292 Courses in London

This fashion design 2-DAY course for beginners and intermediates is a group class aimed to support aspiring designers or designers in need of guidance in the realisation of a viable and realistic collection of bags and/or accessories.This course enables you to understand essential skills required to become a fashion bag designer ans well as guiding you through the steps necessary for designing, developing, prototyping and manufacturing your collection.   WHY THIS IS NOT THE USUAL ‘ACCESSORY DESIGN’ COURSEThis course is designed by a team of designers, prototype makers and handbag manufacturers.It is both a theoretical and practical course which will teach you what the industry requires from designers in order to be able to understand and correctly translate their ideas into finished products.This course is focused on giving you an overview on the complexity and extensiveness of the process that designing a collection of handbags requires.The course will assist you in understanding the prerequisites before and during the design of your styles. This knowledge will enable you to circumvent a lengthy, costly, and occasionally frustrating process when it comes time to prototype and manufacture your collection.   WHY WE CREATED A FASHION DESIGN COURSEAfter years of experience in designing and developing collections for our customers, we realised that there was a substantial lack of clear information available about what designing a collection of handbags and fashion accessories truly requires and how it is achieved.We created this course with the aim of helping the new generation of designers, as well as designers which are still struggling, in developing their ideas and empower them to clearly and correctly communicate them to whoever is going to prototype their collection.We essentially have created this tuition based on the needs and problems of our customers, hoping to promote and facilitate creatives in the realisation of their projects.   WHO IS THIS COURSE FOR?This course is designed for aspiring designers and professionals seeking expert advice from the industry. It caters to those in need of guidance to optimise their design process or understand the nuances of working as a fashion accessory designer.No previous experience is required.   WHAT WILL BE TAUGHT?The designing classes cover various topics, including: - Preliminary considerations before designingUnderstanding the concept and use of a moodboard - Overview of researching crucial aspects like target audience, market placement, pricing strategy, etc - Overview on leather and hardware and their impact on costImportance of construction and finishing optionsAnatomy of a handbag, including lining and reinforcements - Understanding how to structure a collection with a collection planPlanning a balanced collection of fashion accessories - Differences and purposes of illustrations vs technical drawingsSketching techniques, including drawing in perspective and technical drawings - Product development for a specific design - Understanding what technical information the prototype maker requires - Overview of the prototyping processOverview of manufacturing options and processes for your collection HOW WILL THE ABOVE BE TAUGHT:The class will take place in person at our London studio and the lesson will alternate between theoretical lessons and practical exercises.   INCLUDED IN THE COURSE:You will also receive access to a collection of handouts providing relevant information, useful resources and support in continuing your designing process independently.The handouts will contain: – A glossary containing essential key words related to the topic of the lesson – An illustrated glossary containing information about type of bags and bags’ features – An illustrated guide on common hardware used in bags and accessories – Documents about leather types, finishings, tanning processes – Information about perspective and guides to be used as reference to develop your drawings – A list of recommended suppliers for both leather and fittings (physically in London and online) – A glossary containing information about leather types and characteristics WHAT ARE THE ENTRY REQUIREMENTS? You should be able to use measurements and understand verbal and written English instructions.   ARE THERE ANY OTHER COSTS? IS THERE ANYTHING I NEED TO BRING?Materials to exercise with are included.Feel free to bring a notepad, if you would like to take some notes, we will provide the rest. HOW LONG IS THIS TUITION?:This tuition will require up to 14 hours to complete.We aim to provide customised and high-quality tuition services and by only allowing max 6 students at a time, we are able to focus on each person needs and interests. As every student has a different level of ability and previous experience, this course might lead some students to complete the core aspects of the lesson in a shorter time frame than others. Students who complete the course early will be welcome to stay and use the studio facilities to exercise on the topics of the lesson.

