Data Science

PgCert

2023/24 Part-time Postgraduate course

Award:

Postgraduate Certificate

Faculty:

Faculty of Computing, Engineering and the Built Environment

School:

School of Computing, Engineering and Intelligent Systems

Campus:

Magee campus

Start date:

September 2023

Overview

Providing high quality professionals for the Data Science industry.

The University regularly ‘refreshes’ courses to make sure they are as up-to-date as possible.

In addition it undertakes formal periodic review of courses in a process called 'revalidation’ to ensure that they continue to meet standards and are current and relevant.

This course will be revalidated in the near future and it is possible that there will be some changes to the course as described in this prospectus.

Summary

If you have previous computing experience and want to build skills to develop your career, then this is the perfect opportunity for you to begin to specialise in Data Science, a key growth area within the IT sector.

Data Science skills are typically in high demand in many industries including IT, business, security, health, intelligent transport, energy, and the creative industries. Data and analytics capabilities has developed rapidly in recent years. The volume of available data has grown exponentially, more sophisticated algorithms have been developed, and computational power and storage have steadily improved. Most companies, however, are not capturing the full potential value from data and analytics because they do not have the required expertise.

To help address these challenges, the Postgraduate Certificate in Data Science will provide you with the knowledge and skills in key technologies used in data collection, curation, processing, integration, analysis, and visualisation, applied to a variety of data types. Students will be introduced to a data scientist toolkit that can be applied to build data-driven applications.


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About this course

About

This specialist postgraduate course in Data Science is aimed at highly-motivated graduates with a good Honours or non-Honours degree in computing, engineering or a related discipline. While the course has a particular focus on the employment needs of the local economy, the skills and abilities developed are easily transferred to a more global stage.

A major challenge for companies is attracting and retaining the right talent—not only data scientists but business translators who combine data savvy with industry and functional expertise. The science of extracting information from data continues to increase in importance in various disciplines in which the large volume and complexity of the data imposes unprecedented challenges to the data analysis approaches traditionally employed in these disciplines. This course enables graduates to build skills for career development and begin to specialise in the general area of data science.

Modules

Here is a guide to the subjects studied on this course.

Courses are continually reviewed to take advantage of new teaching approaches and developments in research, industry and the professions. Please be aware that modules may change for your year of entry. The exact modules available and their order may vary depending on course updates, staff availability, timetabling and student demand.

  • Data Science Foundations:The focus of this module is to present an understanding of key data science concepts, tools and programming techniques. Within the arena of data science, the theory behind the approaches of statistics, modelling and machine learning will be introduced emphasising their importance and application to data analysis. The notion of investigative and research skills will also be introduced through a number of problem solving exercises. Material covered will be contextualised by providing examples of the latest research within the area. Students will also be introduced to programming with Python. They will learn the basics of syntax, and how to configure their development environment for implementation and testing of algorithms related to data science.
  • Big Data and Infrastructure:Within this module a variety of database and data storage paradigms will be explored, ranging from more traditional relational systems to NoSql and object stores, time series databases, semantic store and graph stores. Consideration will be given to big data and the problem with storing and querying high volumes of highly variable data which is stored and processed at a high speed. The cloud computing paradigm will also be introduced and how to avail of its power and resources. The core concepts of distributed computing will be examined in the context of Hadoop. Students will be taught, practically and theoretically, about the components of Hadoop, workflows, functional programming concepts, use of MapReduce, Spark, Pig, Hive and Sqoop.
  • Business Intelligence:This module aims to contextualise the role of Business Intelligence (BI) and why we need BI systems. A particular focus will be on how to turn already stored data into valuable information and why this is important. Vast amounts of data regarding company's customers and operations is routinely collected and stored in large corporate data warehouses. This data can be of immense value if properly analysed. Students will explore techniques and tools for data analysis, and presentation of the results to non-technical and managerial staff, in alignment with business strategies. Big Data technologies do offer BI however, they are open to certain ethical and consent issues along with risks. These will be analysed, reviewed and evaluated.

Ulster University academics are actively involved in both research and teaching and this ensures that the developments accrued through research can feed into the teaching of students. A high percentage of staff are members of the Higher Education Academy, and all staff are expected to have a Postgraduate Certificate in Higher Education Practice/University Teaching or equivalent. All Computing courses are subject to periodic Faculty Review and University Revalidation.

On successful completion of the programme, students can continue on to our MSc Data Science or our MSc Professional Software Development (Data Science). Both MSc programmes are available as full-time or part-time study options.

Attendance

This is a part-time programme which begins in September and the three modules will be delivered across two semesters.

Start dates

  • September 2023

Teaching, Learning and Assessment

Teaching is delivered through a combination of lectures, directed tutorials, seminars and practical sessions.

The course is assessed by coursework.

The content for each course is summarised on the relevant course page, along with an overview of the modules that make up the course.

