Learners completing this course will be able to analyze process variation, apply Lean and Six Sigma principles, evaluate project selection methods, interpret statistical data, predict process outcomes using regression, and validate improvements through hypothesis testing.

您将学到什么
Apply Lean & Six Sigma tools to analyze and optimize processes.
Use regression, control charts & hypothesis testing for quality.
Evaluate projects, manage CTQs, and implement JIT & 5S methods.
您将获得的技能
- Sample Size Determination
- Microsoft Excel
- Process Improvement
- Quality Improvement
- Quality Management
- Process Analysis
- Six Sigma Methodology
- Lean Methodologies
- Statistical Process Controls
- Regression Analysis
- Statistical Hypothesis Testing
- Continuous Improvement Process
- Data-Driven Decision-Making
- Probability & Statistics
- Predictive Modeling
- Statistical Analysis
- Lean Manufacturing
- 技能部分已折叠。显示 9 项技能,共 17 项。
要了解的详细信息

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12 项作业
October 2025
了解顶级公司的员工如何掌握热门技能

该课程共有3个模块
This module introduces learners to the core foundations of Six Sigma, highlighting its history, principles, and integration with Lean methodology. Learners will explore the prestige of Six Sigma certifications, understand the differences between Lean and Six Sigma, and identify key process improvement methods such as the Seven Wastes (Muda) and Just-In-Time (JIT). By mastering these essentials, participants build a strong knowledge base for applying Six Sigma to real-world quality improvement initiatives.
涵盖的内容
15个视频4个作业
This module explores the practical application of Six Sigma in defining processes, assigning ownership, and aligning quality outcomes with organizational goals. Learners will gain insights into process components, project frameworks, and the importance of CTQ (Critical to Quality) and CTC (Critical to Customer) factors. Additionally, the module emphasizes structured project selection methods and the use of statistics to ensure that limited resources are directed toward the most impactful quality improvement initiatives.
涵盖的内容
9个视频4个作业
This module equips learners with advanced statistical tools and data-driven techniques essential for Six Sigma mastery. Participants will explore graphical analysis, probability concepts, and normality testing to evaluate process performance. The module also covers correlation, regression, and handling of non-normal distributions, enabling practitioners to build predictive models and uncover relationships within data. Finally, learners will apply hypothesis testing, determine correct sample sizes, and set statistical guidelines to ensure reliable, evidence-based decision-making in quality improvement projects.
涵盖的内容
14个视频4个作业
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