Business Process Modeling 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 A process model is a description of a process in terms of its steps or actions, the data flowing between them and participants in the process, machines, systems, and organizations involved. Modeling is a critical business analysis skill. It applies graphical and text communication techniques to describe the actions, objects, and relationships acted upon in the process and the steps that act upon them. This course teaches the technique of process modeling and ties together the core methods of process, behavior, and data modeling to enable business analysts to fully describe business processes in levels of detail from multiple perspectives. What you will Learn Upon completion, participants will be able to: Identify business processes and their components Work with UML diagrams Use process modeling in business diagramming Diagram and model business processes Foundation Concepts The role of the business analyst The IIBA® BABOK® Knowledge Areas Business Process Modeling (BPM) and the business analyst A practical approach to business process modeling The Context for Modeling Business Processes Overview of context for business process modeling Analyzing stakeholder information Modeling best practices Critical inputs for BPM: Business Rules Critical inputs for BPM: Context Diagrams Data Models Overview of data modeling Entity relationship diagrams Object-oriented approach Class diagrams Other data models Process Models - Part I (Non-UML) Overview of process modeling Data flow diagrams Workflow diagrams Flowcharts Process Models - Part II (UML) Overview of UML Process Models UML Activity Diagrams UML Sequence Diagrams Usage Models - Part I (Non-UML) Overview of usage modeling Prototyping options Static prototyping and storyboards Dynamic prototyping User Interface Design and user stories Usage Models - Part II (UML Use Cases) Overview of Use Cases Use Case diagrams Use Case descriptions Use Cases and the product life cycle Integrating the Models Overview of integrating the models General analysis best practices Specific analysis techniques summary Best practices for transition to design Summary and Next Steps What did we learn and how can we implement this in our work environments?

Business Process Modeling: 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 A process model is a description of a process in terms of its steps or actions, the data flowing between them and participants in the process, machines, systems, and organizations involved. Modeling is a critical business analysis skill. It applies graphical and text communication techniques to describe the actions, objects, and relationships acted upon in the process and the steps that act upon them. This course teaches the technique of process modeling and ties together the core methods of process, behavior, and data modeling to enable business analysts to fully describe business processes in levels of detail from multiple perspectives. What you will Learn Upon completion, participants will be able to: Identify business processes and their components Work with UML diagrams Use process modeling in business diagramming Diagram and model business processes Foundation Concepts The role of the business analyst The IIBA® BABOK® Knowledge Areas Business Process Modeling (BPM) and the business analyst A practical approach to business process modeling The Context for Modeling Business Processes Overview of context for business process modeling Analyzing stakeholder information Modeling best practices Critical inputs for BPM: Business Rules Critical inputs for BPM: Context Diagrams Data Models Overview of data modeling Entity relationship diagrams Object-oriented approach Class diagrams Other data models Process Models - Part I (Non-UML) Overview of process modeling Data flow diagrams Workflow diagrams Flowcharts Process Models - Part II (UML) Overview of UML Process Models UML Activity Diagrams UML Sequence Diagrams Usage Models - Part I (Non-UML) Overview of usage modeling Prototyping options Static prototyping and storyboards Dynamic prototyping User Interface Design and user stories Usage Models - Part II (UML Use Cases) Overview of Use Cases Use Case diagrams Use Case descriptions Use Cases and the product life cycle Integrating the Models Overview of integrating the models General analysis best practices Specific analysis techniques summary Best practices for transition to design Summary and Next Steps What did we learn and how can we implement this in our work environments?

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)

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)

Salsa or Latin Dance rhythm private class in London for couples or individuals to achieve a good knowledge of the Salsa, Samba, Bachata, Merengue or Latin dance steps One to One lesson, 5 minimum pack lesson booking. Taught by native instructor You can have this lesson at our premises, on Zoom, Pre-recorded or home visit, the choice is yours!!! The Program includes: 10 or 20 Lesson 1on1 lesson Walking & Leading techniques Female & Male Teachers Footwork & Upper body techniques Steps & routines names (brain method) Body posture and language Tempo & beat music technique Fully equipped dance studio Ownership of your footage work progress & Docs Music library via dropbox or Spotify Salsa or Latin Dance rhythm private class in London for couples or individuals to achieve a good knowledge of the salsa, samba, bachata, merengue or Latin dance steps One to One lesson, 4 minimum pack lesson book Teach by the native instructor We have been training people in salsa in London for almost 20 years and are still in business as salsa in west London is increasing massively.  SALE

This two day programme is designed to support participants to work through the technical steps and stages as well as the more practical realities of project management.

