1031 Courses in London

This course focuses on empowering managers to foster a culture of ownership, leverage effective delegation practices, and enhance productivity within their teams. Participants will explore strategies and techniques to delegate effectively, promote accountability, and optimise team performance. This course is available to book for delivery in-house for your organisation and people exclusively, for either a half or full days training workshop. Prices are dependent on size of group ranging from a minimum of 4 to a maximum of 12 delegates. If you have a smaller number of delegates the Puritas 1:1 Leadership Coaching Programme is recommended.

About this Training Course Liquefied Natural Gas (LNG) has provided intercontinental mobility to natural gas, which now provides about 25% of the global primary energy. Being the cleanest fossil fuel, natural gas/LNG consumption is forecasted to grow in all future scenarios. With the entry of various players, including Trading companies, the LNG value chain is becoming increasingly complex, and a solid understanding of its economics and management of its interfaces have become crucial to identify and assess investment opportunities and risks. Recent market disturbances caused by COVID-19, Oil & Gas price instabilities - coupled with the political (Ukraine/Russia) challenges - make a deep understanding of LNG Value Chain Logistics and Economics even more essential to ensure the security of energy supplies sustainably and profitably. This intermediate level 3 full-day course starts with a concise introduction to the LNG business. Thereafter, the elements of the LNG value chain are described, and their individual economics analysed. A Business Activity Model along the value chain will be developed and discussed in depth, covering the following key processes: 'Buy Gas - Transport Gas - Liquefy Gas - Sell LNG/Products - Ship LNG - Regasify LNG' The integrated chain economics will then be developed and quantified. A hands-on group workshop/exercise developing the economic case of a full-sized Liquefaction project will be carried out, considering the forecasted cash flows throughout the project life, the location of the plant, its markets, project sensitivities and profitability assessment. Participants will be provided with Excel based tools/models (LNG Liquefaction project development Net Present Value (NPV) analyses, Shipping Freight Calculations and Economics) to work through the exercises and also for their future personal use. Training Objectives After the completion of this course, participants will be able to: Understand how the LNG Value Chain operates, bound by the relevant Contracts and Agreements. Learn the basic economic parameters (operating, capital costs, financing, profitability) of each major element of the value chain. Appreciate the complexity of the value chain, and the associated opportunities and risks. Develop quantitative project evaluation skills. Explore options to maximise profitability in a given LNG value chain. Discuss best practices on how to manage, steer and govern these activities. Target Audience Technical, Operational, Shipping, Commercial, Project and Governance professionals who are already active in a specific section of the LNG Value Chain will directly benefit in developing a wider and deeper perspective on how the LNG Value Chain operations and can be optimised. Managers (Technical, Financial, Legal and Governance) less familiar with the specifics of the LNG Industry will also benefit from attending this VILT course, as they will obtain the required background to be able to set sharper targets, suitable performance indicators, and governance and performance assessment guidelines for units engaged in the chain. The course is most relevant for professionals engaged in the LNG industry at: National and International Oil & Gas/Energy Companies LNG Importers/Exporters/Traders/Shippers Government & Regulatory Agencies Finance Institutions It will also apply to the following audience: Business Development Managers Corporate Planning Professionals Project Developers Supply Planners & Scheduling Professionals Regulators Tax & Finance Advisors Compliance Officers Equity Analyst and Bankers Joint Venture Representatives, Board Directors Negotiators and Contracting Staff Trading Professionals Course Level Intermediate Trainer Your expert course leader is an Oil & Gas/LNG professional with more than 35 years of international experience, majority of which was gained at Shell International Joint Ventures engaged in Oil Refining, Supply / Trading, Gas Supply and LNG Businesses in the Netherlands, France, Thailand, Dominican Republic and Nigeria. Since 2004, he has had several roles in the management of the LNG Value Chain including the Commercial Operational Management of Nigeria LNG (NLNG). He played an active role in the start-up and integration of LNG trains 4, 5 and 6 with NLNG becoming the 3rd largest LNG producer in the world in 2007. Commercial operations spanned 4 Gas Supply, 11 LNG Sales & Purchase Agreements, ad-hoc LPG and Condensate Sales and LNG Ship Chartering contracts. Under his supervision, more than 2,000 LNG cargoes were exported. He was part of the organizational transformation of the company from a Project-based set-up to a Production / Commercial based structure and implemented an 'Integrated Planning and Scheduling Department' in which he optimized the value chain (Buy-Gas - Liquify Gas to LNG - Sell - Ship LNG). Staff competence management was one of his focus areas during this period. He was also the NLNG representative on JV Technical, Commercial, Shipping Committees where he interfaced with Government & Regulatory authorities. In 2014, he was appointed as Shell Shareholder representative to NLNG and became a Non-Executive Board member to NLNG companies, including Bonny Gas Transport (BGT) managing 24 LNG Ships. During this period, he was involved in the Economic and Technical steering of the Shipping Fleet and Liquefaction Plant Rejuvenation projects and a further capacity expansion of liquefaction plant which resulted in the achievement of NLNG train 7 project FID in 2019. Since 2016, he has been active as an independent consultant. He co-authored 2 patents and more than 30 published papers/presentations. He holds a PhD from Delft University of Technology in the Netherlands and a MSc and BSc in Chemical Engineering from the University of Birmingham, UK. 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 post training support and fees applicable Accreditions And Affliations

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Breakthrough Plus - overcome trauma and self-esteem issues (2 weekends course) Fast, effective and proven to overcome difficult life experiencesthat have caused you to shut down or have undermined your confidence and self-esteem Overcome your fears, improve your career prospects, build confidence, and make personal breakthroughs. Recommended for introverts, quiet people, or those hampered by difficult life experiences If your lack of confidence is connected to bad experiences in the past that have caused you to shut down and to close down your options, then the Breakthrough Plus is probably the fastest most effective way of overcoming this.

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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)