, Cisco, CiTi-Technology, Cloudreach, Dell, Digital Turbine Asia Pacific, EMC, Enterprise Ireland, Ericsson, First Derivatives, Guidewire, IBM, Intel, Open Text, Paddy Power, Pilz, PWC, SAP Galway Transverse Technologies, Trend Micro, Uniwink, Version 1 (Software).

How to apply: http://www.ucc.ie/en/study/postgrad/how/

Funding and Scholarships

Information regarding funding and available scholarships can be found here: https://www.ucc.ie/en/cblgradschool/current/fundingandfinance/fundingscholarships/

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Train to become a data analyst in a growing industry by studying techniques such as data mining, statistical modelling, business intelligence and data visualisation. Read more
Train to become a data analyst in a growing industry by studying techniques such as data mining, statistical modelling, business intelligence and data visualisation. Study on a course which has been developed with direct input from industry experts who will bring real life business case scenarios to you.

More about this course

This specialist advanced course will equip students with the theoretical, technical and practical data analytics competencies required in an area of economic growth. The course curriculum content has been developed with direct input from industry experts and utilises specialist software tools and techniques. Students’ experience of the course will be enriched with exposure to real life business case scenarios brought to them by skilled professionals in industry.

The specialist nature of the course will allow students to explore and experience advanced techniques in data science. Students will acquire practical skills, often first-hand from an external practitioners, preparing them for employment as data analysts. Students will also be trained in the use of software tools and environments currently used by the industry sector. For example, students on this course will have exposure to R and Python programming, IBM SPSS, SAS®, Tableau, Oracle and Hadoop.

A range of assessment methods are used on the course, including written reports, practical and research assignments, demonstrations, presentations, group work and examinations.

Modular structure

The modules listed below are for the academic year 2016/17 and represent the course modules at this time. Modules and module details (including, but not limited to, location and time) are subject to change over time.

Year 1 modules include:
-Data Analysis and Visualization (core, 20 credits)
-Data Mining for Business Intelligence (core, 20 credits)
-Data Modelling and OLAP Techniques for Data Analytics (core, 20 credits)
-MSc Project (core, 60 credits)
-Programming for Data Analytics (core, 20 credits)
-Statistical Modelling and Forecasting (core, 20 credits)
-Financial Mathematics (option, 20 credits)
-Work Related Learning (option, 20 credits)

After the course

On completion of the course graduates will be well equipped to work in some of the fastest growing sectors of the data science and big data industries. The course offers wide-ranging career opportunities in the commercial industry, public and financial services, especially in areas requiring big data analysis such as consumer, healthcare, scientific, financial, security intelligence, business and social sciences.

Job roles include data scientist, data analyst, digital analyst, big data consultant, statistical analyst and data modeller. Graduates will be eligible to work as data analysts or data scientists in a multitude of areas where skills such as R or Python programming, machine learning and statistical modelling, SAS® and SPSS experience, data visualisation and data-driven decision-making are required.

The course also provides an excellent basis for further study for those wishing to pursue a higher-level research degree or embark on an industry-based research career.

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This Master's course will give you a completely new insight into how language really works and the way people use words to create meaning. Read more

Course description

This Master's course will give you a completely new insight into how language really works and the way people use words to create meaning.

If you would like to learn how to explore language using innovative techniques and computer tools, then our course will offer you cutting-edge, research-led training of the highest quality, taught by leading researchers in the fields of linguistics and computer science.

You will have options enabling you to study:
• How people use words to make meanings;
• How to analyse real language usage;
• The role of phraseology, metaphor, and idioms;
• Creative and poetic uses of language;
• New approaches to language teaching;
• Translation tools such as translation memory systems;
• Creating dictionaries using new kinds of evidence;
• Using computer tools for teaching and translation.

For further information, please download our flyer here: http://rgcl.wlv.ac.uk/wp-content/uploads/2017/01/MA-Practical-Corpus-Linguistics-for-ELT-Lexicography-and-Translation.pdf

Why choose Wolverhampton?

MA Practical Corpus Linguistics for ELT, Lexicography and Translation is an innovative, unique, and up-to-date course based on high-quality interdisciplinary research, with a selection of modules that is unparalleled both on a national and international level. Our research-led teaching is continually evolving to address the latest challenges and breakthroughs in the field. As a result, the knowledge and practical skills developed on the course will allow you to meet the most recent and relevant demands of the industry.

