Senior Lecturer

Data Analytics (with Placement) - UH-000079

Requirements apply to students taking a BCS accredited course. Please refer to the Programme Specification Document under Section 18 'Regulation of Assessment' for details.

The University of Huddersfield seeks and encourages applicants in order to widen participation, improve access and apply the principles of equal opportunities. We provide support for applicants who require additional assistance in order to select the right course of study and make a successful transition to studying at University. We encourage local, national and international applications. Further information for <a href="http://www.hud.ac.uk/international">International Students can be found on their website</a>.
If you were educated outside the UK, you are required to have International English Language Testing System (IELTS) at a score of 6.0 with a minimum score of 6.0 in writing and a minimum of 5.5 in any single component. For the MSc Cyber Security and Digital Forensics with Placement course, the minimum for IELTS is 7.0 overall with 6.5 in any single component. If you have alternative qualifications or do not meet the IELTS requirement we also offer a range of <a href="http://www.hud.ac.uk/international/pre-sessionalenglishprogramme/">Pre-Sessional English Programmes</a>.
The University provides opportunities for the accreditation of prior learning (APL) as stated in section 3 of the <a href="https://www.hud.ac.uk/policies/registry/awards-taught/section-3/">Regulations for Awards</a>.
The University’s general minimum entry requirements are specified in Section 1.5 of the <a href="https://www.hud.ac.uk/policies/registry/awards-taught/section-1/">Regulations for Awards</a> and the <a href="https://www.hud.ac.uk/media/policydocuments/Admissions-Policy-Taught-Courses.pdf">Admissions Policy</a>.
Every person who applies for this course and meets the minimum entry requirement – regardless of any disability – will be given the same opportunity in the selection process. General advice and information regarding disability and the support the University can give can be found by contacting student services as follows:
Telephone: 01484 472675
Email: disability@hud.ac.uk
Further information is available on the <a href="https://students.hud.ac.uk/help/disability/">disability support website</a>.
Further advice on the specific skills and abilities needed to successfully undertake this course can be found by contacting the admissions tutor and by visiting our <a href="https://courses.hud.ac.uk/">course finder website page</a>.
Entry requirements for this course are normally:
<ul>
<li>A BA, BSc or BEng Honours degree (2:1 or above) or equivalent professional qualification in any subject.</li>
<li>Applicants with other appropriate professional qualifications and/or experience will be considered on an individual basis.</li>
<li>If your first language is not English, you will need to meet the minimum requirements of an English Language qualification. The minimum for IELTS is 7.0 overall with no element lower than 6.5, or equivalent will be considered acceptable. Read more about the University’s entry requirements for students outside of the UK on our Where are you from information pages.</li>
</ul>

MSc Data Analytics (with Placement)
The MSc Data Analytics (with Placement) is awarded when students complete 240 credits on an approved course of study, which consists of,
<ul>
<li>180 credits of the MSc, consisting of: 120 credit - taught modules and 60 credit - individual project module - ‘Advanced Technical Project’,</li>
<li>And also 60 – credit Placement module - ‘Professional Development and Practice’.</li>
</ul>
The following regulations apply to MSc Data Analytics (with Placement):
<ul>
<li>The “MSc with Placement” route is full-time and therefore does not apply to part-time students.</li>
<li>In order to be eligible to take up the placement that they have found, a student must pass all 180-credits of the MSc course, confirmed at the appropriate Course Assessment Board (CAB).</li>
<li>Students on the “MSc with Placement” wishing to progress onto the placement module should be in good standing with the University and have confirmed, and had their placement approved, with the School before the end of the 12 month taught period.</li>
<li>September starters will usually begin their placement around October/November after the term 3 CAB.</li>
<li>January starters will usually begin placement around February/March after the term 1 CAB.</li>
<li>Securing a placement is the responsibility of the student. Placements will be assessed for their suitability by the School in terms of their ability to fulfil the Learning Outcomes for the CSP3501/NSP3501 Professional Development and Practice module.</li>
<li>Placements should last between 18 and 24 weeks. Students who do not have an agreed placement before the end of the 12-month taught period will exit with the award of MSc Data Analytics.</li>
<li>Any student failing the placement will not be able to retake this module and will be awarded the MSc Data Analytics.</li>
</ul>
PgCert Data Analytics
The PgCert Data Analytics consists of a 60-credit taught programme in which students must acquire the following credits: 60 credits from any 4 taught modules.
PgDip Data Analytics
The PgDip Data Analytics consists of a programme in which students must acquire 120 credits as follows: All taught modules but no project or any 4 modules plus project.