Introduction to Design Thinking: In-House Training Innovation is the cornerstone of highly successful companies, especially those that continue to be successful over the years and decades. Design thinking practices fuel this continual innovation, as they are the critical links from inspiration to delivery, concept to showroom floor, and start-up to global business. Design thinking is a structured approach to promoting innovation and creative problem-solving. It is not a new approach. It has been around for centuries, as the art, architecture, and inventions of mankind illustrate. By examining the steps to achieving great design and maximum utility of product, design thinking approaches provide a framework in which to develop new solutions to problems and new products to sell. This highly interactive course is designed to help participants think like designers to generate innovation, and to help teams to produce more innovation and creativity. Since design thinking is based on doing rather than thinking, we participants are challenged to apply the techniques, in the classroom, to create new ideas and solutions to a case study project. What you will Learn At the end of this program, you will be able to: Explain the underlying principles and value of using Design Thinking for innovation Describe the basic concepts of the Stanford Model for Design Thinking Evaluate a set of basic Design Thinking techniques for application to your projects Apply tools, techniques, and skills aligned with the 5 stages of the Stanford Model Drive innovation through Design Thinking at some level in your work environment Foundation Concepts Problems and solutions The Design Thinking difference Design Thinking skills and abilities Design Thinking mindset Design Thinking frameworks Stages of Design Thinking Problems and solutions The Design Thinking difference Design Thinking skills and abilities Design Thinking mindset Design Thinking frameworks General Practices Team formation Visualization Improvisation Personalization Empathize Practices Overview of Empathize techniques Observation Engagement Interviews Define Practices Overview of Define practices Unpacking techniques Defining the customer techniques Integrating the Define experience Ideate Practices Overview of Ideate practices Reusable techniques for the Ideate stage New Ideate techniques to explore Prototype & Test Practices Overview of Prototype practices Examples of prototypes Overview of Testing practices Forms of testing techniques Adopt and Adapt Design Thinking Overview of Design Thinking implementation Design Thinking implementation challenges Success in implementing Design Thinking Summary and Next Steps Workshop summary Next steps: Personal Action Plans

Introduction to Design Thinking Innovation is the cornerstone of highly successful companies, especially those that continue to be successful over the years and decades. Design thinking practices fuel this continual innovation, as they are the critical links from inspiration to delivery, concept to showroom floor, and start-up to global business. Design thinking is a structured approach to promoting innovation and creative problem-solving. It is not a new approach. It has been around for centuries, as the art, architecture, and inventions of mankind illustrate. By examining the steps to achieving great design and maximum utility of product, design thinking approaches provide a framework in which to develop new solutions to problems and new products to sell. This highly interactive course is designed to help participants think like designers to generate innovation, and to help teams to produce more innovation and creativity. Since design thinking is based on doing rather than thinking, we participants are challenged to apply the techniques, in the classroom, to create new ideas and solutions to a case study project. What you will Learn At the end of this program, you will be able to: Explain the underlying principles and value of using Design Thinking for innovation Describe the basic concepts of the Stanford Model for Design Thinking Evaluate a set of basic Design Thinking techniques for application to your projects Apply tools, techniques, and skills aligned with the 5 stages of the Stanford Model Drive innovation through Design Thinking at some level in your work environment Foundation Concepts Problems and solutions The Design Thinking difference Design Thinking skills and abilities Design Thinking mindset Design Thinking frameworks Stages of Design Thinking Problems and solutions The Design Thinking difference Design Thinking skills and abilities Design Thinking mindset Design Thinking frameworks General Practices Team formation Visualization Improvisation Personalization Empathize Practices Overview of Empathize techniques Observation Engagement Interviews Define Practices Overview of Define practices Unpacking techniques Defining the customer techniques Integrating the Define experience Ideate Practices Overview of Ideate practices Reusable techniques for the Ideate stage New Ideate techniques to explore Prototype & Test Practices Overview of Prototype practices Examples of prototypes Overview of Testing practices Forms of testing techniques Adopt and Adapt Design Thinking Overview of Design Thinking implementation Design Thinking implementation challenges Success in implementing Design Thinking Summary and Next Steps Workshop summary Next steps: Personal Action Plans

