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Lean Six Sigma Black Belt Certification Program: Virtual In-House Training This course is specifically for people wanting to become Lean Six Sigma Black Belts, who are already Lean Six Sigma practitioners. If advanced statistical analysis is needed to identify root causes and optimal process improvements, (Lean) Six Sigma Green Belts typically ask Black Belts or Master Black Belts to conduct these analyses. This course will change that. Green Belts wanting to advance their statistical abilities will have a considerable amount of hands-on practice in techniques such as Statistical Process Control, MSA, Hypothesis Testing, Correlation and Regression, Design of Experiments, and many others. Participants will also work throughout the course on a real-world improvement project from their own business environment. This provides participants with hands-on learning and provides the organization with an immediate ROI once the project is completed. IIL instructors will provide free project coaching throughout the course. What you Will Learn At the end of this program, you will be able to: Use Minitab for advanced data analysis Develop appropriate sampling strategies Analyze differences between samples using Hypothesis Tests Apply Statistical Process Control to differentiate common cause and special cause variation Explain and apply various process capability metrics Conduct Measurement System Analysis and Gage R&R studies for both discrete and continuous data Conduct and analyze simple and multiple regression analysis Plan, execute, and analyze designed experiments Drive sustainable change efforts through leadership, change management, and stakeholder management Successfully incorporate advanced analysis techniques while moving projects through the DMAIC steps Explain the main concepts of Design for Six Sigma including QFD Introduction: DMAIC Review IIL Black Belt Certification Requirements Review Project Selection Review Define Review Measure Review Analyze Review Improve Review Control Introduction: Minitab Tool Introduction to Minitab Minitab basic statistics and graphs Special features Overview of Minitab menus Introduction: Sampling The Central Limit Theorem Confidence Interval of the mean Sample size for continuous data (mean) Confidence Interval for proportions Sample size for discrete data (proportions) Sampling strategies (review) Appendix: CI and sample size for confidence levels other than 95% Hypothesis Testing: Introduction Why use advanced stat tools? What are hypothesis tests? The seven steps of hypothesis tests P value errors and hypothesis tests Hypothesis Testing: Tests for Averages 1 factor ANOVA and ANOM Main Effect Plots, Interaction Plots, and Multi-Vari Charts 2 factor ANOVA and ANOM Hypothesis Testing: Tests for Standard Deviations Testing for equal variance Testing for normality Choosing the right hypothesis test Hypothesis Testing: Chi Square and Other Hypothesis Test Chi-square test for 1 factor ANOM test for 1 factor Chi-square test for 2 factors Exercise hypothesis tests - shipping Non-parametric tests Analysis: Advanced Control Charts Review of Common Cause and Special Cause Variation Review of the Individuals Control Charts How to calculate Control Limits Four additional tests for Special Causes Control Limits after Process Change Discrete Data Control Charts Control Charts for Discrete Proportion Data Control Charts for Discrete Count Data Control Charts for High Volume Processes with Continuous Data Analysis: Non-Normal Data Test for normal distribution Box-Cox Transformation Box-Cox Transformation for Individuals Control Charts Analysis: Time Series Analysis Introduction to Time Series Analysis Decomposition Smoothing: Moving Average Smoothing: EWMA Analysis: Process Capability Process capability Discrete Data: Defect metrics Discrete Data: Yield metrics Process Capability for Continuous Data: Sigma Value Short- and long-term capabilities Cp, Cpk, Pp, Ppk capability indices Analysis: Measurement System Analysis What is Measurement System Analysis? What defines a good measurement system? Gage R&R Studies Attribute / Discrete Gage R&R Continuous Gage R&R Regression Analysis: Simple Correlation Correlation Coefficient Simple linear regression Checking the fit of the Regression Model Leverage and influence analysis Correlation and regression pitfalls Regression Analysis: Multiple Regression Analysis Introduction to Multiple Regression Multicollinearity Multiple Regression vs. Simple Linear Regression Regression Analysis: Multiple Regression Analysis with Discrete Xs Introduction Creating indicator variables Method 1: Going straight to the intercepts Method 2: Testing for differences in intercepts Logistic Regression: Logistic Regression Introduction to Logistic Regression Logistic Regression - Adding a Discrete X Design of Experiments: Introduction Design of Experiment OFAT experimentation Full factorial design Fractional factorial design DOE road map, hints, and suggestions Design of Experiments: Full Factorial Designs Creating 2k Full Factorial designs in Minitab Randomization Replicates and repetitions Analysis of results: Factorial plots Analysis of results: Factorial design Analysis of results: Fits and Residuals Analysis of results: Response Optimizer Analysis of results: Review Design of Experiments: Pragmatic Approaches Designs with no replication Fractional factorial designs Screening Design of Experiment Case Study Repair Time Blocking Closing: Organizational Change Management Organizational change management Assuring project sponsorship Emphasizing shared need for change Mobilizing stakeholder commitment Closing: Project Management for Lean Six Sigma Introduction to project management Project management for Lean Six Sigma The project baseline plan Work Breakdown Structure (WBS) Resource planning Project budget Project risk Project schedule Project executing Project monitoring and controlling and Closing Closing: Design for Lean Six Sigma Introduction to Design for Lean Six Sigma (DMADV) Introduction to Quality Function Deployment (QFD) Summary and Next Steps IIL's Lean Six Sigma Black Belt Certification Program also prepares you to pass the IASSC Certified Black Belt Exam (optional)

