Instructor-Led Lean Six Sigma Master Black Belt Training & Certification | AI-Powered
Upcoming Instructor-Led Lean Six Sigma Master Black Belt Training & Certification | AI-Powered Training Programs and Certification Cost
August
40 Hours E-Learning + 40 Hours of Instructor Led Training + 56 Hours of Project Mentoring
Instructor-Led Training
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1. E-Learning
₹20,800
2. Option 1 + Live Training & Project Mentoring
₹38,800
3. Option 2 + Certificate
₹48,800
Everything You Need to Know About the Instructor-Led Lean Six Sigma Master Black Belt Training & Certification | AI-Powered Program
Instructor-Led Lean Six Sigma Master Black Belt Training & Certification | AI-Powered
At the top of the Lean Six Sigma journey stands a select group of professionals who don't just solve problems—they build systems, shape strategy, and coach change-makers. These are the Master Black Belts—the trusted advisors to senior leadership, the architects of enterprise-wide excellence, and the mentors behind high-performing teams.
If you're ready to operate at this level, then this program is for you.
The Lean Six Sigma Master Black Belt (MBB) Certification by Lean6SigmaPro is designed to groom top-tier leaders, enterprise coaches, and strategic transformation experts who are equipped to drive impact at scale. This is not just a course—it’s a leadership journey for those who want to set the direction for process excellence across functions and industries.
🎯 Why Choose Lean6SigmaPro Lean Six Sigma Master Black Belt Program?
✅ Built and Trained by a Transformation Leader
✅ Enterprise-Level Strategy and Coaching
✅ Advanced Tools + Real-World Playbooks
✅ Mentor of Mentors
I'm privileged to be trained by him.
Duration
- 40+ Hours of Instructor-Led Online Training
- 56+ Hours Project Mentoring
- 40+ Hours of E-Learning (Lifetime access)
Certification
- Exemplar Global.
Objective
Who Should Attend?
- Certified Black Belts with a minimum of five project experience
- Any professional seeking to accelerate their corporate career
- Anyone who wants to consider Lean Six Sigma as a career option
- Certified Master Black Belts would like to transform themselves as Architects of Lean Six Sigma.
Project Assistance
Trainers Profile
- Certified Master Black Belt & a passionate trainer
- Over 20 years in the field of Lean Six Sigma
- Executed/Mentored over 400 Lean Six Sigma projects with $40+ savings.
- Trained over 12,000 professionals across industries.
- Corporate Lean Six Sigma trainer for Fortune 50 Companies
Srinivas TV - Click to view full profile
Course Fee Includes
- 40+ hours of Instructor-Led Training
- 40+ hours of High-Quality E-learning
- 56+ hours of Project Mentoring (6 Projects)
- 100+ Business scenarios
- One year of access to the E-Learning portal
- Sample question papers with solutions
- Examination & Certification cost
- Unlimited post-certification support
- Exclusive invite to attend Six Sigma project presentations.
- Mentorship & assistance to accelerate your corporate career.