Each course is approved by the University and meets the expectations of:

Attendance and Independent Study

As part of your course induction, you will be provided with details of the organisation and management of the course, including attendance and assessment requirements - usually in the form of a timetable. For full-time courses, the precise timetable for each semester is not confirmed until near the start date and may be subject to change in the early weeks as all courses settle into their planned patterns. For part-time courses which require attendance on particular days and times, an expectation of the days of attendance will often be included in the letter of offer. A course handbook is also made available.

Courses comprise modules for which the notional effort involved is indicated by its credit rating. Each credit point represents 10 hours of student effort. Undergraduate courses typically contain 10- or 20-credit modules and postgraduate course typically 15- or 30-credit modules.

The normal study load expectation for an undergraduate full-time course of study in the standard academic year is 120 credit points. This amounts to around 36-42 hours of expected teaching and learning per week, inclusive of attendance requirements for lectures, seminars, tutorials, practical work, fieldwork or other scheduled classes, private study, and assessment. Part-time study load is the same as full-time pro-rata, with each credit point representing 10 hours of student effort.

Postgraduate Masters courses typically comprise 180 credits, taken in three semesters when studied full-time. A Postgraduate Certificate (PGCert) comprises 60 credits and can usually be completed on a part-time basis in one year. A 120-credit Postgraduate Diploma (PGDip) can usually be completed on a part-time basis in two years.

Class contact times vary by course and type of module. Typically, for a module predominantly delivered through lectures you can expect at least 3 contact hours per week (lectures/seminars/tutorials). Laboratory classes often require a greater intensity of attendance in blocks. Some modules may combine lecture and laboratory. The precise model will depend on the course you apply for and may be subject to change from year to year for quality or enhancement reasons. Prospective students will be consulted about any significant changes.

Assessment

Assessment methods vary and are defined explicitly in each module. Assessment can be via one method or a combination e.g. examination and coursework . Assessment is designed to assess your achievement of the module’s stated learning outcomes. You can expect to receive timely feedback on all coursework assessment. The precise assessment will depend on the module and may be subject to change from year to year for quality or enhancement reasons. You will be consulted about any significant changes.

Coursework can take many forms, for example: essay, report, seminar paper, test, presentation, dissertation, design, artefacts, portfolio, journal, group work. The precise form and combination of assessment will depend on the course you apply for and the module. Details will be made available in advance through induction, the course handbook, the module specification and the assessment timetable. The details are subject to change from year to year for quality or enhancement reasons. You will be consulted about any significant changes.

Normally, a module will have four learning outcomes, and no more than two items of assessment. An item of assessment can comprise more than one task. The notional workload and the equivalence across types of assessment is standardised.

Calculation of the Final Award

The class of Honours awarded in Bachelor’s degrees is usually determined by calculation of an aggregate mark based on performance across the modules at Levels 5 and 6 (which correspond to the second and third year of full-time attendance).

Level 6 modules contribute 70% of the aggregate mark and Level 5 contributes 30% to the calculation of the class of the award. Classification of integrated Masters degrees with Honours include a Level 7 component. The calculation in this case is: 50% Level 7, 30% Level 6, 20% Level 5. At least half the Level 5 modules must be studied at the University for Level 5 to be included in the calculation of the class.

All other qualifications have an overall grade determined by results in modules from the final level of study. In Masters degrees of more than 200 credit points the final 120 points usually determine the overall grading.

Figures correct for academic year 2019-2020.

Academic profile

The University employs over 1,000 suitably qualified and experienced academic staff - 59% have PhDs in their subject field and many have professional body recognition.

Courses are taught by staff who are Professors (25%), Readers, Senior Lecturers (20%) or Lecturers (55%).

We require most academic staff to be qualified to teach in higher education: 82% hold either Postgraduate Certificates in Higher Education Practice or higher. Most academic staff (81%) are accredited fellows of the Higher Education Academy (HEA) by Advanced HE - the university sector professional body for teaching and learning. Many academic and technical staff hold other professional body designations related to their subject or scholarly practice.

The profiles of many academic staff can be found on the University’s departmental websites and give a detailed insight into the range of staffing and expertise.  The precise staffing for a course will depend on the department(s) involved and the availability and management of staff.  This is subject to change annually and is confirmed in the timetable issued at the start of the course.

Occasionally, teaching may be supplemented by suitably qualified part-time staff (usually qualified researchers) and specialist guest lecturers. In these cases, all staff are inducted, mostly through our staff development programme ‘First Steps to Teaching’. In some cases, usually for provision in one of our out-centres, Recognised University Teachers are involved, supported by the University in suitable professional development for teaching.

Figures correct for academic year 2021-2022.

Magee campus

Accommodation

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Sports Facilities

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Student Wellbeing

At Student Wellbeing we provide many services to help students through their time at Ulster University.

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Magee Campus Location

Campus Address

Ulster University,
Northland Rd,
Londonderry
BT48 7JL

T: 02870 123 456

Standard entry conditions

We recognise a range of qualifications for admission to our courses. In addition to the specific entry conditions for this course you must also meet the University’s General Entrance Requirements.

