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Quality Systems & Data Analytics - Part of Modular Certificate in Digitalisation & Project Management (DEE1)

Name: Quality Systems & Data Analytics - Part of Modular Certificate in Digitalisation & Project Management (DEE1)
Price: 1866.00 SGD

Training Provider: Ngee Ann Polytechnic

Course Reference: TGS-2024049611

S$1,866

About This Course

Quality Systems & Data Analytics - Part of Modular Certificate in Digitalisation & Project Management (DEE1) is a 60hrs module.

What You'll Learn

This module provides the students with the necessary knowledge and skills to apply quality system management principles, statistical data analysis techniques, quality improvement tools, manufacturing management concepts in their workplace. Topics covered include Quality Management & Process Improvement; Six Sigma Methodology for defect reduction; Fundamentals of Statistics & Probability; Process Capability Analysis, Statistical Hypothesis Testing; Root Cause Analysis; Repeatability & Reproducibility for measurement system analysis; Design of Experiments for optimizing and improving products and processes; Statistical Process Control for quality assurance.

Entry Requirements

The following GCE ‘O’ Level grades and with at least 1 year of relevant work experience:
– English Language (Grade 1-7)
– Mathematics (Grade 1-6)
– Science (Grade 1-6)

OR NITEC with GPA >= 3.5
OR NITEC with GPA >= 3.0 and with at least 1 year of relevant work experience

OR Higher NITEC with GPA >= 2.0
OR Higher NITEC with GPA >= 1.5 and with at least 1 year of relevant work experience

OR NITEC in Technology or Services with GPA >= 3.5 and with at least 1 year of relevant working experience

OR Higher NITEC in Technology or Services with GPA >=2.0 and with at least 1 year of relevant working experience

OR relevant Advanced WSQ Certificate (or higher) and Level 6 WSQ Workplace Literacy SOA and Workplace Numeracy SOA and with at least 1 year of relevant working experience

OR applicants with at least 2 years of relevant working experience may apply for the course

Recognition of Prior Learning (RPL)
Applicants who do not meet the entry requirements may be consider