- 100% Placement assistance
Course Program
- 1.0 Introduction to Lean
- 2.0 What is Lean & Application of Lean
- 3.0 6S Before Lean(Simulation to Understand)
- 4.0 Types of Waste – (Videos &Simulation to Understand)
- 4.1 Different Types of Wastes
- 4.2 Causes of Waste
- 4.3 Remedies of Waste
- 5.0 Lean Principles Introduction
- 5.1 Identify Customers & Specify Value
- 5.2 Value Stream Mapping
- 5.3 Create Flow
- 5.4 Respond to Pull
- 5.5 Pursuit Perfection
- 6.0 Identify Customers & Specify Value
- 6.1 Customer – Internal & External
- 6.2 Value Added & Non-Value Added (Simulation to Understand)
- 7.0 Create Value Stream Mapping (VSM) (Simulation to Understand)
- 7.1 Terminologies (CT, FTY, RTY, CO, TPT, WIP, WIQ)
- 7.2 Process Efficiency
- 7.3 Customer Takt time
- 7.4 Create VSM(Simulation to Understand)
- 7.5 Process Efficiency
- 8.0 Create Value Stream Design (VSD) (Simulation to Understand)
- 9.0 Create Flow & Respond to Pull (Simulation to Understand)
- 9.1 Single Piece Flow (Simulation to Understand)
- 9.2 Single Minute of Exchange of Dies(Simulation to Understand)
- 9.3 Line Balancing (Simulation to Understand)
- 9.4 Kanban (Pull Production) (Simulation to Understand)
- 9.5 Heijunka (Production Levelling)(Simulation to Understand)
- 9.6 Just In Time(Simulation to Understand)
- 10.0 Additional Lean Tools
- 10.1 Spaghetti Diagram
- 10.2 Circle Diagram
- 10.3 Total Productive Maintenance
- 10.4 Andon & Visual Management
- 10.5 Visual Factory
- 10.6 Gemba
- 10.7 Hoshin Kanri (Policy Deployment)
- 10.8 PDCA (Plan Do Check Act)
- 10.9 Poka-Yoke (Mistake Proofing) (Simulation to Understand)
- 10.10 Root Cause Analysis
- 10.11 Standardized Work (Simulation to Understand)
- 10.12 Theory of Constraints (Introduction)
- 1.0 Introduction to Quality
- 2.0 Quality Leaders (Juran, Deming, Shewhart, Ishikawa) (Videos to Understand)
- 3.0 Cost of Quality (COQ)
- 4.0 Cost of Poor Quality (COPQ) (Videos to Understand)
- 5.0 Optimum Quality Levels
- 6.0 Failure Mode & Effect Analysis (FMEA)
- 6.1 Create Process FMEA (Simulation to Understand)
- 6.2 Create Design FMEA
- 7.0 Key Performance Measures
- 7.1 Key Performance Indictors
- 7.2 Customer Satisfaction
- 7.3 Product Differentiation
- 7.4 Customer Loyalty Metrics
- 7.5 Leading & Lagging Indicators
- 7.6 Create Line of Sight
- 8.0 Key Business Drivers & their Impact
- 8.1 Profit/Margin (Practice to Understand)
- 8.2 Market Share
- 8.3 Net Present Value (NPV)
- 8.4 Cost Benefit Analysis (CBA)
- 8.5 Hard & Soft Benefits (Practice to Understand)
- 8.6 Cost avoidance & Cost reduction (Practice to Understand)
- 9.0 Organisation Goals & Six Sigma
- 10.0 Balanced Score Card& Six Sigma
- 11.0 History & Evolution of Six Sigma
- 12.0 Continuous Improvement
- 13.0 Basics of Six Sigma (Simulation to Understand)
- 14.0 Six SigmaApplications
- 15.0 Types of Six Sigma Projects
- 15.1 DMAIC
- 15.2 DFSS (DMADV/IDOV)
- 16.0 Organization Road Blocks
- 16.1 Organisation Structure & Culture
- 16.2 Common Causes of Six Sigma Failures
- 16.3 Stakeholder Analysis (Six Sigma Impact)
- 17.0 Change Management (Simulation & Videos to Understand)
- 17.1 Basics of Change Management
- 17.2 Readiness Assessment
- 17.3 Communication Plans to Overcome Barriers
- 18.0 Strategic Planning & Deployment
