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This accredited course gives you an introduction to mental health and wellbeing - what it is, how to take care of yourself and support others

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)

High Performing Teams. Moccasin Approach, Moccasin Manager,

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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.

MySQL Performance & Tuning training course description This MySQL Performance & Tuning course is designed for Database Administrators, Application Developers and Technical Consultants who need to monitor and tune the performance of MySQL servers and databases. The course provides practical experience in monitoring and tuning MySQL servers and databases. Note: This MySQL Performance & Tuning course does not cover clustering (other than at overview level), replication or non-standard storage engines such as Falcon and PBXT. What will you learn Develop a monitoring and tuning plan Use server configuration and status variables. Identify and improve problem queries. Make efficient use of indexes. Monitor and size memory caches and locks. Tune the MyISAM and InnoDB storage engine. Evaluate the use of partitioning for performance. MySQL Performance & Tuning training course details Who will benefit: Anyone who wishes to monitor and tune MySQL performance. Prerequisites: Delegates must have a working knowledge of MySQL Database Administration Duration 3 days MySQL Performance & Tuning training course contents Introduction to performance tuning Tuning overview, Resolving performance issues, Recommended approach to tuning, Items to evaluate, Where to look, Planning a monitoring routine, Building a new database for performance, Tuning an existing database, Setting suitable goals. MySQL performance tuning tools Administration tools, the information schema, performance-related SHOW commands, benchmarking tools, the MySQL performance schema, MonYog. Hands on Obtaining performance information. Schema design Normalisation, de-normalisation, naming conventions, load generation, stress testing and benchmarking tools, selecting data types, data types, character sets, choosing storage engines. Hands on effects of design on performance. Statement tuning Overview of statement tuning, identifying problem queries, the optimizer, explain, explain extended. Hands on identifying problem queries and using explain. Indexes Index overview, Types of index, Index tuning, Indexes and joins. Hands on Indexes and performance. Server configuration and monitoring Server configuration variables, server status variables, table cache, multi-threading, connection issues, query cache. Hands on setting and interpreting server variables and caching. Locking Types of locking, locking and storage engines, effects of locking on performance. Hands on locking and performance. The InnoDB engine Transactions, crash recovery, locking, monitoring InnoDB, caches and buffers, configuring data files, configuring the log files. Hands on InnoDB configuration and performance. Other storage engines MyISAM engine, merge engine, archive engine, memory engine, blackhole engine, CSV engine, the Spider engine, the ColumnStore engine, the MyRocks engine, mixing sorage engines. Hands on storage engine performance. Overview of clustering and performance Advantages of performance, advantages of clustering, performance issues and clustering, the NDBCluster engine, the Galera cluster, the Percona XtraDB cluster, MySQL InnoDB cluster, the federated engine, the federatedX engine, overview of other high availability techniques. NOSQL and Mencached overview. Dumping and loading data SQL statements versus delimited data, parameters affecting dump performance, parameters affecting load performance. Hands on dump and load performance. Partitioned tables Partitioned tables concepts, range partitioning, hash partitioning, key partitioning, list partitioning, composite partitioning or subpartitioning, partition pruning. Hands on partitioned table performance.

The Alarm Installation Course is designed to teach participants how to install an intruder alarm system in domestic, commercial or industrial premises. The Alarm Installation Course simulates the practical installation of many different alarm control panels. The course is designed to equip students with the skills and expertise to competently install a wide variety of Alarm systems on the market.

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