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AI Powered Lean Six Sigma Black Belt Online Certification & Training

AI Powered Lean Six Sigma Black Belt (Online)

November

32 Hours E-Learning + 16 hours Instructor Led Online Training + 16 Hours Project Mentoring


November 17 - January 05
E-Learning at your comfort
14:00 - 18:00 IST
Project Mentoring
(Sunday Only)


Project Mentoring Dates
Nov
Sun
17
 
Sun
24
Dec
Sun
01
 
Sun
08
 
Sun
15
 
Sun
22
 
Sun
29
Jan
Sun
05
E-Learning + Project Mentoring

₹19,800

E-Learning + Project Mentoring + Certification

₹28,800

January

32 Hours E-Learning + 16 hours Instructor Led Online Training + 16 Hours Project Mentoring


January 05 - February 23
E-Learning at your comfort
14:00 - 18:00 IST
Project Mentoring
(Sunday Only)


Project Mentoring Dates
Jan
Sun
05
 
Sun
12
 
Sun
19
 
Sun
26
Feb
Sun
02
 
Sun
09
 
Sun
16
 
Sun
23
E-Learning + Project Mentoring

₹19,800

E-Learning + Project Mentoring + Certification

₹28,800

6 Reasons to choose Lean6SigmaPro

Help you make the optimal use of AI in LSS projects
Project - enabled learning & practice with indusrty data
Post - certification support, career guidance & assistance
Learn from the best consultants & LinkedIn top voices
Internationally recognized Certificates: TUV SUD or Exemplar Global
100% Certification guaranteed + Project Certificate


AI Powered Lean Six Sigma Black Belt

AI Powered Lean Six Sigma Black Belt

A Lean Six Sigma Black Belt is a highly skilled leader in Lean Six Sigma. They act as a catalyst for change and improvement, guiding and mentoring Green Belts and aspiring Black Belts in project execution. They also oversee more complex Six Sigma projects involving multiple functions.  


This Lean Six Sigma Black Belt course, powered by AI, will provide you with the necessary skills for this important role. By the end of the course, you will be capable of leading high-impact projects to successful conclusions. The use of AI will significantly enhance your ability to execute complex Lean Six Sigma projects and mentor Green Belts and Black Belts with ease. 


The AI-powered Lean Six Sigma Black Belt program offers 

  • 32+ Hours of high-Quality E-learning
  • 16+ Hours of project Mentoring
  • 16+ Hours of Instructor Led Online Training
  • 50+ Minitab Practice Exercise  


Gain a thorough understanding of Lean Six Sigma concepts and develop the statistical expertise required for successful project execution and mentoring with our exceptional 32+ hours of High-Quality E-learning program. For more challenging concepts, complement your learning with our interactive 16+ hours of Instructor-led online training sessions. This flexible structure allows you to balance your commitments while mastering the material and maximizing the use of AI tools.                                                                                                                                                                                                                         

Duration
64 Hours: 32 Hours of E-Learning + 16 Hours of Instructor Led Online Training + 16 Hours of Project Mentoring
Certification
We help you with internationally recognized certification from TÜV SÜD or Exemplar Global. However, the course design enables you to pass any certification exam like the ASQ, IASSC, KPMG, ISI with ease.
Objective

Our objective is to empower participants with the knowledge, methodology, and skills required to drive and mentor DMAIC Lean Six Sigma Black Belt projects in their respective industries.

Who Should Attend?
  • Professionals with over four years of experience
  • Any professional seeking to accelerate his/her corporate career
  • Anyone who wants to consider Lean Six Sigma as a career option
  • Certified Black Belts seeking to upgrade their practical skills
  • Professionals seeking Lean Six Sigma knowledge rather than just certification
Project Assistance
We provide you with free assistance from an expert from your field.
Essentials
Certified Green Belts with a minimum of 1 year as Green Belt, or professionals with over four years of industry experience.
Trainers Profile