- 18.1 Importance of Lean Six Sigma
- 18.2 Hoshin Kanri (Policy Deployment) (Practice to Understand)
- 18.3 SWOT Analysis (Practice to Understand)
- 18.4 PEST
- 18.5 Business Contingency Planning
- 19.0 Team Management (Simulation & Videos to Understand)
- 19.1 Team Types & Constraints
- 19.2 Team Roles &Responsibilities
- 19.3 Team Member Selection Criteria
- 19.4 Team Success Factors
- 20.0 ProjectTeam Dynamics (Simulation to Understand)
- 20.1 Forming
- 20.2 Storming
- 20.3 Norming
- 20.4 Performing
- 20.5 Team Communication
- 21.0 Team Facilitation
- 21 Motivational Technique
- 22 Team Stages & Development
- 23 Team Communication
- 24 Team Leadership & Models
- 22.0 Team Dynamics (Simulation & Videos to Understand)
- 22.1 Group Behaviour
- 22.2 Meeting Management
- 22.3 Team Decision Making Methods
- 23.0 Team Training (Simulation to Understand)
- 23.1 Need Assessment
- 23.2 Delivery
- 23.3 Evaluation
- 1.0 Voice of Customer & Business(Simulation to Understand)
- 1.1 Collect Customer & Business Voices
- 1.2 Eliminate Vagueness & Ambiguity
- 1.3 VOC Clarity Table
- 2.0 Kano Model (Practice to Understand)
- 3.0 Benchmarking
- 3.1 Competitive
- 3.2 Collaborative
- 3.3 Best Practices
- 4.0 Customer Requirements to Process Requirements
- 4.1 Critical to X (X-Quality, Cost, Safety or any other )
- 4.2 CTQ Drill Down
- 4.3 Quality Function Deployment (Practice to Understand)
- 5.0 Project Section & Prioritisation (Practice to Understand)
- 6.0 Process Owners & Stakeholder Analysis
- 7.0 Project Charter (Practice to Understand)
- 7.1 Business Case
- 7.2 Problem Statement
- 7.3 Project Goal Statement
- 7.4 Project Team
- 7.5 Project Timeline
- 7.6 Project Scope
- 7.7 Expected Benefits
- 8.0 Financial Evaluation & Business Case
- 9.0 Develop Project Metrics
- 10.0 Project Short &Long Terms Gain (Practice to Understand)
- 11.0 Project Risk Analysis
- 12.0 Six Sigma Project Types
- 13.0 ProjectRoles & Responsibilities
- 13.1 Roles of Executive Leadership
- 13.2 Roles of Champion
- 13.3 Roles of Sponsor
- 13.4 Roles of Master Black Belt
- 13.5 Roles of Black Belt
- 13.6 Roles of Green Belt & Team
- 14.0 Project Managements & Analytical tools
- 14.1 Gantt charts
- 14.2 Work Breakdown Structure
- 14.3 Critical Path Method (CPM) (Simulation to Understand)
- 14.4 Project Evaluation & Review Technique
- 14.5 RACI model
- 14.6 Activity Network Diagram
- 14.7 Tree Diagram
- 14.8 Matrix Diagram
- 15.0 Project Scope
- 16.0 SIPOC & Process Mapping (Simulation to Understand)
- 17.0 Project Performance Measurement
- 17.1 Define Performance Measurement
- 17.2 Process Critical Elements
- 17.3 Key Outputs
- 18.0 Project Tool Gate Review
- 1.0 Process Analysis & Documentation
- 1.1 Process Flow Charts
- 1.2 Work Instructions &Gap Analysis
- 2.0 Types of Data & Measurement Scale (Practice to Understand)
- 2.1 Continuous (Variable) Data
- 2.2 Discrete (Attribute) Data
- 2.3 Nominal Data
- 2.4 Ordinal Data
- 2.5 Interval Measurement
- 2.6 Ratio Measurement
- 3.0 Population & Sampling
- 3.1 Basics of Sampling
- 3.2 Calculate Sample size(Practice to Understand)
- 4.0 Type of Samples(Simulation to Understand)
- 4.1 Random Sample
- 4.2 Systematic Sample
- 4.3 Stratified Sample
- 5.0 Basics of Statistics (Simulation to Understand)