You will become proficient in the use of sophisticated corpus tools such as the Sketch Engine (https://www.sketchengine.co.uk), as well as state-of-the-art specialist software for professional translators and lexicographers. You will also be given an option to learn basic computer programming in Python, which is one of the most robust, popular, and widely used programming languages in the field. By the end of the course, you will have developed a unique set of transferrable skills that will make you highly competitive in the marketplace and allow you to find employment as a language professional in industry or in academia.

Figures speak louder than words: the University of Wolverhampton boasts an outstanding graduate employability rate – 98% of our postgraduate students are in work or further training six months after graduation!

What will I learn?

This course will introduce you to the use of corpora – large electronic collections of written and/or spoken text that serve as a reliable source of evidence in linguistic analysis. (‘Corpora’ is the plural of ‘corpus’.) You will learn how to design, analyse, and exploit corpora in language teaching, dictionary writing, and translation for English or any other language.

You will be given freedom and flexibility to tailor the course content to your needs and research interests as we offer a unique selection of general and specialized elective modules from which to choose. Our teaching staff will provide you with support and guidance in selecting the most suitable combination for your research topic.

Semester I will focus on developing general linguistic knowledge and research skills, which you will be able to apply to your chosen area of expertise in Semester II. You will learn about words, meanings, and linguistic creativity, broaden your knowledge of grammar, and acquire basic research and professional skills. You will also have an opportunity to learn the essentials of computer programming by attending our elective module in Python.

Semester II will introduce you to corpus linguistic methods and their application to three areas of research: language teaching, lexicography, and translation. You will start planning your dissertation and engage in one-on-one consultations with your supervisor.
For further information on modules and assessments, please visit our website: http://rgcl.wlv.ac.uk/macorling

Opportunities

As a Master's student on this course, you will be part of our Research Institute of Information and Language Processing (RIILP), an independent, research-driven University unit specializing in linguistics and natural language processing.
• You will be taught by leading researchers in the field: http://rgcl.wlv.ac.uk/macorling/who-will-teach-you-on-this-course/; our teaching staff at RIILP are engaged in high-quality research, as evidenced by the latest RAE 2008 and REF 2014 results;
• We offer an exciting programme of invited lectures and research seminars, attended by both students and staff;
• The institute has a wide network of contacts in academia and in the industry which you will be able to benefit from;
• You will also have an opportunity to travel the world – Malaga, Valencia, Besançon, Naples, Alicante, and Plovdiv are just a few of the many possible destinations covered by our institute’s Erasmus agreements.

Career path

Graduates will be able to pursue a career path in language teaching, translation, lexicography, editing, and human language technology, working either as freelancers or in a variety of industry locations, including publishing houses, translation agencies and IT companies that specialize in the development of language resources and tools (e.g. language learning applications, CAT tools). English language teachers will benefit greatly from the course, as they will develop knowledge and practical skills in using modern lexical resources, corpus data and tools in the preparation of teaching material and in the classroom, which will significantly improve their chances of securing a job in the ELT sector.

The course will also provide a sound intellectual platform for students to progress onto doctorate level study and a career in higher education. As the teaching on the course is based on research carried out within the Research Institute of Information and Language Processing (RIILP), graduates will be well-placed to continue their academic careers by applying for PhD positions within our institute or at other leading centres specializing in Corpus Linguistics, ELT/TESOL, Lexicography, Translation Studies, or Natural Language Processing.

Contact us

• Dr Sara Moze (course leader):
• April Harper (admin office):
• Research Group website: http://rgcl.wlv.ac.uk/
• Twitter: @RGCL_WLV


*Subject to approval

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The Spatial Data Science and Visualisation MSc teaches cutting-edge data analysis, mining, modelling and visualisation techniques for spatial systems. Read more
The Spatial Data Science and Visualisation MSc teaches cutting-edge data analysis, mining, modelling and visualisation techniques for spatial systems. Students carry out their own research project, supported by academics, researchers and other students in one of the most exciting, interdisciplinary research teams in the field. The programme takes place within The Bartlett, UCL’s Faculty of the Built Environment.

Degree information

Students gain a grounding in the principles and skills of spatial research, data analysis and visualisation, agent-based models and virtual environments, and develop an understanding of research methodology for data collection and analysis. Subject-specific modules provide students with the opportunity to develop skills in spatial analysis and to contribute to current debates in the field. They will learn programming skills in Java/Processing, Python, R, JavaScript and SQL, and the ability to use a range of interactive geospatial and visualisation tools (ArcGIS, Unity, Mapbox and CityEngine).

