600 Courses

Lean Six Sigma Black Belt Certification Program: 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)

Lean Six Sigma Black Belt Certification Program 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)

Writing and Managing Requirements Documents This course is part of IIL's Business Analysis Certificate Program (BACP), a program designed to help prepare individuals pass the IIBA™ Certification exam to become a Certified Business Analysis Professional (CBAP™). Learn more at www.iil.com/bacp. Once a business analyst has completed the information gathering and analysis to produce the solution to a business problem, the results must be documented for all stakeholders to see and understand. This course will enhance the skill set needed for writing and managing the complex readership that business analysts interact with on a day-to-day basis. What you will Learn Upon completion, participants will be able to: Write an understood requirements document that is approvable and acceptable Validate a requirements document Manage the changes to requirements documents through the SDLC Foundation Concepts The role of the business analyst An introduction to the BABOK® Guide The business analyst and the product/project life cycle The requirements documentation process Planning for Effective Requirements Documentation Overview of requirements planning Planning for validation Planning for verification: well-formed criteria Planning for verification: understood and usable criteria Writing Effective Requirements Documents Overview of writing requirements documents Using a standard structure / template Applying formatting techniques Meeting the challenge of writing non-functional requirements Baselining Requirements Documents Overview of the requirements baseline process Validation Verification Approval Managing Requirements Change through the Product Life Cycle Overview of requirements change management Establishing a formal change management process Tracing requirements through design and development (build, test, and implementation) Following through to post-implementation (transition and early production)

Leading People Through Change (Free L&I Conference Course) (On-Demand) Research shows that 70% of change initiatives fail in large organizations. The largest factor contributing to this failure rate is leadership - the inability to plan and lead people through change. In many change situations, tremendous focus is put on strategy, processes, and systems, while the issue of changing people's behavior is assumed it will 'just happen'. In this interactive course, you will learn why the people's side of change is crucial. We will begin by understanding why and how people resist change, and how important it is to become strong and effective change champions. Next, we will focus on critical change management practices - creating our vision of the future state, planning for acceptance in our change audience and stakeholders, mitigating threats, and capitalizing on opportunities. We will use metrics to plan, show progress, and confirm success. Lastly, we will focus on the need to reinforce and sustain change, and to prevent relapse to old ways and methods. What you will Learn At the end of this program, you will be able to: Realize the nature of change and describe how resistance manifests in people Compare prevalent change models and categorize their similarities Identify and rate the skills, traits, and behaviors of effective change champions Envision the future state and assess stakeholders Plan for change communication, training, and risks Evaluate change effectiveness using feedback and metrics Develop reinforcement practices for benefits and communication Foundation Concepts What is Change? Resistance to Change Common Change Management Theories Becoming a Change Champion Plan Envisioning the future state Planning for people Change management plan Do Change communication Training Piloting Risks Study Feedback Metrics Variance analysis Act Benefits realization Change sustainment Reinforcement messaging and communications

Leading People through Change: On-Demand: On-Demand Research shows that 70% of change initiatives fail in large organizations. The largest factor contributing to this failure rate is leadership - the inability to plan and lead people through change. In many change situations, tremendous focus is put on strategy, processes, and systems, while the issue of changing people's behavior is assumed it will 'just happen'. In this interactive course, you will learn why the people side of change is crucial. We will begin by understanding why and how people resist change, and how important it is to become strong and effective change champions. Next, we will focus on critical change management practices - creating our vision of the future state, planning for acceptance in our change audience and stakeholders, mitigating threats, and capitalizing on opportunities. We will use metrics to plan, show progress, and confirm success. Lastly, we will focus on the need to reinforce and sustain change, and to prevent relapse to old ways and methods. What you will Learn At the end of this program, you will be able to: Realize the nature of change and describe how resistance manifests in people Compare prevalent change models and categorize their similarities Identify and rate the skills, traits, and behaviors of effective change champions Envision the future state and assess stakeholders Plan for change communication, training, and risks Evaluate change effectiveness using feedback and metrics Develop reinforcement practices for benefits and communication Foundation Concepts What is Change? Resistance to Change Common Change Management Theories Becoming a Change Champion Plan Envisioning the future state Planning for people Change management plan Do Change communication Training Piloting Risks Study Feedback Metrics Variance analysis Act Benefits realization Change sustainment Reinforcement messaging and communications