- 5.1 Central Tendency
- 5.2 Dispersion
- 5.3 Proportion
- 6.0 Introduction to Statistical Software (Minitab)
- 6.1 Minitab Practice
- 6.2 Descriptive Statistics
- 6.3 Inferential Statistics
- 7.0 Probability
- 7.1 Basic Concepts
- 7.2 Independence Events
- 7.3 Mutually Exclusive Events
- 7.4 Addition & Multiplication Rules
- 7.5 Complimentary Probability
- 7.6 Occurrence of events
- 8.0 Statistical Distributions (Practice to Understand)
- 8.1 Normal
- 8.2 Binominal
- 8.3 Poisson
- 8.4 Chi-Square
- 8.5 Student’s T
- 8.6 F distribution
- 8.7 Hypergeometric
- 8.8 Bivariate
- 8.9 Exponential
- 8.10 Lognormal
- 8.11 Weibull
- 9.0 Probability of Distributions (Practice to Understand)
- 9.1 Frequency Distribution
- 9.2 Cumulative Frequency Distribution
- 9.3 Inverse Cumulative Frequency Distribution
- 10.0 Central Limit Theorem (Simulation to Understand)
- 11.0 Measurement & Data Collection
- 11.1 What is Measurement
- 11.2 Operation Definition
- 12.0 Data Collection Plan (Simulation to Understand)
- 12.1 Check Sheets
- 12.2 Data Coding
- 12.3 Data Cleaning
- 12.4 Data Collection Pitfalls
- 12.5 Avoid Data Collection Pitfalls
- 12.6 Seasonality Effect on Data
- 12.7 Data Collectors Training
- 13.0 Data Mining
- 14.0 Data Preparation
- 15.0 Graphical Analysis (Practice to Understand)
- 15.1 Pareto
- 15.2 Scatter Plot
- 15.3 Box Plot
- 15.4 Histogram
- 15.5 Stem &Leaf Plots
- 15.6 Time Series Plot
- 15.7 Run Chart
- 15.8 Normality (using Minitab)
- 15.9 Graphical Summary
- 16.0 Metrology
- 16.1 Elements of Metrology
- 16.2 Calibration System
- 16.3 Traceability &Reference Standards
- 16.4 Control & Integrity of Standards
- 17.0 Variations& Measurement System Analysis
- 17.1 Understanding Variations (Simulation to Understand)
- 17.2 Measurement System Analysis (MSA)
- 17.2.1 Discrimination
- 17.2.2 Accuracy
- 17.2.3 Precision
- 17.2.4 Stability
- 17.3 GRR for Continuous data (Simulation to Understand)
- 17.4 GRR for Discrete Data (Simulation to Understand)
- 17.5 Destructive Measurement System
- 17.6 Control Charts & Stability (Simulation to Understand)
- 17.6.1 I-Chart
- 17.6.1 I-MR Chart
- 17.6.1 X-Bar R Chart
- 17.6.1 X-Bar S Chart
- 17.6.1 C Chart
- 17.6.1 U Chart
- 17.6.1 NP Chart
- 17.6.1 P Chart
- 18.0 Sporadic problems
- 19.0 Measurement Systems to
- 19.1 Sales & Marketing
- 19.2 Engineering
- 19.3 Supply chain & Management
- 19.4 Research & Development
- 19.5 Customer Satisfaction
- 20.0 Baseline Process Performance (Practice to Understand)
- 20.1 Baseline Discrete Data (DPU, DPO,DPMO)
- 20.2 Baseline Continuous Data (Cp, Cpk, Pp, Ppk, Cpm)
- 20.3 Sigma Value (Short term & Long term)
- 20.4 Sigma Shift (Short term Vs Long term)
- 21.0 Process Capability in Detail (Practice to Understand)
- 21.1 Natural Process Limits & Specification Limits
- 21.2 Design & Conducting Process Capability Studies
- 21.3 Specifications, Sampling Plan, Stability & Normality
- 21.4 Capability for Normal & Non-Normal Data
- 21.5 Process Performance (PPM, DPU, DPMO)
- 21.6 Transformations (Box-Cox & Johnson transformation)
- 21.7 Capability for Discreet Data
- 1.0 Identify Potential Causes (Practice to Understand)
- 1.1 Brain Storming
- 1.2 Affinity Diagram
- 1.3 Cause & Effect Diagram
- 1.4 Five Whys?
