2525 Courses in Reading

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)

OOAD training course description A workshop course providing thorough practical knowledge of object oriented analysis and design methods. What will you learn Perform Systems Analysis with Object Oriented methods. Identify key classes and objects. Expand and refine OO problem domain models. Design Class hierarchies using inheritance and polymorphism. Design programs with Object Oriented methods. OOAD training course details Who will benefit: System analysts, designers, programmers and project managers. Prerequisites: It is desirable that delegates have experience of programming in C++/Java or some other OOP language. Duration 5 days OOAD training course contents What is OO? Classes, objects, messages, encapsulation, associations, inheritance, polymorphism, reusability. What is Systems Analysis and design? Data flow diagrams, structure diagrams. The OO approach. OOA The problem domain and object modelling. Identifying classes and objects. Generalisation and inheritance. Defining attributes and methods. OOD Refining the OOA results. Designing the User Interface. Designing the algorithms and data structures using objects. Designing the methods. OOP Prototyping. Implementing OOD with OOPs and OOPLs.

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Trauma Risk Management is an evidence based, peer delivered risk assessment and ongoing support system, designed specifically to help in the management of traumatic events.

Join a Climate Fresk Climate science workshop to learn about the causes and effects of climate change through a fun and collaborative experience.

Join a Biodiversity collage workshop to learn about the biodiversity crisis and how to tackle it.

Overview Performance management is a continuous process which involves making sure the performance of your employees contributes to organisational and team goals. Having effective employment management in place helps everyone in the organisation to know what the business is trying to achieve, the skill and competencies they need to fulfil their role and how they can develop their performance to develop the organisation.

Overview The protocol is one of the most modern terms in terms of language but very old in terms of history as the word protocol is a development of the word of the conventions and understandings this is in the world of politics and at the international level, but within the field of business management has become the formulation of protocols is one of the important and necessary skills and very necessary for people who wish to They must take administrative duties. Through this course, we are going to introduce the rules and practices of gentle behaviour, the best practices for communication with others, and good reception, since all such related matters represent a large portion of our personality.

Overview Objective Describing the HR role and Strategies Describe different approaches to employee training Describe different approaches to professional development Describe different approaches to performance appraisals Summarize different forms of employee compensation

Overview The course begins by introducing credit risk, its components and its drivers. The course then dives into business risk assessment and group structure risks. After examining financial statements, including accounting concepts and principles, the course concludes with a review of financial analysis and its four main risk areas.