34554 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)

A Psychology-led day retreat for parents and carers of children with learning disabilities and/or Autism in the beautiful Wye Valley. 9th October 2024 at Forest Retreats, Tintern, Monmouthshire, Wales.

Location: Grantham Price: £79 (Course Cost Includes Refreshments & Lunch!) Mastering Compliance and Safety on the Road This essential 7 hours course is designed to equip professional drivers with the knowledge and skills necessary to comply with complex driving regulations and ensure safe loading practices. Key areas covered include: Drivers’ Hours and Working Time Regulations: Gain a comprehensive understanding of driving and rest periods, breaks, and exemptions to avoid penalties and ensure driver well-being. Tachograph Regulations: Learn how to correctly use and interpret analog and digital tachographs to accurately record driving activities and comply with legal requirements. Safe Loading of Vehicles: Acquire essential knowledge and practical skills for securing loads effectively,preventing accidents, and complying with road safety regulations. By the end of this course, you will have a strong foundation in regulatory compliance and safe driving practices, helping you to protect your license, your employer, and other road users. Invest in your professional development and become a safer, more compliant driver. Please review our Terms and Conditions for more information.

Are you passionate about the business side of film? Do you have an entrepreneurial mindset and ambitions to pave a career in a fast-growing creative industry? The BA (Hons) Film Business & Production degree reflects current demands for professionally ready graduates equipped with the vital creative, business and entrepreneurial skills to navigate the modern film, screen and media environment.

Overview The effective management of finances is a fundamental function for any organisation but particularly so in the public sector. Governments, under the scrutiny of the citizens they represent, are increasingly under pressure to improve public services whilst at the same time identifying ways to cut spending and increase efficiency. This programme recognises these difficulties and ensures that participants leave the programme with a full understanding of effective financial management in the public sector - including budgeting systems, auditing, preparing financial statements and tracking expenditure. 

Overview For internal employees who want to understand and expand their roles related to financial reporting, as well as those who simply need a refresher on financial accounting, this course is the ideal way to get up to speed. By exploring concepts that go beyond basic accounting, this course will enable participants to approach financial auditing with renewed confidence. The programme will walk participants through an analysis of an organization's financial statements using case study exercises, where participants will calculate key ratios and analyze trends over time. Engaging in discussions on both historic and current fraud cases, participants will learn how to recognize “red flags” in financial statement reporting.

🌟 Unlock the Power of Information Management with 'Information Overload - Surplus of Data, Deficit of Time' Course! 🌟   Are you drowning in a sea of information but struggling to stay afloat with limited time? The digital age has blessed us with an abundance of data, yet mastering how to harness this information efficiently remains a challenge. ⏳ Time is your most valuable asset, and this course is your key to mastering the art of managing information overload!     🚀 Our comprehensive course offers: Strategies for Efficient Information Processing: Learn techniques to sift through the surplus of data swiftly and extract the most relevant insights without getting overwhelmed. Productivity Hacks for Time Optimization: Discover time-saving methods and tools to streamline your workflow, allowing you to make the most of your precious time. Effective Organization and Prioritization Techniques: Gain insights into organizing information effectively and prioritizing tasks to maximize productivity without sacrificing quality. Mindfulness and Stress Management in Information Handling: Understand how to maintain a healthy balance and reduce stress while navigating through the data deluge. Practical Exercises and Real-Life Scenarios: Apply learned strategies through hands-on exercises and real-world scenarios to solidify your understanding and implementation.   🎓 Taught by industry experts with years of experience in information management, this course equips you with the skills needed to conquer information overload, empowering you to thrive in today's data-driven world. 🌐 Join a community of like-minded individuals and embark on a journey to master the art of handling information overload effectively! Course Curriculum Module- 1 00:00 Module- 2 00:00 Module- 3 00:00 Module- 4 00:00 Module- 5 00:00 Module- 6 00:00 Module- 7 00:00 Module- 8 00:00 Module- 9 00:00 Module- 10 00:00

Overview This Leadership and Management course is essential reading for anyone wanting to improve their skills and reach their potential as a team leader or manager. The course is fully interactive and prompts you to assess your own leadership or management style and then learn how to develop it further. The course covers key topics such as effective communication, the importance of managing your time well, how to build solid relationships with your team, mental fitness and taking care of your own well-being, and how to better solve workplace problems.

Overview We encounter lots of incidents every day at home or at work in which we need to think deeply about our decisions. Making the right choice not only saves time but also saves money and makes everyone happy. In this course, participants will learn how to refine their intuitions in order to make them trustable. Critical thinking and analysis will be a practice and habit for them and they will find themselves subconsciously using them. They will learn how to make sensible conclusions out of the data they managed to gather.