The programme consists of four core modules (60 credits), a group mini-project (30 credits), two elective modules (30 credits), and a dissertation (60 credits).

Core modules
The core modules focus on technical skills, leading to applications in mapping, visualising and analysing spatial data.
- Data Science for Spatial Systems
- Geographic Information Systems and Science
- Introduction to Programming
- Quantitative Methods
- Group Mini Project: Digital Visualisation

Elective modules
Students select two elective modules from a wide range available at UCL, subject to approval.

Dissertation/report
Dissertation

Teaching and learning
The programme is delivered through a combination of lectures, seminars, tutorials and practical-based workshops and classes. The interlinked laboratory research-based mini project with data collection focuses on ‘remote data mining’ rather than fieldwork in the traditional planning/geographical/architectural sense. Assessment is through group and individual projects and the dissertation.

Careers

Recent graduates of our related Spatial Data Science and Visualisation MRes have gone on to work as developers, in spatial analysis, and a number have continued to PhDs. Through our PhD partners, Knowledge Transfer Partnerships and substantial outreach, graduates will be able to take advantage of CASA's links to the world outside academia.

Employability
The Spatial Data Science and Visualisation MSc provides a unique skill set in computation mapping, visualisation and spatial research. Research-led skills are increasingly a key element in our understanding of complex spatial functions, particularly as vast amounts of previously unused data are becoming available either from changes in accessibility regulation or more widely as a result of new mass data collection methodologies.

Why study this degree at UCL?

The Centre for Advanced Spatial Analysis (CASA) is a research centre specialising in computational and mathematical approaches, with cutting-edge research in GIS, urban simulation, mapping, data visualisation, and 3D environments in cities and space.

Students of this programme will be exposed to a range of programming languages (Java/Processing, R, Python and MySQL), 3D visualisation packages, and be given a substantive grounding in GIS, programming structure, mathematical methods and data design.

The combination of skills involved in this programme is unique – graduates from this programme will be able to lead institutions and companies in new directions and be involved in changing cultures across the sector.

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This course is designed to provide a broad-based education in the principles and practice of GIS. Read more
This course is designed to provide a broad-based education in the principles and practice of GIS. Core modules cover issues such as the representation, acquisition, management and manipulation of spatial data; spatial analysis and modelling; remote sensing; GIS in the commercial environment; spatial databases and web-based programming. Concepts and techniques are illustrated using a variety of applications.

Key benefits

- Study to PgCert, PgDip or MSc level
- Modules may be taken in 'standalone' mode.
- Available both on-campus and by fully online distance learning
- Can be taken part-time or full-time
- Flexibility to transfer between full-time and part-time, on-campus and distance learning
- Strong focus on employable and professional skills
- Extensive hands-on practice with key software
- Entirely assessed by coursework - no formal examinations
- Established course (15 years +) with excellent reputation and feedback

Visit the website: https://www.ulster.ac.uk/course/msc-environmental-management-with-geographic-information-systems-pt-el

Course detail

- Description -

Graduates of the course are expected to have a broad overview of the field of GIS, to have extensive practical experience of GIS and related software and hardware, and be able to operate at a professional level in GIS employment.

PgDip modules cover issues such as the representation, acquisition, management and manipulation of spatial data, spatial analysis and modelling, remote sensing, GIS in the commercial environment, databases and web programming. Concepts and techniques are illustrated using a variety of applications. Students can take one optional module from a choice of GIS work experience / work-based project, GIS for environmental management, and customising GIS. Students may also opt for an environmental strand of the course.

In addition to acquiring substantial theoretical knowledge of the subject, students gain extensive practical experience using a variety of software, focusing primarily on ArcGIS but also including ERDAS Imagine, PostgreSQL, PostGIS, MySQL, OpenLayers, Geoserver, QGIS, Excel, SPSS and a number of GIS extensions and plug-ins. One of the core modules gives students experience of web-based programming languages such as HTML, CSS and JavaScript, while an optional module in customising GIS applications introduces them to Esri ModelBuilder and the Python programming language.

- Teaching and learning assessment -

Assessment is 100% by course work (no sessional examinations); a mixture of methods including practical reports, problem analysis, projects, literature reviews and essays, class tests, group work and a research project.

