Last updated 3/2021
MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz
Language: English | Size: 1.77 GB | Duration: 15h 30m
A Comprehensive Certified Six Sigma Black Belt Training & Sure Shot Way to Become a Master of Six Sigma
What you’ll learn
Prepare for Lean Six Sigma Black Belt Certifications (CSSBB , LSSBB)
Perform advanced data analysis using Minitab with 75+ datasets
Downloadable material for future reference in each section covering Body of knowledge of accreditation bodies
140 Quiz Questions as a mock to evaluate your Six Sigma knowledge
Requirements
Green Belt Certification & Green Belt Level working knowledge
The participant should have sufficient exposure to his/her domain or industry, It is advisable to have a minimum of 5-8 years of industry work experience
Description
As per Indeed, a job site’s survey, Certified Six Sigma Black Belt salaries range between $100,000 – $200,000. Lean Six Sigma Black Belts command a premium in Job market. CSSBB & LSSBB deliver business results, so there are 75% more likely to be promoted that one without, but with similar domain experience.This Lean Six Sigma Black Belt Training will help you succeed in accredited certification exam or process to become a certified Lean Six Sigma Black Belt because the BoK is based on Global Certification Bodies such as IASC and AQ curriculums. Instructor is an Accredited Training Associate.Every topic is application based. It starts with a business scenario and Six Sigma concepts are introduced subsequently. There are 75+ Data Files & Practices Files for you to download. You can follow the step-by-step instructions as you see in the lecture and mirror the instructor. It is a great way to master advanced statistical and analytics tools covered in Lean Six Sigma Black Belt body of knowledgeOver TemplatesOver 40 Minitab Instruction Videos on advanced Six Sigma Black Belt Level topics are included in this Online Black Belt CourseStudent Testimonials:"I passed six sigma black belt certification exam. Black belt course and practice tests played pivotal role for cracking the test in one go. Thanks Nil !" – Sandeep J."This training material assisted me in the preparation of ASQ CSSBB exam. There are a lot of real-world examples included. Great Work! "- Temesgen E."Very thorough, will absolutely help a serious professional reach "create" level of proficiency – "Mastery" – Matthew M."The training was full of knowledge on whole plethora of Six Sigma application. The lessons were very informative in very simple languages. I recommend all to pursue this course under Udemy. Special Thanks to mentor Mr. Nilakantasrinivasan Janakiraman Sir". – Mofidur R.CERTIFIED LEAN SIX SIGMA BLACK BELT Body of knowledge covered in this course are
Black Belt leadership Expectations from a Black Belt role in market Leadership Qualities Organizational Roadblocks & Change Management Techniques Mentoring Skills Basic Six Sigma Metrics CTQ Tree, Big Y , CTX Including DPU, DPMO, FTY, RTY, Cycle Time, Takt time Sigma scores with XL, Z tables, Minitab Target setting techniques Role of Benchmarking Business Process Management System BPMS and its elements Benefits of practicing BPMS (Process centricity and silos) BPMS Application scenarios BSC Vs Six Sigma MSA Performing Variable GRR using ANOVA/X-bar R method Precision, P/T , P/TV, Cont %, No. of Distinct Categories Crossed & Nested Designs Procedure to conduct Continuous MSA Performing Discrete GRR using agreement methods for binary and ordinal data Agreement & Disagreement Scores for part, operator, standard Kappa Scores Computation for ordinal data and criteria for acceptance of gage Statistical Techniques Probability Curve, Cumulative Probability, Inverse Cumulative Probability (Example and procedure), Shape, Scale and Location parameters Types of Distributions ( Normal, Weibull, Exponential, Binomial, Poisson) & their interpretation and application Identifying distributions from data Central Limit Theorem – Origin, Standard Error, Relevance to Sampling Example & Application of Central Limit Theorem Sampling Distributions Degrees of Freedom t-distribution – Origin, relevance, pre-requisites, t-statistic computation Chi-square distribution – Origin, relevance, pre-requisites, Chi-square statistic computation, Approximation to discrete data F-distribution – Origin, relevance, pre-requisites, F-Statistic and areas of applications Point & Interval estimates – Confidence and Predictive estimates for Sampling distributions Application of Confidence Estimates in decision making Sampling of Estimates Continuous and Discrete Sample Size Computation for sampling of estimates Impact of Margin of Error, standard deviation, confidence levels, proportion defective and population on sample size Sample Size correction for finite population Scenarios to optimize Sample Size such as destructive tests, time constraints Advanced Graphical Methods Depicting 1 or 2 variables (with example and procedure) Dot Plot Box Plot Interval Plot Stem-and-Leaf Plot Time Series & Run Chart Scatter Plot Marginal Plot Line Plots Depicting 3 variables (with example and procedure) Contour Plot 3D scatter Plot 3D Surface Plot Depicting > 3 Variables (with example and procedure) Matrix Plot Multi Vary Chart Inferential Statistics Advanced Introduction to Hypothesis Tests Significance and implications of 1 tail and 2 tail Types of Risks – Alpha and Beta Risks Significance & computation of test statistic, critical statistic, p-value Sample Size for Hypothesis Tests Sample Size computation for hypothesis tests Power Curve Scenarios to optimize Sample Size, Alpha, Beta, Delta such as destructive tests Hypothesis Tests 1Z, 1t, 2t, Parried t Test – Pre-requisites, Components & interpretations One and Two Sample Proportion Chi-square Distribution Ch-square Test for Significance & Good of Fit – Components & interpretations ANOVA & GLM ANOVA – Pre-requisites, Components & interpretations Between and Within Variation, SS, MS, F statistic 2-way ANOVA – Pre-requisites, Interpretation of results Balanced, unbalanced and Mixed factors models GLM – Introduction, Pre-requisites, Components & Interpretations Correlation & Regression Linear Correlation – Theory and computation of r value Non-linear Correlation – Spearman’s Rho application and relevance Partial Correlation – Computing the impact of two independent variables Regression – Multi-linear Components & interpretations Confidence and Prediction Bands, Residual Analysis, Building Prediction Models Regression – Logistic(Logit) & Prediction – Components & interpretations with example Dealing with Non-normal data Identifying Non-normal data Box Cox & Johnson Transformation Process Capability Process Capability for Normal data Within Process Capability, Sub-grouping of data Decision Tree for Type of Process Capability Study Process Capability of Non-normal data – Weibull, Binomial, Poisson Process Capability and interpretation of results Non Parametric Tests Mann-Whitney Kruskal-Wallis Mood’s Median Sample Sign Sample Wilcoxon Experimental Design DOE terms, (independent and dependent variables, factors, and levels, response, treatment, error, etc.) Design principles (power and sample size, balance, repetition, replication, order, efficiency, randomization, blocking, interaction, confounding, resolution, etc.) Planning Experiments (Plan, organize and evaluate experiments by determining the objective, selecting factors, responses and measurement methods, choosing the appropriate design, One-factor experiments (Design and conduct completely randomized, randomized block and Latin square designs and evaluate their results) Two-level fractional factorial experiments (Design, analyze and interpret these types of experiments and describe how confounding affects their use) Full factorial experiments (Design, conduct and analyze full factorial experiments) Advanced Control Charts X-S chart CumSum Chart EWMA Chart _________________________________________________________________________________________________________________________________________Note: We are not a representative of ASQ®, IASSC® ASQ® is the registered trademark of the American Society for Quality.IASSC® is the registered trademark of the International Association for Six Sigma Certification.We are an independent training provider. We are neither currently associated nor affiliated with the above mentioned. The name and title of the certification exam mentioned in this course are the trademarks of the respective certification organization. The Fair Use of these terms are for describing the relevant exam and the body of knowledge associated.