- 1.5 Fault tree analysis
- 2.0 Tabular Analysis
- 3.0 Process Analysis
- 3.1 Value Stream Mapping (Recap from Lean)
- 4.0 Data Analysis
- 5.0 NormalCurve & Normality Test(Practice to Understand)
- 6.0 Outlier Analysis
- 7.0 Data Normalisation
- 8.0 Confidence Interval, Risk & P value
- 9.0 Hypothesis Testing -Null & Alternate
- 9.1 Significance of Confidence Level
- 9.2 Significance of Power
- 9.3 Statistical &Practical Significance
- 9.4 Sample Size for Hypothesis Tests
- 9.5 Point & Interval Estimates
- 9.6 Contingency Tables
- 10.0 Alpha & Beta Risks (Practice to Understand)
- 11.0 Hypothesis with Normal Data(Practice to Understand)
- 11.1 One Sample T Test
- 11.2 Two Sample T Test
- 11.3 Paired T Test
- 11.4 One-Way Anova
- 11.5 Test of Variance
- 11.5.1 One Variance Test
- 11.5.2 Two Variance Test
- 12.0 Hypothesis with Non- Normal Data(Practice to Understand)
- 12.1 1 Sample Sign
- 12.2 1 Sample Wilcoxon
- 12.3 Mann – Whitney
- 12.4 Kruskal- Wallis
- 12.5 Mood’s Median
- 13.0 Hypothesis with Discrete Data (Practice to Understand)
- 13.1 1 Proportion
- 13.2 2 Proportions
- 13.3 Chi-Square
- 14.0 Multi Vari Chart (Practice to Understand)
- 15.0 Correlation & its Terminologies (Practice to Understand)
- 16.0 Correlation &Causation (Practice to Understand)
- 17.0 Regression Analysis (Practice to Understand)
- 18.0 Linear & Non-Linear Regression (Practice to Understand)
- 19.0 Simple & Multi-Linear Regression (Practice to Understand)
- 20.0 Residual Analysis (Practice to Understand)
- 21.0 Predicting Modelling using Classification and Regression Tree
- 22.0 Logistic Regression Analysis
- 23.0 Anova
- 23.1 One Way Anova
- 23.1 Two Way Anova
- 23.1 General Linear Model
- 24.0 Chi-Square Test (Practice to Understand)
- 25.0 Multivariate Tools (Practice to Understand)
- 25.1 Factor Analysis
- 25.2 Item Analysis
- 25.3 Discriminant Analysis
- 25.4 Simple & Multiple Correspondence Analysis
- 26.0 Exploratory Data Analysis
- 27.0 Queuing theory
- 28.0 Reliability Theory
- 29.0 Qualitative analysis
- 30.0 Design of Experiments (Practice to Understand)
- 30.1 Need for DOE
- 31.0 Terminologies
- 31.1 Factors, Levels, Response, Treatment
- 31.2 Blocks, Randomisation, Effects & Replication
- 31.3 DOE Plots: Main Effect & Interaction Plots
- 31.4 Confounding
- 32.0 DOE Designs
- 32.1 Full Factorial Experiments (Practice to Understand)
- 33.0 Fractional Factorial (Practice to Understand)
- 34.0 Latin Square Designs
- 35.0 Balanced & Orthogonal Arrays
- 36.0 Taguchi’s Design
- 37.0 Confounding
- 1.0 Generate & Evaluate Ideas (Simulations to Understand)
- 1.1 Brain Storming
- 1.2 SCAMPER
- 1.3 Six Thinking Hats
- 1.4 Benchmarking
- 1.5 doHow
- 1.6 Lean Solutions
- 1.7 TRIZ (Practice to Understand)
- 2.0 Selecting Best Solution(Practice to Understand)
- 2.1 Multi-Voting
- 2.2 Pay-off Matrix
- 2.3 Criteria Matrix
- 3.0 Pugh Matrix
- 4.0 Force Field Analysis
- 5.0 Solution Prioritization matrix
- 6.0 Error Proofing
- 6.1 Prevention & Detection
- 6.2 Mistake Proofing &Examples
- 7.0 Assess Risk FMEA (Recap)
- 8.0 Piloting & Implementation
- 8.1 Pilot Solutions
- 8.2 Pilot Location
- 8.3 Pilot Success Criteria
- 9.0 Implementation
- 9.1 Plan for implementation
- 9.2 Stakeholder Analysis
- 9.3 Communication Plan
- 9.4 Implementation
- 10.0 Change Management
- 10.1 Techniques to gain commitment
- 10.2 Techniques to overcome organizational barriers
- 10.3 Necessary organizational structure for deployment
- 10.4 Communications with management
- 11.0 Organizational culture
- 1.0 What is Control or Sustain?