Students are able to use the University's extensive online resources of electronic journals, books and databases.

Career options

Successful students develop a range of skills in the management, processing, analysis, interpretation and presentation of geo-spatial data, as well as skills in project management, report writing and problem solving.

Graduates of the course have secured employment in a variety of roles in Ireland, the UK, Europe and further afield (including Australia, New Zealand, Canada and the Middle East), in GIS positions including technicians and analysts, development and sales, lecturing and research, within organisations such as mapping agencies and GIS companies, environmental consultancies, resource management and environmental agencies, planning, health services, housing authorities, local government, rural development, utilities and infrastructure, education, mining and retail analysis. Knowledge and understanding of geo-spatial data is also increasingly required in a variety of jobs outside of the GI profession, making a GIS qualification a valuable asset enhancing employability in a range of fields.

How to apply: https://www.ulster.ac.uk/apply/how-to-apply#pg

Why Choose Ulster University ?

1. Over 92% of our graduates are in work or further study six months after graduation.
2. We are a top UK university for providing courses with a period of work placement.
3. Our teaching and the learning experience we deliver are rated at the highest level by the Quality Assurance Agency.
4. We recruit international students from more than 100 different countries.
5. More than 4,000 students from over 50 countries have successfully completed eLearning courses at Ulster University.

Flexible payment

To help spread the cost of your studies, tuition fees can be paid back in monthly instalments while you learn. If you study for a one-year, full-time master’s, you can pay your fees up-front, in one lump sum, or in either five* or ten* equal monthly payments. If you study for a master’s on a part-time basis (e.g. over three years), you can pay each year’s fees up-front or in five or ten equal monthly payments each year. This flexibility allows you to spread the payment of your fees over each academic year. Find out more by visiting https://www.ulster.ac.uk/apply/fees-and-finance/postgraduate

Scholarships

A comprehensive range of financial scholarships, awards and prizes are available to undergraduate, postgraduate and research students. Scholarships recognise the many ways in which our students are outstanding in their subject. Individuals may be able to apply directly or may automatically be nominated for awards. Visit the website: https://www.ulster.ac.uk/apply/fees-and-finance/scholarships

English Language Tuition

CELT offers courses and consultations in English language and study skills to Ulster University students of all subjects, levels and nationalities. Students and researchers for whom English is an additional language can access free CELT support throughout the academic year: https://www.ulster.ac.uk/international/english-language-support

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Our MSc Computational Finance equips you with the core concepts and mathematical principles of modern quantitative finance, plus the operational skills to use computational packages (mainly Matlab) for financial modelling. Read more
Our MSc Computational Finance equips you with the core concepts and mathematical principles of modern quantitative finance, plus the operational skills to use computational packages (mainly Matlab) for financial modelling.

We provide practical, hands-on learning about how modern, highly computerised financial markets work, how assets should be priced, and how investors should construct a portfolio of assets. In addition to traditional topics in derivatives and asset pricing, we place a special emphasis on risk management in non-Gaussian environment with extreme events.

You master these areas through studying topics including:
-Non-linear and evolutionary computational methods for derivatives pricing and portfolio management
-Applications of calculus and statistical methods
-Computational intelligence in finance and economics
-Financial markets

You also graduate with an understanding of the use of artificial financial market environments for stress testing, and the design of auctions and other financial contracts.

Our Centre for Computational Finance and Economic Agents is an innovative and laboratory-based teaching and research centre, with an international reputation for leading-edge, interdisciplinary work combining economic and financial modelling with computational implementation.

Our research is geared towards real-world, practical applications, and many of our academic staff have experience of applying their findings in industry and in advising the UK government.

This course is also available on a part-time basis.

Professional accreditation

This degree is accredited by the Institution of Engineering and Technology (IET).This accreditation is increasingly sought by employers, and provides the first stage towards eventual professional registration as a Chartered Engineer (CEng).

Our expert staff

This course is taught by experts with both academic and industrial expertise in the financial and IT sectors. We bring together leading academics in the field from our departments of economics, computer science and business.

Our staff are currently researching the development of real-time trading platforms, new financial econometric models for real-time data, the use of artificially intelligent agents in the study of risk and market-based institutions, operational aspects of financial markets, financial engineering, portfolio and risk management.