Overview
Section 1: Introduction
Lecture 1 Welcome
Lecture 2 Canopus BB course structure & curriculum & BB Certification Process I
Lecture 3 Softwares Needed
Section 2: BB Leadership
Lecture 4 Black Belt – Market expectations
Lecture 5 Black Belt Project – Do’s & Don’ts
Lecture 6 Downloadable Takeaways
Section 3: Six Sigma Metrics
Lecture 7 Six Sigma Metrics Intro
Lecture 8 Six Sigma Metrics II
Lecture 9 Rolled Throughput Yield
Lecture 10 Baseline
Lecture 11 Target Setting
Lecture 12 Downloadable Takeaways
Section 4: VoC
Lecture 13 VoC Intro
Lecture 14 Gemba I
Lecture 15 Gemba II
Lecture 16 Gemba III
Lecture 17 Prioritizing Customer Needs using Kano Model (Recap Lesson)
Lecture 18 Conducting Kano Survey
Lecture 19 Downloadable Takeaways
Section 5: Business Process Management System
Lecture 20 BPMS Intro
Lecture 21 Organizational Silos
Lecture 22 Business Processes
Lecture 23 Big Y
Lecture 24 Types of Inputs
Lecture 25 Operational Definition
Lecture 26 CTQ Tree
Lecture 27 Business Process Management System
Lecture 28 Downloadable Takeaways
Section 6: Measurement System Analysis
Lecture 29 MSA Overview
Lecture 30 Elements of Measurement System
Lecture 31 Discrete Gage R&R
Lecture 32 Performing MSA Kappa Study
Lecture 33 MSA ANOVA
Lecture 34 Understanding MSA ANOVA Terms
Lecture 35 Performing MSA ANOVA 1
Lecture 36 Performing MSA ANOVA 2
Lecture 37 MSA Practice Files
Lecture 38 Downloadable Takeaways
Section 7: Statistical Techniques – Advanced
Lecture 39 Probability Distribution Refresher
Lecture 40 Standard Normal Variable
Lecture 41 Application of Probabilities
Lecture 42 Types of Distributions
Lecture 43 Distribution Parameters
Lecture 44 Process Lead Time Data
Lecture 45 Weibull Distribution
Lecture 46 Identifying Distributions
Lecture 47 Application of Weibull Distributions
Lecture 48 Exponential Distribution
Lecture 49 Binomial Distribution
Lecture 50 Binomial Application
Lecture 51 Poisson Distribution
Lecture 52 Poisson Distribution Application
Lecture 53 Normal Approximations
Lecture 54 Central Limit Theorem
Lecture 55 Application of Central Limit Theorem
Lecture 56 Statistical Techniques Practice Files
Lecture 57 Downloadable Takeaways
Section 8: Sampling Distribution
Lecture 58 Confidence intervals
Lecture 59 Confidence interval for means
Lecture 60 Degrees of freedom
Lecture 61 t-Distribution
Lecture 62 CI for t-Distribution
Lecture 63 Proportion of CI
Lecture 64 Chi-Square distribution
Lecture 65 F- Distribution
Lecture 66 Sampling Distribution Practice Files
Lecture 67 Downloadable Takeaways
Section 9: Estimate Sampling
Lecture 68 Estimate Sampling
Lecture 69 Rational Sub-Grouping
Lecture 70 Sample Size Computation Part 1
Lecture 71 Sample size computation for estimates for discrete data
Lecture 72 Sample Size Computation Part 2
Lecture 73 Sample size computation for estimates for Continuous data
Lecture 74 Sample size for finite population
Lecture 75 Estimate Sampling Practice Files
Lecture 76 Downloadable Takeaways
Section 10: Advanced Graphical Methods
Lecture 77 Graphical Methods Intro
Lecture 78 Dot Plots, Box Plots & Interval Plots
Lecture 79 Run Charts
Lecture 80 Time Series Plots
Lecture 81 Theory of R
Lecture 82 Non-linear correlation
Lecture 83 Marginal Plots
Lecture 84 3D Plots
Lecture 85 Multi Vary Charts
Lecture 86 Advanced Graphical Methods Practice Files
Lecture 87 Downloadable Takeaways
Section 11: Hypothesis Sampling
Lecture 88 Risks in hypothesis testing
Lecture 89 Sampling of hypothesis testing
Lecture 90 Hypothesis Sampling Practice Files
