142 Influence courses in Loughton

If you have no intention of removing asbestos but work on buildings built or refurbished before the year 2000, asbestos could be present. You will need awareness training so you know how to avoid the risks. Asbestos awareness training should be given to employees whose work could foreseeably disturb the fabric of a building and expose them to asbestos or who supervise or influence the work. In particular, it should be given to those workers in the refurbishment, maintenance and allied trades where it is foreseeable that ACMs may become exposed during their work.

Enhance patient care with our "Understanding Physiological Observations" course. Gain comprehensive knowledge and skills to accurately assess and interpret vital signs and other measurements.

If you have no intention of removing asbestos but work on buildings built or refurbished before the year 2000, asbestos could be present. You will need awareness training so you know how to avoid the risks. Asbestos awareness training should be given to employees whose work could foreseeably disturb the fabric of a building and expose them to asbestos or who supervise or influence the work. In particular, it should be given to those workers in the refurbishment, maintenance and allied trades where it is foreseeable that ACMs may become exposed during their work.

This highly practical workshop will help you become a more effective negotiator and learn the skills that master negotiators use.

About this Training Course Petrophysics remains a vital component to many facets of the petroleum industry, from quantification of hydrocarbon reserves to developmental strategies to real-time decision making for reservoir navigation. Targeted at awareness to knowledge level, this course addresses the tenets of petrophysics and formation evaluation, using integrative perspective of multiple datasets, including geological, geophysical, and logging and core data. Significant worldwide case histories are included, as well as several exercises designed to provide hands-on experience. This course can also be offered through Virtual Instructor Led Training (VILT) format. Training Objectives By attending this course, the participants will be able to: Understand better the latest geological, geophysical, and logging/core technologies and their role in petrophysical analysis, formation evaluation, and reservoir characterization. Address the pros and cons of key datasets, with emphasis on need for integrative studies and calibration of datasets. Apply quick-look qualitative techniques as well as quantitative aspects to understand vital aspects such as volume of shale/clay, porosity, permeability, and water saturation determinations. Select tool combinations to resolve key issues and for specific applications. Assess uncertainty in petrophysical measurements and techniques and its influence on reserve estimation. Target Audience This course is recommended for development and exploration geologists, petrophysicists, log and core analysts, geophysicists, petroleum engineers, managers, and technical personnel. Course Level Intermediate Trainer Your expert course leader received his B.S. and M.S. degrees in Geology from the now University of Louisiana-Lafayette in 1989 and 1990 respectively, and his Ph.D. as a National Science Foundation fellow at Baylor University, Waco, Texas, in 1993. From 1994 - 1996, he studied planetary tectonics as a NASA-funded postdoctoral fellow at Southern Methodist University. In 1996, he returned to UL-Lafayette, where he was awarded in 1997 the Hensarling-Chapman Endowed Professorship in Geology. He began independent consulting activities in 1991, and in 2001, he left academia for full-time consulting for clients ranging from one-man shops to supermajors. He rejoined UL-Lafayette as an adjunct professor from 2011 - 2018. He is an active researcher, receiving several million dollars in grants from federal, state, and industry sources, presenting numerous talks, including a 2019 AAPG Levorsen award, and publishing on a diversity of geoscience topics, including a Grover E. Murray Best Published Paper award in 2017. He is co-author of the inaugural GCAGS/GCSSEPM Transactions Best Student Paper award in 2018. He served as the GCAGS Publisher since 2006 and in various GCAGS/GCSSEPM Transactions editing capacities since 2006, including the 2014 and 2017 - 2022 Editor (named Permanent Transactions Editor in 2017), and Managing Editor since 2011, receiving a GCAGS Distinguished Service Award in 2018. He served as the General Chair for GeoGulf 2020 (70th GCAGS/GCSSEPM Convention), the 1st hybrid geoscience conference in the world. He is a Past President of the Lafayette Geological Society and served as its Editor and Publisher from 2002 - 2018. In 2018, he founded the Willis School of Applied Geoscience, reformulating decades of industry-training experience to provide alternative opportunities for graduate-level education. In 2020, he received an Honorary Membership from GCSSEPM. He also joined the LSU faculty as an adjunct professor in 2020. In 2021, he co-founded the Society of Applied Geoscientists and Engineers, serving as its President, General Chair for the SAGE 2022 Convention & Exposition, and Vice-Chair for the Benghazi International Geoscience & Engineering Conference 2022 (BIGEC 2022). POST TRAINING COACHING SUPPORT (OPTIONAL) To further optimise your learning experience from our courses, we also offer individualized 'One to One' coaching support for 2 hours post training. We can help improve your competence in your chosen area of interest, based on your learning needs and available hours. This is a great opportunity to improve your capability and confidence in a particular area of expertise. It will be delivered over a secure video conference call by one of our senior trainers. They will work with you to create a tailor-made coaching program that will help you achieve your goals faster. Request for further information about post training coaching support and fees applicable for this. Accreditions And Affliations

Build confidence & capability and engage in meaningful dialogue about race.

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)

Welcome to the Female Leadership Retreat - Intrinsically You! Come join us for a transformative 2 day (1 night) experience, where women come together to empower, inspire, and connect. At this leadership retreat, you'll have the opportunity to unleash your leadership potential, participate in workshops and discussions led by industry experts, and network with like-minded individuals. Embrace your authentic self and explore the leader within you in a supportive and encouraging environment. This retreat is designed to inspire growth and confidence in every attendee for women within Senior Leadership roles, Directors and Business Owners. You will be part of a small, intimate group with each retreat limited to just 10 guests. The environment will be calm, welcoming, and inclusive, with an informal and relaxed format that is supportive. The entire experience will leave you feeling energised with greater clarity, a new sense of purpose, and new personal insights, ready to fully engage with the next steps of your leadership journey. Don't miss out on this opportunity to invest in yourself and connect with a community of strong, empowered women. Join us at the all-inclusive*, Female Leadership Retreat - 'Intrinsically You' and embrace your leadership potential! *Price includes all accommodation, food and refreshments provided, use of spa facilities and training materials and a 1:1 coaching session following the event at a time to suit you. (Note: price excludes individually booked spa treatments, which can be organised directly with the venue in advance by participants.) Now is your time to step back, reflect and re-energise!

If you want to improve your or your team ability to lead a team successfully, feel free to check out my Training course focusing on the keys to success to effective Leadership.