Entry Requirements

Applicants must:

(a) have gained

(i) an Honours or non-Honours degree in the subject areas of computing, engineering or related discipline from a University of the United Kingdom or the Republic of Ireland, or from a recognised national awarding body, or from an institution of another country which is recognised as being of an equivalent standard;

or

(ii) an equivalent standard in a Graduate Certificate or Graduate Diploma or an approved alternative qualification in the subject areas of computing, engineering or related discipline;

and

(b) provide evidence of competence in written and spoken English (GCSE grade C or equivalent);

In exceptional circumstances, as an alternative to (a) (i) or (a) (ii) and/or (b), where an individual has substantial and significant experiential learning, a portfolio of written evidence demonstrating the meeting of graduate qualities (including subject-specific outcomes, as determined by the Course Committee) may be considered as an alternative entrance route. Evidence used to demonstrate graduate qualities may not be used for exemption against modules within the programme.

English Language Requirements

English language requirements for international applicants
The minimum requirement for this course is Academic IELTS 6.0 with no band score less than 5.5. Trinity ISE: Pass at level III also meets this requirement for Tier 4 visa purposes.

Ulster recognises a number of other English language tests and comparable IELTS equivalent scores.

Exemptions and transferability

The entry requirements facilitate accreditation of prior learning.

Careers & opportunities

Career options

The key message from employability and work-related learning initiatives is that enhancing opportunities to develop work-related learning and employability enhances the learning of the subject being studied. We understand the importance of including real industrial and commercial contexts to our student's experience, so this Postgraduate Certificate in Data Science will pursue opportunities for industrially linked teaching material and student project work.

A recent statement from Ulster University’s Careers Office indicates that Data Analysts are in high demand across all sectors, such as finance, consulting, manufacturing, pharmaceuticals, government and education. Data analysts can work in large companies such as the ‘big four’ consultancies or financial services firms, or consumer retail firms, small and medium sized businesses such as marketing agencies’ or the public sector.

Work placement / study abroad

This programme does not include a work placement.

Apply

Start dates

  • September 2023

Fees and funding

2023/24 Fees

Our postgraduate fees are subject to annual increase and are currently under review. See our tuition fees page for the current fees for 2022/23 entry.

Additional mandatory costs

None

It is important to remember that costs associated with accommodation, travel (including car parking charges) and normal living will need to be covered in addition to tuition fees.

Where a course has additional mandatory expenses (in addition to tuition fees) we make every effort to highlight them above. We aim to provide students with the learning materials needed to support their studies. Our libraries are a valuable resource with an extensive collection of books and journals, as well as first-class facilities and IT equipment. Computer suites and free Wi-Fi are also available on each of the campuses.

There are additional fees for graduation ceremonies, examination resits and library fines.

Students choosing a period of paid work placement or study abroad as a part of their course should be aware that there may be additional travel and living costs, as well as tuition fees.

See the tuition fees on our student guide for most up to date costs.

Contact

We’d love to hear from you!

We know that choosing to study at university is a big decision, and you may not always be able to find the information you need online.

Please contact Ulster University with any queries or questions you might have about:

  • Course specific information
  • Fees and Finance
  • Admissions

For any queries regarding getting help with your application, please select Admissions in the drop down below.

For queries related to course content, including modules and placements, please select Course specific information.

We look forward to hearing from you.


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Disclaimer

  1. The University endeavours to deliver courses and programmes of study in accordance with the description set out in this prospectus. The University’s prospectus is produced at the earliest possible date in order to provide maximum assistance to individuals considering applying for a course of study offered by the University. The University makes every effort to ensure that the information contained in the prospectus is accurate but it is possible that some changes will occur between the date of printing and the start of the academic year to which it relates. Please note that the University’s website is the most up-to-date source of information regarding courses and facilities and we strongly recommend that you always visit the website before making any commitments.
  2. Although reasonable steps are taken to provide the programmes and services described, the University cannot guarantee the provision of any course or facility and the University may make variations to the contents or methods of delivery of courses, discontinue, merge or combine courses and introduce new courses if such action is reasonably considered to be necessary by the University. Such circumstances include (but are not limited to) industrial action, lack of demand, departure of key staff, changes in legislation or government policy including changes, if any, resulting from the UK departing the European Union, withdrawal or reduction of funding or other circumstances beyond the University’s reasonable control.
  3. If the University discontinues any courses, it will use its best endeavours to provide a suitable alternative course. In addition, courses may change during the course of study and in such circumstances the University will normally undertake a consultation process prior to any such changes being introduced and seek to ensure that no student is unreasonably prejudiced as a consequence of any such change.
  4. The University does not accept responsibility (other than through the negligence of the University, its staff or agents), for the consequences of any modification or cancellation of any course, or part of a course, offered by the University but will take into consideration the effects on individual students and seek to minimise the impact of such effects where reasonably practicable.
  5. The University cannot accept any liability for disruption to its provision of educational or other services caused by circumstances beyond its control, but the University will take all reasonable steps to minimise the resultant disruption to such services.