Certificate in Science in Quality Management and Quantitative Data Analysis (Postgraduate) (Certificate in Science in Quality Management and Quantitative Data Analysis (Postgraduate))

Waterford Institute of Technology (8325)
Key Programme Details
Award

Special Purpose Award

NFQ Level

Level 9 About NFQ

Delivery Method

Blended

Mode

Part Time

ECTS Credits

20

Department

Science

General Information
Contact

Lorraine Quirke

Email

lquirke@wit.ie

Phone

051834137

Address

Springboard Administrator
School of Education and Lifelong Learning
Waterford Institute of Technology
Cork Road
Waterford

Role

Springboard Administrator

Important Dates
Application Deadline

20/09/2020

Start Date

25/09/2020

End Date

07/05/2021

About this Course

The course is comprised of two 10-credit modules:
- Strategic Quality Management
- Statistics and Data Analysis

The module Strategic Quality Management will provide the student with:
- an advanced understanding of the theory, practices and implementation issues associated with advanced quality methodologies such as Leadership, Six Sigma and Lean Manufacturing;
- the skills necessary to evaluate how lean, Six Sigma and risk management principles can be used to guide lean implementation, and to identify the key factors for effective motivation of staff applying these lean tools and techniques.
The course will also develop the student's competence in a range of technical and management quality tools, managing change, competitive advantage and demonstrate how these can be applied in an industrial environment as well as enhancing students critical-thinking, problem solving and decision making skills.

The module Statistics and Data Analysis enables students to apply statistical analysis processes to data sets, interpret the results to quantify data quality and compare data sets through use of industrially used statistical software packages. Students will learn to critically analyse real world analytical data sets using appropriate descriptive statistics tests, and/or applied inter-comparison significance tests. The student will also develop competence in a range of process control tools and minimisation strategies, and will learn to justify their usefulness to control a process. Critical evaluation of sampling plans, statistical analysis of quality, continuous improvement and data-driven decisions will be emphasised.

Entry Requirements

Applicants for entry to this programme should hold a bachelor's degree at honours level 8 minimum 2.2 in an appropriate subject area or equivalent qualification. In addition, in order to fully appreciate the industrial impact of the Quality Management and Statistics/data analysis modules within this programme, it has been deemed necessary to have a minimum of two years relevant industrial experience.

Applicants whose first language is not English must submit evidence of competency in English, please see WIT's English Language Requirements for details. http://www.wit.ie/about_wit/documents_and_policies/english_language_requirements

Long Description

The module Strategic Quality Management will provide the student with:
- an advanced understanding of the theory, practices and implementation issues associated with advanced quality methodologies such as Leadership, Six Sigma and Lean Manufacturing;
- the skills necessary to evaluate how lean, Six Sigma and risk management principles can be used to guide lean implementation, and to identify the key factors for effective motivation of staff applying these lean tools and techniques.
The course will also develop the student's competence in a range of technical and management quality tools, managing change, competitive advantage and demonstrate how these can be applied in an industrial environment as well as enhancing students critical-thinking, problem solving and decision making skills.

The module Statistics and Data Analysis enables students to apply statistical analysis processes to data sets, interpret the results to quantify data quality and compare data sets through use of industrially used statistical software packages. Students will learn to critically analyse real world analytical data sets using appropriate descriptive statistics tests, and/or applied inter-comparison significance tests. The student will also develop competence in a range of process control tools and minimisation strategies, and will learn to justify their usefulness to control a process. Critical evaluation of sampling plans, statistical analysis of quality, continuous improvement and data-driven decisions will be emphasised.

Timetable Info

• Friday 25 September 2020 a group Zoom meeting will take place at 11:00-14:00 with breaks to introduce the lecturing group and inform students of the arrangements for delivery and assessment of the module.
• A schedule will be prepared for live Zoom lectures which will be delivered on Friday 23 October 2020, Friday 13 November 2020 and Friday 04 December 2020 over a 3-hour timeframe 11:00 - 14:00 with breaks as per remote delivery; this timeline might be subject to change for the November/December dates to enable assessment/presentations.
• Lectures will be uploaded weekly to Moodle for the group to review in their own time
• Continuous assessment will be used to assess the module.

Delivery Location

WIT Main Campus

Delivery Notes

Blended

Admissions Contact Details
Contact Person

Springboard Team

Email

springboard@wit.ie