- 2.0 Types of Control
- 2.1 Process Control
- 2.1 Visual Controls
- 3.0 Different Types of Process controls
- 4.0 Response Plan & Reaction Plan
- 5.0 Automated Process Control
- 6.0 Statistical Process Control (Practice to Understand)
- 6.1 Monitoring, Controlling of Process Performance
- 6.2 Identify & Select Critical Process Parameters
- 6.3 Subgrouping & Rational Subgrouping
- 6.4 SPC- Continuous Data (I-MR, Xbar R, X bar S)
- 6.5 SPC – Discrete Data (C,U,P,NP charts)
- 7.0 Monitoring, Controlling of Process Performance
- 8.0 Identify & Select Critical Process Parameters
- 9.0 Subgrouping & Rational Subgrouping
- 10.0 SPC- Continuous Data (I-MR, Xbar R, X bar S)
- 11.0 SPC – Discrete Data (C, U, P, NP charts)
- 12.0 Uniformly Moving Average Chart
- 13.0 Exponentially Weighted Moving Average
- 14.0 CUSUM chart
- 15.0 Analyse Control Charts
- 16.0 Control Plan
- 17.0 Visual Control
- 18.0 Sustain Improvements
- 18.1 Lesson Learnt
- 18.2 Documentation
- 18.3 Trainings
- 18.4 Ongoing Evaluation
- 19.0 Benefit Computation
- 20.0 Project Closure
- 20.1 Lesson Learnt
- 20.2 Documentation
- 20.3 Trainings
- 20.4 Ongoing Evaluation
- 21.0 Celebration
- 1.0 Common DFSS/ DMADV Methodologies
- 1.1 Define
- 1.2 Measure
- 1.3 Analyze
- 1.4 Design
- 1.5 Validate
- 2.0 Design for X (DFX)
- 2.1 Design Constraints
- 2.2 Design Cost
- 2.3 Design for Manufacturability
- 2.4 Design for Test
- 2.5 Design for Maintainability
- 3.0 Robust Design
- 3.1 Robust Product Design
- 3.2 Tolerance for Design
- 3.3 Statistical Tolerancing
- 3.4 Robust Process Design
- 1.0 Strategies for Implementing Lean Six Sigma
- 2.0 Balance Score Card (Practice to understand)
- 3.0 Pipeline creation of new projects
- 4.0 Develop governance documents, tracking tools,
- 5.0 Project Alignment with a strategic plan
- 6.0. Project alignment with business objectives
- 7.0 Resource planning
- 8.0 Resource development (Train & Mentor)
- 9.0 Belt coaching and mentoring
- 10.0 Project reviews
- 11.0 Team facilitation and meeting management
- 12.0 non-belt coaching and mentoring
- 13.0 Execution
- 14.0 Systems thinking
- 15.0 Organizational culture
- 16.0 Development of Maturity Models
- 17.0 Organizational dynamics
- 18.0 Intervention styles
- 19.0 Interdepartmental conflicts
- 20.0. Leadership and communication
- 21.0 Business Transformation
- 22.0 Business Process Management
- 23.0 RPA Implementation
1.0 Introduction to Artificial Intelligence
1.1 Overview of AI
1.1.1 Definition and types of AI (Narrow, General, and Super AI)
1.1.2 History and Evolution of AI
1.2 Key AI Technologies
1.2.1 Machine Learning
1.2.2 Deep Learning
1.2.3 Natural Language Processing
1.2.4 Computer Vision
2.0 Integrating AI with Lean Six Sigma
2.1 AI in Project Discovery & Definition
2.2 AI in Data Collection and Measurement
2.3 AI in Data Analysis and Insights
2.4 AI in Improvement and Optimization
2.5 AI in Identifying Control Mechanism
Certification Procedure
Exemplar Global
-
Pre-requisite::
Graduate, Certified Black Belt & Complete LSS MBB training
-
Examination (Online)::
100 Questions
-
Exam time (Online)::
180 Mins
-
Pass Criteria::
1. Successfully clear the online or paper-based exam with a score of 70% or higher. 2. Complete 6 Lean Six Sigma projects. 3. Complete 100 hours of Lean Six Sigma training
-
Lean6SigmaPro Support::
End-to-end support to appear for the Exam & Certification
Our Courses
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- Instructor-Led Lean Six Sigma Yellow Belt Training & Certification | AI-Powered.
