Root Cause Analysis

Root Cause Analysis (RCA) is a problem-solving method aiming to identify the underlying reasons for faults or problems within a system. Coursera's RCA catalogue teaches you the principles and techniques for conducting a thorough and effective root cause analysis. You'll learn how to identify and address the root causes of problems rather than the symptoms, implement corrective actions, prevent recurrence of the issues, and promote continuous improvement. Through this skill, you'll be able to apply systematic logic, tools, and techniques such as Fishbone diagrams, 5 Whys, and Fault Tree Analysis, enhancing your problem-solving skills in various sectors including engineering, healthcare, IT, and business management.
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Results for "root cause analysis"

  • Status: Free Trial

    Skills you'll gain: Precision Medicine, Clinical Trials, Data Analysis, Data-Driven Decision-Making, Analytics, Data Science, Strategic Decision-Making, Root Cause Analysis, Random Forest Algorithm, Treatment Planning, Personalized Service, A/B Testing, Machine Learning, Online Advertising

  • Status: Free Trial

    Skills you'll gain: Statistical Process Controls, Lean Methodologies, Six Sigma Methodology, Risk Analysis, Quality Improvement, Process Improvement, Continuous Improvement Process, Process Capability, Business Process, Project Risk Management, Project Management, Root Cause Analysis, Product Design, Team Leadership

  • Skills you'll gain: Process Optimization, Process Improvement, Kaizen Methodology, Root Cause Analysis, Waste Minimization, Customer experience improvement, Business Process Improvement, Continuous Improvement Process, Performance Analysis, Employee Engagement, Performance Measurement, Job Safety Analysis

  • Status: Free Trial

    Skills you'll gain: Six Sigma Methodology, Lean Methodologies, Operational Excellence, Process Improvement, Stakeholder Management, Quality Management, Organizational Strategy, Continuous Improvement Process, Root Cause Analysis, Data-Driven Decision-Making, Data Analysis

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