Specialist facilities

We are one of the largest and best resourced computer science and electronic engineering schools in the UK. Our work is supported by extensive networked computer facilities and software aids, together with a wide range of test and instrumentation equipment.
-We have six laboratories that are exclusively for computer science and electronic engineering students. Three are open 24/7, and you have free access to the labs except when there is a scheduled practical class in progress
-All computers run either Windows 7 or are dual boot with Linux
-Software includes Java, Prolog, C++, Perl, Mysql, Matlab, DB2, Microsoft Office, Visual Studio, and Project
-Students have access to CAD tools and simulators for chip design (Xilinx) and computer networks (OPNET)
-We also have 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

Your future

We have an extensive network of industrial contacts through our City Associates Board and our alumni, while our expert seminar series gives you the opportunity to work with leading figures from industry.

Our recent graduates have gone on to become quantitative analysts, portfolio managers and software engineers at various institutions, including:
-HSBC
-Mitsubishi UFJ Securities
-Old Mutual
-Bank of England

We also work with the university’s Employability and Careers Centre to help you find out about further work experience, internships, placements, and voluntary opportunities.

Example structure

-CCFEA MSc Dissertation
-Financial Engineering and Risk Management
-Introduction to Financial Market Analysis
-Learning and Computational Intelligence in Economics and Finance
-Professional Practice and Research Methodology
-Quantitative Methods in Finance and Trading
-Big-Data for Computational Finance (optional)
-Industry Expert Lectures in Finance (optional)
-Mathematical Research Techniques Using Matlab (optional)
-Programming in Python (optional)
-Artificial Neural Networks (optional)
-High Frequency Finance and Empirical Market Microstructure (optional)
-Machine Learning and Data Mining (optional)
-Trading Global Financial Markets (optional)
-Creating and Growing a New Business Venture (optional)
-Evolutionary Computation and Genetic Programming (optional)
-Constraint Satisfaction for Decision Making (optional)

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This specialist postgraduate degree provides you with high-quality postgraduate training in bioinformatics. It provides a foundation for the development of essential bioinformatics knowledge and skills, as well as an introduction to the emerging field of systems biology. Read more
This specialist postgraduate degree provides you with high-quality postgraduate training in bioinformatics. It provides a foundation for the development of essential bioinformatics knowledge and skills, as well as an introduction to the emerging field of systems biology. The course is run in parallel with an MRes course that includes a larger research component.

The programme is designed for students from a range of scientific backgrounds, who want to pursue research training in the interdisciplinary field of bioinformatics and systems biology. It is relevant to those seeking a future career in both academia and industry.

On successful completion of this programme, students from all backgrounds should be able to:

- Understand the core concepts and statistical fundamentals that underpin the field of bioinformatics, most notably in the area of sequence analysis.
- Program in Python, and design and query databases using SQL. Experience of more advanced programming practices (such as software testing and application development) will also be gained.
- Explain core biological concepts (such as genes and genomes, protein structure and function) and growth areas such as Next Generation Sequencing and (at least at an introductory level) systems modelling.

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MSc Risk Management & Financial Engineering is a highly quantitative programme tailored to high calibre and technically-minded graduates wanting a deeper, more analytical study of risk management and financial engineering than is found in general finance programmes. Read more
MSc Risk Management & Financial Engineering is a highly quantitative programme tailored to high calibre and technically-minded graduates wanting a deeper, more analytical study of risk management and financial engineering than is found in general finance programmes.

The programme is accredited by the Professional Risk Managers’ International Association (PRMIA) and the School offers students on this programme the opportunity to attend PRMIA events, have access to its resources and receive considerable discounts on PRMIA exams.

The programme

In September you will study five foundation modules to introduce the tools of modern finance and enhance your career development skills. These include:
• Markets and Securities
• Financial Modelling
• Application of Matlab to Finance
• Data Structures and Algorithms using Python
• The Finance Industry

You’ll take eight core modules which are the backbone of our programme, providing you with a solid knowledge base in each subject area. Each module builds on previous experience while introducing new and challenging disciplines. These include:
• Empirical Finance: Methods and Applications
• Financial Engineering
• Financial Statistics
• Investments and Portfolio Management
• Risk Management and Valuation
• Stochastic Calculus

You will also receive training in Visual Basic for Applications (VBA), choose from a variety of electives and undertake a final project. The selection of electives include:
• Advanced Options Theory
• Credit Risk
• Advanced Financial Statistics
• Enterprise Risk Management
• Fixed Income Securities
• International Elective: Macro and Finance for Practitioners
• International Finance
• Insurance
• Structured Credit and Equity Products
• Private Equity and Venture Capital
• Wealth Management and Alternative Investments
• Topics in FinTech Innovation
• Big Data in Finance

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Applications are invited for the MSc in Bioinformatics and Theoretical Systems. Biology. The programme will provide an interdisciplinary training and applications. Read more
Applications are invited for the MSc in Bioinformatics and Theoretical Systems
Biology. The programme will provide an interdisciplinary training and applications
are invited from students graduating from any biological, physical, computational
or mathematical first degree course. We are keen to encourage graduates from
numerical and physical sciences to join the course.