    Srinivas TV - Click to view full profile

  • Certified Master Black Belt & a passionate trainer
  • Over 20 years in the field of Lean Six Sigma
  • Executed/Mentored over 300 Lean Six Sigma projects with $30+ Saving.
  • Trained over 10,000 professionals across industries.
  • Corporate Lean Six Sigma trainer for Fortune 50 Companies
Course Fee Includes
  • 64 hours of project-enabled experiential learning
  • Lifetime access to the student portal of the Lean6SigmaPro Page
  • Minitab Training & over 80 hours of extensive practice
  • Industry-specific Lean Six Sigma case studies
  • Sample question papers with solutions
  • Support in executing projects for two years
  • Refresher training at no charges
  • Exclusive invite to attend Black Belt project presentations
  • Mentorship & assistance to accelerate your corporate career
  • Pay just the differential amount when you take up Lean Six Sigma Master Black Belt training in the future
  • 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
  • 7.0 Create Value Stream Mapping (VSM)
  •    7.1 Terminologies (CT, FTY, RTY, CO, TPT, WIP, WIQ)
  •    7.2 Process Efficiency
  •    7.3 Customer Takt time
  •    7.4 Create VSM
  •    7.5 Process Efficiency
  • 8.0 Create Value Stream Design (VSD)
  • 9.0 Create Flow & Respond to Pull
  •    9.1 Single Piece Flow
  •    9.2 Single Minute of Exchange of Dies
  •    9.3 Line Balancing
  •    9.4 Kanban (Pull Production)
  •    9.5 Heijunka (Production Levelling)
  •    9.6 Just In Time
  • 10.0 Additional Lean Tools
  • 1.0 Introduction to Quality
  • 2.0 Quality Leaders (Juran, Deming, Shewhart, Ishikawa)
  • 3.0 Cost of Quality (COQ)
  • 4.0 Cost of Poor Quality (COPQ)
  • 5.0 Optimum Quality Levels
  • 6.0 Kano Model (Practice to Understand)
  • 7.0 Key Performance Measures
  •    7.1 Key Performance Indicators
  •    7.2 Customer Satisfaction
  •    7.3 Product Differentiation
  •    7.4 Leading & Lagging Indicators
  •    7.5 Create a 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 Strategic Planning & Deployment
  •    16.1 SWOT Analysis (Practice to Understand)
  •    16.2 PEST
  •    16.3 Business Contingency Planning
  • 17.0 ProjectTeam Dynamics (Simulation to Understand)
  •    17.1 Forming
  •    17.2 Storming
  •    17.3 Norming
  •    17.4 Performing
  • 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 Customer Requirements to Process Requirements
  •    2.1 Critical to X (X-Quality, Cost, Safety or any other )
  •    2.2 CTQ Drill Down
  •    2.3 Quality Function Deployment (Practice to Understand)
  • 3.0 Project Section & Prioritisation (Practice to Understand)
  • 4.0 Process Owners & Stakeholder Analysis
  • 5.0 Project Charter (Practice to Understand)
  •    5.1 Business Case
  •    5.2 Problem Statement
  •    5.3 Project Goal Statement
  •    5.4 Project Team
  •    5.5 Project Timeline
  •    5.6 Project Scope
  •    5.7 Expected Benefits
  • 6.0 Financial Evaluation & Business Case
  • 7.0 Develop Project Metrics
  • 8.0 SIPOC & Process Mapping (Simulation to Understand)
  • 9.0 Project Tool Gate Review
  • 1.0 Types of Data & Measurement Scale (Practice to Understand)
  •    1.1 Continuous (Variable) Data
  •    1.2 Discrete (Attribute) Data
  •    1.3 Nominal Data
  •    1.4 Ordinal Data
  •    1.5 Interval Measurement
  •    1.6 Ratio Measurement
  • 2.0 Population & Sampling
  •    2.1 Basics of Sampling
  •    2.2 Calculate Sample size(Practice to Understand)
  • 3.0 Type of Samples
  •    3.1 Random Sample
  •    3.2 Systematic Sample
  •    3.3 Stratified Sample
  • 4.0 Basics of Statistics
  •    4.1 Central Tendency
  •    4.2 Dispersion
  •    4.3 Proportion
  • 5.0 Introduction to Statistical Software (Minitab)
  •    5.1 Minitab Practice
  •    5.2 Descriptive Statistics
  •    5.3 Inferential Statistics
  • 6.0 Statistical Distributions (Practice to Understand)
  •    6.1 Normal
  •    6.2 Binominal
  •    6.3 Poisson
  •    6.4 Chi-Square
  •    6.5 Student’s T
  •    6.6 F distribution
  •    6.7 Hypergeometric
  •    6.8 Bivariate
  •    6.9 Exponential
  •    6.10 Lognormal
  •    6.11 Weibull
  • 7.0 Probability of Distributions (Practice to Understand)
  •    7.1 Frequency Distribution
  •    7.2 Cumulative Frequency Distribution
  •    7.3 Inverse Cumulative Frequency Distribution
  • 8.0 Central Limit Theorem (Simulation to Understand)
  • 9.0 Measurement & Data Collection
  •    9.1 What is Measurement
  •    9.2 Operation Definition
  • 10.0 Variations& Measurement System Analysis
  •    10.1 Understanding Variations (Simulation to Understand)
  •    10.2 Measurement System Analysis (MSA)
  •       10.2.1 Discrimination
  •       10.2.2 Accuracy
  •       10.2.3 Precision
  •       10.2.4 Stability
  •    10.3 GRR for Continuous Data (Simulation to Understand)
  •    10.4 Kappa Analysis
  • 11.0 Control Charts & Stability (Simulation to Understand)
  • 12.0 Baseline Process Performance (Practice to Understand)
  •    12.1 Baseline Discrete Data (DPU, DPO, DPMO)
  •    12.2 Baseline Continuous Data (Cp, Cpk, Pp, Ppk, Cpm)
  •    12.3 Sigma Value (Short term & Long term)
  •    12.4 Sigma Shift (Short term Vs. Long term)
  • 13.0 Process Capability in Detail (Practice to Understand)
  •    13.1 Natural Process Limits & Specification Limits
  •    13.2 Design & Conducting Process Capability Studies
  •    13.3 Specifications, Sampling Plan, Stability & Normality
  •    13.4 Capability for Normal & Non-Normal Data
  •    13.5 Process Performance (PPM, DPU, DPMO)
  •    13.6 Transformations (Box-Cox & Johnson transformation)
  • 1.0 Identify Potential Causes (Practice to Understand)
  •    1.1 Brain Storming
  •    1.2 Affinity Diagram
  •    1.3 Cause & Effect Diagram
  •    1.4 Five Why Analysis
  • 2.0 Process Analysis
  •    2.1 Value Stream Mapping (Recap from Lean)
  • 3.0 Data Analysis
  • 4.0 Graphical Analysis (Practice to Understand)
  •    4.1 Pareto
  •    4.2 Scatter Plot
  •    4.3 Box Plot
  •    4.4 Histogram
  •    4.5 Time Series Plot
  •    4.6 Run Chart
  •    4.7 Normality (using Minitab)
  •    4.8 Graphical Summary
  • 5.0 NormalCurve & Normality Test(Practice to Understand)
  • 6.0 Confidence Interval, Risk & P value
  • 7.0 Hypothesis Testing -Null & Alternate
  •    7.1 Significance of Confidence Level
  •    7.2 Significance of Power
  •    7.3 Statistical &Practical Significance
  •    7.4 Sample Size for Hypothesis Tests
  •    7.5 Point & Interval Estimates
  •    7.6 Contingency Tables
  • 8.0 Alpha & Beta Risks (Practice to Understand)
  • 9.0 Hypothesis with Normal Data(Practice to Understand)
  •       9.1 1 Sample T
  •       9.2 2-Sample T
  •       9.3 Paired T
  •       9.4 One-Way Anova
  •       9.5 Test of Variance
  • 10.0 Hypothesis with Non-Normal Data(Practice to Understand)
  •       10.1 1 Sample Sign
  •       10.2 1 Sample Wilcoxon
  •       10.3 Mann – Whitney
  •       10.4 Kruskal- Wallis
  •       10.5 Mood’s Median
  • 11.0 Hypothesis with Discrete Data (Practice to Understand)
  •    11.1 1 Proportion
  •    11.2 2 Proportions
  •    11.3 Chi-Square
  • 12.0 Multi Vari Chart (Practice to Understand)
  • 13.0 Correlation & its Terminologies (Practice to Understand)
  • 14.0 Correlation &Causation (Practice to Understand)
  • 15.0 Regression Analysis (Practice to Understand)
  • 16.0 Linear & Non-Linear Regression (Practice to Understand)
  • 17.0 Simple & Multi-Linear Regression (Practice to Understand)
  • 18.0 Residual Analysis (Practice to Understand)
  • 19.0 Design of Experiments (Practice to Understand)
  •    19.1 Need for DOE
  •    19.2 DOE Terminologies
  • 20.0 DOE Designs
  •    20.1 Full Factorial Experiments (Practice to Understand)
  •    20.2 Fractional Factorial (Practice to Understand)
  •    20.3 Balanced & Orthogonal Arrays
  •    20.4 Taguchi’s Design