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- Instructor-Led Lean Six Sigma Black Belt Training & Certification | AI-Powered
- Six Sigma Yellow Belt
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- Lean Six Sigma Consultant Program
- PMP - Project Management Professional
- Theory Of Constraints
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- Minitab Mastery
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- Instructor-Led Lean Six Sigma Master Black Belt Training & Certification | AI-Powered
- 5S Methodology
- Eight Wastes of Lean (Service & Manufacturing)
- Eight Wastes of Lean (Manufacturing Industry)
- Value Stream Mapping (Service)
- Value Stream Mapping (Manufacturing & Service)
- Kanban and Supermarket
- Total Productive Maintenance
- Quality Function Deployment
- Process Mapping
- Cause & Effect Diagram
- Population and Sampling
- Graphical Analysis
- Hypothesis Testing
- Advanced Hypothesis Testing
- Measurement System Analysis
- Sampling Distributions
- Capability Analysis
- Design of Experiments
- Taguchi Designs
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Lean6SigmaPro: Lean Six Sigma Green Belt
Very carefully designed course to help you master the fundamentals of mighty Lean & Six Sigma and impart the skills required for you to apply the learnings at your respective workplace & able to drive Lean Six Sigma projects.
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Lean more >Lean Six Sigma Green Belt FAQs
Lean is a systematic method for waste elimination or minimization with the intent to increase process efficiency and performance gain. Waste is that for which the customer is not willing to pay.
Six Sigma is a disciplined, data-driven approach and methodology to reduce variation in processes that enhance the system's performance, and directly or indirectly translates into customer satisfaction and significant financial gain.
Lean Six Sigma uses the concepts of both Lean & Six Sigma to drive significant business results. Most projects can be executed with the Six Sigma DMAIC or DMADV methodology. It is useful to apply Lean concepts on a need basis.
A Lean Six Sigma Master Black Belt is the highest level of Six Sigma certification. MBBs lead enterprise-wide improvement strategies, mentor Lean Six Sigma Black Belts and Lean Six Sigma Green Belts, and align Six Sigma initiatives with business goals.
Typically, candidates must be certified Lean Six Sigma Black Belts with experience leading multiple high-impact projects. Strong knowledge of DMAIC, statistical analysis, leadership, and business acumen is essential for success at the Master Black Belt level.
A Lean Six Sigma Black Belt leads process improvement projects and mentors Green Belts. A Master Black Belt provides strategic direction, drives Six Sigma culture, manages enterprise-level projects, and trains Lean Six Sigma Black Belts and Green Belts.
Lean Six Sigma Master Black Belts are highly sought after for roles such as Director of Operational Excellence, Process Transformation Leader, Lean Six Sigma Consultant, or VP of Continuous Improvement across various industries.
Depending on the program and your availability, completing a Lean Six Sigma Master Black Belt training can take 3 to 6 months, including coursework, mentoring hours, and project submissions.
Yes, especially for professionals aiming for strategic leadership roles. The Lean Six Sigma Master Black Belt certification enhances your ability to drive enterprise-level improvements and significantly boosts career advancement and earning potential.
Yes, our Lean Six Sigma Master Black Belt program offers live project mentoring, real-world business cases, and support from expert trainers to ensure practical application of Lean Six Sigma methodologies.
The Lean Six Sigma Master Black Belt course covers advanced topics like Design for Six Sigma (DFSS), Multiple Regression, Advanced DOE, Predictive Analytics, AI-Driven Root Cause Analysis, and Lean Enterprise Planning.
Top certifying bodies like TÜV SÜD, Exemplar Global, ASQ, IASSC, and KPMG offer globally recognized Lean Six Sigma Master Black Belt certifications. But more than the certificate, applied knowledge, and hands-on project experience are key to success in Six Sigma.
Yes. Our Lean Six Sigma Master Black Belt online certification program includes self-paced modules, instructor-led sessions, and project mentoring—ideal for working professionals.