This programme will provide students with the necessary skills to produce effective
research in Bioinformatics and Systems Biology. The course, which is based at the
South Kensington campus, has been designed and is taught by staff from the Faculties
Natural Sciences, Engineering (Computing) and Medicine.

In the first term, students take the following courses:
• Bioinformatics and Systems Biology - Introduction to biology; advanced tools for the
analysis of biological data; and approaches for modelling biological systems
• Computing - Python, R, & Unix
• Mathematics & statistical inference - high level algorithms & analysis of large datasets

The remainder of the year is devoted to three full-time research projects,
undertaken under the supervision of researchers at Imperial College.

Wellcome Trust 4 year PhD Programme

Please note there is also a separate funded 4 year PhD programme, supported by the Wellcome Trust, which starts with this Master’s course and then progresses to a three year PhD. The closing date for application is Monday 5 December 2016 for admission in October 2017. Details, including how to apply, can be found at

http://www.imperial.ac.uk/wellcome-bioinformatics-phd/

Applicants must have or be expected to obtain at least an upper second honours
degree or an equivalent overseas qualification. Please be aware that we do not
do any 'wet lab' research as part of our courses, it is purely computer based. If you
are not an EU citizen, we do not have any finance for our MSc. For further details and the application procedure
see:

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This course addresses the need to propel information-gathering and data organisation, and exploit potential information and knowledge hidden in routinely collected data to improve decision-making. Read more
This course addresses the need to propel information-gathering and data organisation, and exploit potential information and knowledge hidden in routinely collected data to improve decision-making. The course, which builds on the strength of two successful courses on data mining and on decision sciences, is more technology focused, and stretches the data mining and decision sciences theme to the broader agenda of business intelligence.

You will focus on developing solutions to real-world problems associated with the changing nature of IT infrastructure and increasing volumes of data, through the use of applications and case studies, while gaining a deep appreciation of the underlying models and techniques. You will also gain a greater understanding of the impact technological advances have on nature and practices adopted within the business intelligence and analytics practices, and know how to adapt to these changes.

Course content

Embedded into the course are two key themes. The first will help you to develop your skills in the use and application of various technologies, architectures, techniques, tools and methods. These include warehousing and data mining, distributed data management, and the technologies, architectures, and appropriate middleware and infrastructures supporting application layers. The second theme will enhance your knowledge of algorithms and the quantitative techniques suitable for analysing and mining data and developing decision models in a broad range of application areas. The project consolidates the taught subjects covered, while giving you the opportunity to pursue in-depth study in your chosen area.

Teaching approaches include lectures, tutorials, seminars and practical sessions. You will also learn through extensive course work, class presentations, group research work, and the use of a range of industry standard software such as R, Python, Simul8, Palisade Decision Tools, Hadoop and Oracle.

Taught modules may be assessed entirely through course work, or may include a two-hour exam at the end of the year.

Modules

The following modules are indicative of what you will study on this course.

Core modules
-BIG DATA THEORY AND PRACTICE
-BUSINESS ANALYTICS
-DATA MINING AND MACHINE LEARNING
-RESEARCH METHODS AND PROFESSIONAL PRACTICE
-BUSINESS SYSTEMS POSTGRADUATE PROJECT

Option modules
-ADVANCED BIG DATA ANALYTICS
-BUSINESS OPTIMISATION
-DATA VISUALISATION AND DASHBOARDING
-DATA WAREHOUSING AND OLAP
-DATA REPOSITORIES PRINCIPLES AND TOOLS
-SIMULATION MODELLING: RISK, PROCESSES, AND SYSTEMS
-WEB AND SOCIAL MEDIA ANALYTICS

Associated careers

Graduates can expect to find employment as consultants, decision modelling or advanced data analyst, and members of technical and analytics teams supporting management decision making in diverse organisations. Typical employers include local authorities, PLCs (such as GlaxoSmithKline, Prudential, Santander and Unilever), public sector organisations (such as the NHS and primarily care trusts), retail head offices, the BBC, the Civil Service and the host of banks, brokers and regulators that makeup the city, along with all the specialist support consultancies in IT and market research and forecasting, all of the whom us data for the full range of decision making.