Writing and Managing Requirements Documents: In-House Training This course is part of IIL's Business Analysis Certificate Program (BACP), a program designed to help prepare individuals pass the IIBA™ Certification exam to become a Certified Business Analysis Professional (CBAP™). Learn more at www.iil.com/bacp. Once a business analyst has completed the information gathering and analysis to produce the solution to a business problem, the results must be documented for all stakeholders to see and understand. This course will enhance the skill set needed for writing and managing the complex readership that business analysts interact with on a day-to-day basis. What you will Learn Upon completion, participants will be able to: Write an understood requirements document that is approvable and acceptable Validate a requirements document Manage the changes to requirements documents through the SDLC Foundation Concepts The role of the business analyst An introduction to the BABOK® Guide The business analyst and the product/project life cycle The requirements documentation process Planning for Effective Requirements Documentation Overview of requirements planning Planning for validation Planning for verification: well-formed criteria Planning for verification: understood and usable criteria Writing Effective Requirements Documents Overview of writing requirements documents Using a standard structure / template Applying formatting techniques Meeting the challenge of writing non-functional requirements Baselining Requirements Documents Overview of the requirements baseline process Validation Verification Approval Managing Requirements Change through the Product Life Cycle Overview of requirements change management Establishing a formal change management process Tracing requirements through design and development (build, test, and implementation) Following through to post-implementation (transition and early production)

Leading People Through Change (Free L&I Conference Course): On-Demand The goal of this course is for you to effectively lead and manage people through times of change. Research shows that 70% of change initiatives fail in large organizations. The largest factor contributing to this failure rate is leadership - the inability to plan and lead people through change. In many change situations, tremendous focus is put on strategy, processes, and systems, while the issue of changing people's behavior is assumed it will 'just happen'. In this interactive course, you will learn why the people's side of change is crucial. We will begin by understanding why and how people resist change, and how important it is to become strong and effective change champions. Next, we will focus on critical change management practices - creating our vision of the future state, planning for acceptance in our change audience and stakeholders, mitigating threats, and capitalizing on opportunities. We will use metrics to plan, show progress, and confirm success. Lastly, we will focus on the need to reinforce and sustain change, and to prevent relapse to old ways and methods. What You Will Learn At the end of this program, you will be able to: Realize the nature of change and describe how resistance manifests in people Compare prevalent change models and categorize their similarities Identify and rate the skills, traits, and behaviors of effective change champions Envision the future state and assess stakeholders Plan for change communication, training, and risks Evaluate change effectiveness using feedback and metrics Develop reinforcement practices for benefits and communication Foundation Concepts What is Change? Resistance to Change Common Change Management Theories Becoming a Change Champion Plan Envisioning the future state Planning for people Change management plan Do Change communication Training Piloting Risks Study Feedback Metrics Variance analysis Act Benefits realization Change sustainment Reinforcement messaging and communications

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)

Writing and Managing Requirements Documents: Virtual In-House Training This course is part of IIL's Business Analysis Certificate Program (BACP), a program designed to help prepare individuals pass the IIBA™ Certification exam to become a Certified Business Analysis Professional (CBAP™). Learn more at www.iil.com/bacp. Once a business analyst has completed the information gathering and analysis to produce the solution to a business problem, the results must be documented for all stakeholders to see and understand. This course will enhance the skill set needed for writing and managing the complex readership that business analysts interact with on a day-to-day basis. What you will Learn Upon completion, participants will be able to: Write an understood requirements document that is approvable and acceptable Validate a requirements document Manage the changes to requirements documents through the SDLC Foundation Concepts The role of the business analyst An introduction to the BABOK® Guide The business analyst and the product/project life cycle The requirements documentation process Planning for Effective Requirements Documentation Overview of requirements planning Planning for validation Planning for verification: well-formed criteria Planning for verification: understood and usable criteria Writing Effective Requirements Documents Overview of writing requirements documents Using a standard structure / template Applying formatting techniques Meeting the challenge of writing non-functional requirements Baselining Requirements Documents Overview of the requirements baseline process Validation Verification Approval Managing Requirements Change through the Product Life Cycle Overview of requirements change management Establishing a formal change management process Tracing requirements through design and development (build, test, and implementation) Following through to post-implementation (transition and early production)

Managers at all levels have to be able to introduce, lead and manage change to ensure the organisational objectives of change are met.