  • 1.0 Generate & Evaluate Ideas (Simulations to Understand)
  •    1.1 Brain Storming
  •    1.2 SCAMPER
  •    1.3 Benchmarking
  •    1.4 Lean Solutions
  •    1.5 TRIZ (Introduction)
  • 2.0 Selecting Best Solution(Practice to Understand)
  •    2.1 Multi-Voting
  •    2.2 Pay-off Matrix
  •    2.3 Force Field Analysis
  • 3.0 Error Proofing
  •    3.1 Prevention & Detection
  •    3.2 Mistake Proofing &Examples
  • 4.0 Assess Risk FMEA
  • 5.0 Piloting & Implementation
  • 6.0 Implementation
  • 1.0 What is Process Control?
  • 2.0 Different Types of Process Controls
  • 3.0 Response Plan & Reaction Plan
  • 4.0 Statistical Process Control (Practice to Understand)
  •    4.1 Monitoring, Controlling of Process Performance
  •    4.2 Identify & Select Critical Process Parameters
  •    4.3 Subgrouping & Rational Subgrouping
  •    4.4 SPC- Continuous Data (I-MR, Xbar R, X bar S)
  •    4.5 SPC – Discrete Data (C, U, P, NP charts)
  • 5.0 Analyse Control Charts
  • 6.0 Control Plan
  • 7.0 Project Closure
  • 8.0 Celebration
  • 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  
Course Program Comparision
Lean6SigmaPro
Tuv Sud
IASSC
ASQ
Exemplar Global
KPMG
Introduction to Lean
What is Lean & Application of Lean
5S Before Lean(Simulation to Understand)
Types of Waste–(Videos &Simulation to Understand)
Different Types of Wastes
Causes of Waste
Remedies of Waste

