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Institution / Waterford Institute of Technology

Data Analysis & Research Methodologies

The Postgraduate Certificate in Data Analysis and Research Methodologies programme is aimed at those already working in the pharmaceutical, biopharmaceutical and food industries and will enable and facilitate career progression for graduates in scientific research and also in industry. This programme is also suitable for students intending to/already undertaking postgraduate research study.

The course will provide students with the skills to perform a range of data handling & analysis tools, as well as a variety of statistical tests. Computer packages such as MS Office and dedicated statistical software packages will be used for the delivery of this programme, features of which will enable the student to perform a comprehensive analysis and assessment of data quality.

The programme will also provide students with skills in accessing scientific information for preparation of literature review on specialised industry-driven research topics. The acquisition of a high standard of oral and poster presentation techniques will also be the objective of the course by providing students with the necessary skills to deliver an effective poster presentation on their research in a formal research environment.

At the end of the course, students will have developed competence in a range of transferable skills such as research skills, technical writing skills and IT skills as well as data analysis and statistical expertise.

On successful completion of this module, a student will be able to:

1. Critically evaluate information contained in the primary literature pertaining to a given research topic and determine its relative importance.

2. Collate information and write a cohesive and fully referenced literature review report on a given research topic that conforms to a high standard of technical writing.

3. Design a well-illustrated A0 poster presentation to summarise the research topic and deliver an oral presentation on this poster in a formal research environment.

4. Critically appraise analytical data quality using appropriate descriptive statistics tests.

Special Feature

The Postgraduate Certificate in Data Analysis of Research Methodologies can be taken as a stand-alone module worth 10 credits at level 9, or if the student wishes, they can use these credits towards the Postgraduate Diploma / MSc in Analytical Science with Quality Management.

Wales Ireland Network for Scientific Skills (WINSS)

This programme was developed following a Scientific Skills Survey which was conducted by the Wales Ireland Network for Scientific Skills (WINSS) team to address the scientific skills gaps within industries based in Dublin, Meath, Kildare, Waterford, Kilkenny, Wexford, Wicklow, Carlow, South Tipperary, Cork and Kerry.

The survey was sent to more than 100 companies in the pharmaceutical/biotechnology, medical device and food sectors. Transferable skills such as project management, data handling and analysis, statistics and IT skills are in high demand based on the response from 70% of the companies surveyed. Of the transferable skills listed, the skills most commonly required by the companies (84%) were training in the area of data handling and analysis.

As a direct result, the Postgraduate Certificate in Data Analysis and Research Methodologies was developed , along with the overarching Postgraduate Diploma/MSc in Analytical Science with Quality Management (WD 519/520)

Entry requirements

Data Analysis And Research Methodologies
Entry Requirements

•Applicants for entry to this Postgraduate Certificate course should hold a bachelors degree at honours level (Level 8) in an appropriate subject area or equivalent qualification.

•In addition, in order to fully appreciate the industrial impact of the analytical content of this programme, it has been deemed necessary to have a minimum of two years relevant industrial experience

•This module is worth 10 credits and can be taken singly or as part of the Postgraduate Diploma/MSc in Analytical Science with Quality Management WD519/WD520.

•Applicants whose first language is not English must submit evidence of competency in English, please see WIT’s English Language Requirements for details

Duration

4 months part-time

Careers or further progression

Students graduated with the Postgraduate Certificate will have a better employment opportunity in the research and development in pharmaceutical, biopharmaceutical and food industries.

Further study opportunities
The postgraduate certificate programme can be taken as a stand-alone module worth 10 credits at level 9, or if the student wishes, they can use these credits towards the Postgraduate Diploma/MSc in Analytical Science with Quality Management (WD 519/520)

Further enquiries

Course Leader(s)
Dr. Kathleen Grennan
Phone: +353 51302047
Email: kgrennan@wit.ie

Subjects taught

The certificate programme will be taught using a block approach on a part-time basis to facilitate people in full-time employment.

•The course will be offered every two years. The course will run subject to sufficient numbers of students.

•This programme contains a blend of lectures, tutorial sessions and IT practicals, as well as independent study.

•Over the duration of the programme, students will be required to attend WIT for approximately 10-12 days from September-December.

•Continuous assessment will be carried throughout the course of the programme.

•Lectures will be used to introduce the concepts behind a range of data handling & analysis tools, as well as a variety of statistical tests. This material will be significantly expanded upon and developed through problem-solving, an approach that will be adopted during tutorial sessions.

•Online lectures will be used to introduce the student to the variety of electronic databases available to search the scientific literature, and also to demonstrate how to use features of MS Office to compile a literature review and A0 poster presentation on a chosen research topic.

•IT practicals will also be used to demonstrate how data analysis tools and dedicated statistical software packages can be used to evaluate relationships in scientific data.

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