Professional Certificate in Quality Management with R
-- ViewingNowThe Professional Certificate in Quality Management with R is a comprehensive course that equips learners with essential skills in quality management and data analysis using R programming. This course emphasizes the importance of data-driven decision-making and process improvement in today's fast-paced business environment.
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⢠Introduction to Quality Management with R – Understanding the fundamental principles of quality management, the role of R in quality management, and the benefits of using R for quality improvement.
⢠Statistical Process Control (SPC) with R – Learning how to use R for SPC, including control charts, capability analysis, and process capability indices.
⢠Measurement System Analysis (MSA) with R – Understanding the importance of MSA in quality management, and how to use R for MSA techniques such as gauge R&R, bias, and linearity.
⢠Hypothesis Testing with R – Learning the basics of hypothesis testing, including null and alternative hypotheses, type I and type II errors, and p-values, and how to use R for hypothesis testing.
⢠Design of Experiments (DOE) with R – Understanding the principles of DOE, including factorial and fractional factorial designs, response surface methodology, and Taguchi methods, and how to use R for DOE.
⢠Six Sigma with R – Learning the principles of Six Sigma, including the DMAIC (define, measure, analyze, improve, control) methodology, and how to use R for Six Sigma tools such as histograms, Pareto charts, and control charts.
⢠Lean Methodologies with R – Understanding the principles of Lean, including value stream mapping, 5S, and just-in-time, and how to use R for Lean tools such as flow charts and process maps.
⢠Quality Costs with R – Learning the basics of quality costs, including prevention, appraisal, internal failure, and external failure costs, and how to use R for quality cost analysis.
⢠Quality Audits with R – Understanding the principles of quality audits, including the audit process, audit checklists, and audit reports, and how to use R for quality audit analysis.
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