UH-000079 - Data Analytics (with Placement)

Masters Core

Masters Compulsory

Masters Optional

Masters Level

Structure

An approved exception to the University of Huddersfield's Regulations for Awards is in place to allow this Master's with Advanced Professional Practice course to include "(with Placement)" at the end of the course title, rather than the standard "(Advanced Professional Practice)".
The following course regulation will be applicable from academic year 2022-2023 for those students wanting to partially or fully meet the requirements for Chartered Engineer (CEng). The regulation is not applicable nor required for meeting requirements for Chartered IT Professional (CITP).
<ul>
<li>A maximum of 15 credits in a Master’s degree can be condoned (termed Compensation by the Engineering Council).</li>
</ul>

Postgraduate Certificate

Postgraduate Diploma

Master of Science

Conduct a substantial self-managed project, in a professional, methods-driven manner.

Communicate complex ideas in both written and oral form to technical and non-technical researchers and practitioners.

Produce high quality evidence and documentation of the processes and practices of analysis, design, implementation and evaluation of DA related problems and solutions.

Have an in-depth knowledge of how to analyse large amounts of unstructured data using massively parallel and scalable cloud computation systems.

Gather, organise and deploy ideas and information in order to formulate arguments cogently, and express them effectively using a range of media.

Have a systematic understanding of the theoretical concepts and techniques of data science and its applications.

Demonstrate advanced problem-solving and evaluation skills in meeting the needs of different stakeholders and make informed decisions to satisfy them.

Demonstrate a sound understanding of professional development planning for career enhancement.

Have a comprehensive understanding of appropriate file system architectures used with large data sets.

Have a comprehensive understanding of one or more tools for the development of solutions to data analysis problems.

Have a systematic understanding of what Big Data is, where it comes from and the key challenges it presents.

Have an in-depth knowledge of statistical techniques to support data analysis.

Research advances in data science in an insightful manner.

Use a variety of skills to solve complex problems – demonstrating the ability to create, identify and evaluate options and then to implement and subsequently review the decisions.

Exercise critical judgement in the selection and use of various tools and techniques within the DA domain appropriate to the given project.

Effectively apply the theoretical concepts, techniques and/or tools to develop solutions for data analysis problems.

Have a sound knowledge of legal issues arising from any DA project and the decisions required to resolve them.

Assess and respond to the needs for continuing professional development and lifelong learning in a rapidly changing and evolving industry.

Synthesise a range of information and data from a variety of sources within the subject domain.

Have a comprehensive understanding of where such techniques differ to those of traditional IS application development.

Have a critical appreciation of the latest and emerging data analytics (DA) techniques and be able to critically evaluate the current and emerging technological trends.

Critically analyse and apply a range of concepts, principles and practices within the DA domain.

Demonstrate information retrieval skills, including on-line searches and primary literature research skills.

Have a sound knowledge of professional ethics in the DA context.

Develop good time management and organisational skills – the ability to initiate, co-ordinate and direct programmes of work and study, including a major research project.

<ul>
<li>The School Teaching and Learning Committee, a sub-committee of the University Teaching and Learning Committee, is tasked with implementing the University’s teaching and learning strategy and with fostering innovation in teaching and learning and the dissemination of good practice.</li>
<li>The School Board, via the School Teaching and Learning Committee has responsibility for implementing University policy through school-defined procedures.</li>
<li>Periodic school and subject reviews take place on a rolling quinquennial programme and focus inter alia on the arrangements for quality management and enhancement, teaching, learning and assessment, C&amp;IT strategies, the articulation and assurances of standards, external examiner reports and evaluation and links with professional bodies, employers and other external organisations.</li>
<li>The Course Committee is responsible for the monitoring and development of the course or programme, taking account of feedback from staff, students and external examiners. Feedback is sought as follows:
<ul>
<li>From students through annual course and module evaluation questionnaires.</li>
<li>From external examiners through annual reports, course assessment board minutes, assessment moderation reports and informal verbal communication during the year.</li>
<li>The annual evaluation of the course/programme is the responsibility of the School Board. The Course Committee prepares an annual evaluation report comprising reporting and evaluation, informed by feedback from staff, students and external examiners and by statistical data.</li>
</ul>
</li>
<li>Amendments to course/programme and module documents are validated by the School Accreditation and Validation Panel.</li>
<li>A process for peer observation of teaching is in place with the object of enhancing teaching practice and sharing ideas between staff.</li>
</ul>

UH-000079

The latest subject review for the subject area that includes this course took place in January 2021. The panel commended the subject area for, among others, the strong links with industry which offers clear benefits for students and the ambitious plans for curriculum development.

<ul>
<li>Supporting documentation is provided, online, in the form of Student Handbooks, Module Handbooks, Programme Specification Documents (PSD) and Module Specification Documents (MSD).</li>
<li>The Course Leader is available to provide guidance on academic progress.</li>
<li>Module tutors are available to help with academic problems during term time, either on campus or through electronic means such as Microsoft Teams, to facilitate support for distance learning students.</li>
<li>All modules and year groups are supported on the Virtual Learning Environment.</li>
</ul>