Lecture 91 Downloadable Takeaway
Section 12: Hypothesis Testing
Lecture 92 Hypothesis Testing
Lecture 93 Hypothesis testing in t-tests I
Lecture 94 Hypothesis testing in t-tests II
Lecture 95 Hypothesis testing in t-tests III
Lecture 96 ANOVA Fundamentals I
Lecture 97 ANOVA Fundamentals II
Lecture 98 Performing ANOVA I
Lecture 99 Performing ANOVA II
Lecture 100 Performing ANOVA III
Lecture 101 Type of Chi-square test
Lecture 102 Hypothesis testing using Chi-square tests
Lecture 103 Performing Chi-square tests I
Lecture 104 Performing Chi-square tests II
Lecture 105 Hypo Testing Proportion Test I
Lecture 106 Hypo Testing Proportion Test II
Lecture 107 Hypothesis Testing Practice Files
Lecture 108 Downloadable Takeaways
Section 13: Non Parametric Testing
Lecture 109 Non Parametric Intro
Lecture 110 One Sign & Wilcoxon Test
Lecture 111 Mann Whitney & Moods Median
Lecture 112 Non Parametric Testing Practice Files
Lecture 113 Downloadable Takeaways
Section 14: Correlation & Regression
Lecture 114 Line of Best Fit
Lecture 115 Regression in Minitab
Lecture 116 Fits & Residuals
Lecture 117 Partial Correlation
Lecture 118 Importance of Rsq
Lecture 119 Confidence Band and Prediction Band
Lecture 120 Multiple Linear Regression
Lecture 121 Multi-collinearity
Lecture 122 Best Subsets
Lecture 123 Logistic Regression Intro
Lecture 124 Performing Logistic Regression
Lecture 125 Predicting using Models
Lecture 126 Correlation & Regression Practice Files
Lecture 127 Downloadable Takeaways
Section 15: Design of Experiments
Lecture 128 Introduction to Experiments
Lecture 129 Phases of Experiments
Lecture 130 Basic DOE Terms
Lecture 131 Performing Full Factorial Experiment in Minitab
Lecture 132 Analyzing Full Factorial Results in Minitab – Part 1
Lecture 133 Analyzing Full Factorial Results in Minitab – Part 2
Lecture 134 Advanced DOE Terms
Lecture 135 Performing Fractional Factorial Experiments – Part 1
Lecture 136 Performing Fractional Factorial Experiments – Part II
Lecture 137 Analyzing Fractional Factorial Results in Minitab
Lecture 138 DOE Practice Files
Lecture 139 Downloadable Takeaway
Section 16: Process Capability
Lecture 140 Process Capability Intro
Lecture 141 Process Capability Decision Tree
Lecture 142 Performing Process Capability Analysis in Minitab I
Lecture 143 Performing Process Capability Analysis in Minitab II
Lecture 144 Performing Process Capability Analysis in Minitab III
Lecture 145 Interpreting Process Capability Analysis Results I
Lecture 146 Interpreting Process Capability Analysis Results II
Lecture 147 Data Transformation I
Lecture 148 Data Transformation II
Lecture 149 Data Transformation III
Lecture 150 Weibull Process Capability
Lecture 151 Binomial Process Capability
Lecture 152 Process Capability Practice Files
Lecture 153 Downloadable Takeaways
Section 17: Change Management
Lecture 154 Change Management & its importance
Lecture 155 Barriers to Change
Lecture 156 Accelerating Change
Lecture 157 Managing Change in BB Project
Lecture 158 Accountability for Improvement
Lecture 159 Change Management Strategies
Lecture 160 Downloadable Takeaways
Section 18: Statistical Process Control – Advanced
Lecture 161 Pre-Control Charts I
Lecture 162 Pre-Control Charts II
Lecture 163 Advanced Control Charts I
Lecture 164 Advanced Control Charts II
Lecture 165 Downloadable Takeaways
Lecture 166 Bonus Lecture: List of our other courses
Certified or Trained Six Sigma Green Belts
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