Professional recognition

This course is accredited by the British Computer society for partial fulfilment of the academic requirement for Chartered IT professional.

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Designed for graduates who want to move into computing from another discipline, the MSc Computing and IT Management provides you with a broad technical knowledge and a sound business context for managing IT systems. Read more
Designed for graduates who want to move into computing from another discipline, the MSc Computing and IT Management provides you with a broad technical knowledge and a sound business context for managing IT systems.

Through this course you will learn the skills needed to develop business applications through a fundamental understanding of software and web development, e-commerce and database management. You will also gain an understanding of the professional skills required to lead IT managers by working as a part of a team on a business change project.

You will have the option of learning about new and emerging technologies, such as cloud computing, that are radically changing the opportunities and threats for the provision of IT systems. You may also opt for human-centric computing which focuses on defining and delivering effective information systems from a human-centric perspective. You also have the option of learning the knowledge and skills required to create interactive visualisations and explanations of data.

On successful completion of the taught phase you will move to the dissertation phase. This provides the opportunity of developing your research skills and applying technical and management concepts and techniques to solve a complex computing problem.

This one-year full-time or three-year part-time course offers a balanced combination of theory and practice, and can serve either as preparation for a career as an IT professional, doctoral research, or as a self-contained advanced qualification in its own right.

Distinctive features

• The opportunity to undertake a conversion course in Computing and IT.

• Provides an intensive course specifically designed for those who wish to move into computing and IT management from another discipline.

• Professionally accredited by the BCS, the Chartered Institute for IT.

• The opportunity to learn the technical knowledge and skills needed to develop business applications.

• Working in a team on a business change project to develop IT management skills.

• The facility to tailor the course to your interests by the selection of an advanced option module.

Structure

You will study core modules to a total of 160 credits including dissertation, with an optional module worth 20 credits. Students will also undertake an individual project.

This is a full-time course undertaken over one calendar year. It is also available as a part-time course over three years, and with placement.

Core modules:

Information Processing in Python
Web Application Development
Information Modelling & Database Systems
Business and IT Management
E-Commerce and Innovation
Dissertation

Optional modules:

Distributed and Cloud Computing
Human Centric Computing
Visual Communication and Information Design
Computer Science Topic 1: Web and Social Computing (Part-time only)

Teaching

The School of Computer Science and Informatics has a strong and active research culture which informs and directs our teaching. We are committed to providing teaching of the highest standard and received an excellent report in the most recent Quality Assurance Agency (QAA) review.

A diverse range of teaching and learning styles are used throughout the MSc in Computing and IT Management. Students will attend lectures, participate in seminars, workshops and tutorials, and carry out practical and laboratory work.

Students obtain support materials usually via Learning Central (Cardiff University’s Virtual Learning Environment).

Students will also undertake a project and independent study to enable them to complete their dissertation. Dissertation topics may be suggested by the student or chosen from a list of options proposed by academic staff reflecting their current interest.

Support

As a School, we pride ourselves on providing a supportive environment in which we are able to help and encourage our students.

All students are allocated a personal tutor who will monitor your progress throughout your time at university and will support you in your personal development planning. You will see your Personal Tutor at least once each semester.

Our Senior Personal Tutor can also advise and respond to any personal matters as they arise. The School also has a formal student-staff panel to discuss topics or issues of mutual interest.

Feedback:

Feedback on coursework may be provided via written comments on work submitted, by provision of ‘model’ answers and/or through discussion in contact sessions.

Assessment

The taught modules within the courses are assessed through examinations and a wide range of in-course assessments, such as written reports, extended essays, practical assignments and oral presentations.

The individual project and dissertation will enable students to demonstrate their ability to build upon and exploit knowledge and skills gained to exhibit critical and original thinking based on a period of independent study and learning.

Career prospects

Recent graduates from the MSc Computing and IT Management course have gained employment in roles such as systems and business analysts, quality assurance testers, IT consultants and project managers.

Graduates are employed by organisations of all sizes locally, nationally, and internationally.

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