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DASA DevOps Professional: Enable and Scale: Virtual In-House Training DevOps embodies both cultural changes and practices through which organizations can facilitate the IT functions of software development (Dev) and software operation (Ops). The DevOps movement advocates automation and phase-based monitoring practices. Its objectives include: Decreasing development cycles · Increasing deployment frequency Improving the reliability of releases Developing a closer alignment with business objectives The DASA DevOps Professional: Enable and Scale course (formerly known as DevOps Practitioner) is designed to provide individuals with the core education necessary to put DevOps into practice. With the help of DevOps theory, pragmatic examples and exercises, and interactive group discussions, the course will help you understand how to apply the necessary skills to practice DevOps. Building on the knowledge learned on theFundamentals course (the 'why'), you will learn the 'how'. The DevOps Professional: Enable and Scale course focuses on improving the skill set of the DASA competency model, which includes competencies like Courage, Teambuilding, DevOps Leadership, and Continuous Improvement. On completion of the DASA DevOps Professional: Enable and Scale training and passing the exam, the certification is awarded. What you will Learn At the end of this program, you will be able to: Explain the importance of DevOps culture and the aspects that can influence it Explain why courage, teambuilding, leadership, and continuous improvement are required in a DevOps environment Explain why courage is essential to enable trust, honesty, and experimentation Identify and evaluate different types of behavior in a DevOps environment Recognize the signals indicating impediments and/or team dysfunctions Describe how to form good DevOps teams and assess their maturity List the effects of happiness and motivation on team performance Identify how leaders encourage feedback and transparency Discuss the factors that leaders can influence to build trust Explain how and why leaders promote a 'safe to fail' environment Analyze value streams to improve throughput and flow Facilitate the tools for continuous improvement: structured problem-solving workshops, Story Mapping sessions, and retrospectives TEAMBUILDING Teambuilding is about understanding the other's point of view, collaboration, mutual accountability, common purpose, and the ability to integrally support the service/product. Design Teams Characteristics of a DevOps team Skills of a DevOps Team Self-organization and autonomy Rules to consider when designing DevOps teams Build Teams Effects of happiness and motivation on performance Feedback Creating high-performance teams Governance Governance within teams and between multiple teams Governance between organizations DevOps contracts DEVOPS LEADERSHIP This module describes how to facilitate teams to high performance, DevOps behavior, transparency, and a service lifecycle mindset. Build Culture Creating the right environment and providing vision and purpose Stimulating the right behavior Servant leadership: giving control, supporting, and inspiring Create Purpose Defining and aligning purpose Purpose of having a purpose Alignment versus autonomy Be a Servant Leader Give control to the team Inspire and support the team Focus on Success Output versus outcome Measuring and steering COURAGE The Courage module is about coaching courageous behavior, proactivity, reflection, trust, open discussions, experimentation, fail fast, and the courage to change. Build Courage The importance of courage Courage in relationship with leadership and feedback Enabling courage at the team level Dealing with failure Think Different Courage day to day Encourage critical thinking Techniques to promote courageous behavior VALUE CUSTOMER-CENTRIC ACTION This module describes the important aspects that are relevant to identify and deliver the required and expected value for all relevant stakeholders. Aspects of Value and Managing Expectations The different aspects of value Stakeholder management Customer collaboration and using customer feedback How to do prioritization CONTINUOUS IMPROVEMENT Continuous improvement describes the importance of a Kaizen mindset, quality at the source, first time right, knowledge-sharing, and the ability to adapt. Build Flow Understanding the importance of flow Using Lean to optimize flow Kaizen as a mindset Radical change versus Kaizen Using Pull to optimize flow Continuous Improvement Tools Kaizen Event Value Stream Mapping Visual Management Retrospective Daily Standup Five Times Why

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