Certification Procedure

Exemplar Global

  • Mandatory Training Hours:
    72 Hours of LSSBB Training

  • Project:
    1 Black Belt project

  • Pass Criteria:
    - Successfully pass online/Paper & Pen based exam with 60% - Successfully pass project/viva evaluation with 60% - Combined exam + project/viva evaluation 70%

  • Lean6SigmaPro Support:
    End to End support to appear for exam, project certification

  • Additional Fee:
    NA

TÜV & SÜD

  • Mandatory Training Hours:
    72 Hours of LSSBB Training

  • Project:
    1 Black Belt project

  • Pass Criteria:
    - Successfully pass online/Paper & Pen based exam with 70% - Successfully pass project evaluation with 70%

  • Lean6SigmaPro Support:
    End to End support to appear for exam, project & Certification

  • Additional Fee:
    NA

ASQ

  • Mandatory Training Hours:
    Attend online/classroom training

  • Project:
    1 Black Belt project

  • Pass Criteria:
    Successfully pass online/Paper & Pen based exam

  • Lean6SigmaPro Support:
    End to End support to appear for exam

  • Additional Fee:
    As per ASQ exam fee (Approx. Rs.37000)

IASSC

  • Mandatory Training Hours:
    Attend online/classroom training

  • Project:
    NA

  • Pass Criteria:
    Successfully pass online/Paper & Pen based exam with 70%

  • Lean6SigmaPro Support:
    End to End support to appear for exam

  • Additional Fee:
    As per IASSC exam fee (Approx. Rs.28000)

Certification Criteria

Exemplar Global

  • Pre-requisite:
    Green Belt Certified + LSSBB Training Completion

  • Examination (Computer):
    100 questions

  • Exam time (Computer):
    3 hours

  • Examination (Paper & Pencil):
    100 questions

  • Exam time (Paper & Pencil):
    3 hours

  • Recertification:
    NA

TÜV & SÜD

  • Pre-requisite:
    Green Belt Certified + LSSBB Training Completion

  • Examination (Computer):
    100 questions

  • Exam time (Computer):
    3 hours

  • Examination (Paper & Pencil):
    100 questions

  • Exam time (Paper & Pencil):
    3 hours

  • Recertification:
    NA

IASSC

  • Pre-requisite:
    NA

  • Examination (Computer):
    150 questions (achieve min. 70%)

  • Exam time (Computer):
    4 hours

  • Examination (Paper & Pencil):
    150 questions (achieve min. 70%)

  • Exam time (Paper & Pencil):
    4 hours

  • Recertification:
    Every 3 years

ASQ

  • Pre-requisite:
    3 years (full time paid role) in one or more areas of the green belt body of knowledge + one completed projects with signed affidavits (or) two completed projects with signed affidavits

  • Examination (Computer):
    165 questions (150 (scored) + 15 (unscored))

  • Exam time (Computer):
    4hr 30 min

  • Examination (Paper & Pencil):
    150 questions

  • Exam time (Paper & Pencil):
    4 hours

  • Recertification:
    Every 3 years

Please contact us via below from for more info

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