Lean Six Sigma Green Belt Certification Program This learning series is designed to enable participants to fulfill the important role of a Lean Six Sigma Green Belt and to incorporate the Lean Six Sigma mindset into their leadership skills. Green Belt is not just a role, it is also a competency required for leadership positions at many top companies. This learning series is designed to enable participants to fulfill the important role of a Lean Six Sigma Green Belt and to incorporate the Lean Six Sigma mindset into their leadership skills. With a real-world project focus, the series will teach the fundamental methodology, tools, and techniques of the Define, Measure, Analyze, Improve and Control Process Improvement Methodology. This course is delivered through sixteen 3-hour online sessions. What you Will Learn At the end of this program, you will be able to: Identify strategies for effectively leading high performing process improvement teams Analyze whether projects align with business strategy Apply process improvement methodologies to DMAIC steps, based on real world scenarios Explain ways to appropriately respond to process variation Distinguish among best practice problem solving methodologies Evaluate and effectively communicate data-driven decisions, based on real world scenarios Introduction Lean Six Sigma & quality The vision The methodologies The metric Project Selection Why Projects Random idea generation Targeted idea generation CTQs (Critical to Quality) & projects Project screening criteria Quick improvements Introduction to Define Project Planning Developing the core charter Developing a project charter Facilitation Process Management Business process management Top-down process mapping Voice of the Customer Voice of Customer Stakeholder analysis Communication planning Kicking off the project Define Summary Introduction to Measure Data Collection Fact-based decision making Data sampling Operations definitions Data collection plan Measurement system analysis Graphical Statistics for Continuous Data Meet Six SigmaXL Graphical & statistical tools Data stratification Graphical Statistics for Discrete Data Pareto analysis Dot plots Plotting data over time: Looking for patterns Variation Concepts Variation is reality Special Cause and Common Cause variation Example of standard business reporting Individuals Control Chart Process Capability Genesis of process capability Calculating the metrics of Six Sigma Yield metrics: Measuring process efficiency Cost of Poor Quality The Cost of Poor Quality (COPQ) Cost of Quality categories Calculating the Cost of Poor Quality Measure Summary Introduction to Analyze Process Analysis Introduction to process analysis Value-added analysis Cycle time analysis WIP & pull systems Analyzing bottlenecks and constraints Cause & Effect Analysis Fishbone/Ishikawa diagram 5-Whys analysis Graphical & statistical tools Advanced Analysis Why use hypothesis rests? Hypothesis tests Correlation and regression analysis Analyze Summary Introduction to Improve Solutions Creativity techniques Generating alternative solutions Solution selection techniques Introduction to Design of Experiments Introduction to DOE DOE activity Error Proofing Failure mode & effect analysis Poka-Yoke Project Management Fundamentals Successful teams Project roles Conflict management Standardization Standardization The Visual Workplace 5S Piloting & Verifying Results What is a pilot? Evaluating results Improve Summary Introduction to Control Statistical Process Control Review of Special & Common Cause variation Review of Individual Control Chart P-Chart for discrete proportion data Transition Planning Control plan Project closure Control Summary Summary and Next Steps