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.
Six Sigma Black Belt: Analyze, Improve & Control
Gain insight into a topic and learn the fundamentals.
1 week to complete
at 10 hours a week
Flexible schedule
Learn at your own pace
What you'll learn
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.
Skills you'll gain
- Predictive Modeling
- Lean Manufacturing
- Continuous Improvement Process
- Statistical Analysis
- Regression Analysis
- Probability & Statistics
- Quality Improvement
- Statistical Hypothesis Testing
- Statistical Process Controls
- Process Improvement
- Quality Management
- Six Sigma Methodology
- Data-Driven Decision-Making
- Sample Size Determination
- Process Analysis
- Microsoft Excel
- Lean Methodologies
Details to know
Shareable certificate
Add to your LinkedIn profile
Recently updated!
October 2025
Assessments
12 assignments
Taught in English
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There are 3 modules in this course
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.
What's included
15 videos4 assignments1 plugin
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.
What's included
9 videos4 assignments
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.
What's included
14 videos4 assignments
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Frequently asked questions
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