385 Analyst courses in Tilbury delivered Live Online

Enhance your knowledge in coal power plant life cycle management and flexible operations with EnergyEdge. Learn about decommissioning, preservation, repurposing, and recommissioning.

Enhance your knowledge of natural gas and LNG sales agreements with EnergyEdge course. Enroll now to gain valuable industry knowledge and skills.

Duration 3 Days 18 CPD hours This course is intended for CxO?s IT Managers/ Directors Senior Project Officers Project & Program Coordinator/Managers Operations Managers Quality Managers Business Analysts Engineering Managers IT Infrastructure Managers Internal Consultants Professional Consultants Overview Change and the individual Change and the organization Communication and stakeholder engagement Change practice Dealing with change and more importantly, the impact of change is a high priority for all organisations. The Change Management Certification has been developed by APMG in partnership with the Change Management Institute (CMI), an independent, global professional association of change managers. Together they have developed a professional ?body of knowledge? for the discipline of change management. This body of knowledge now provides an independent benchmark for the professional knowledge expected of an effective change manager. APMG?s refreshed Change Management certification is fully aligned with the change management body of knowledge. Prerequisites There is no prerequisite to attending this foundation course, although it is recommended that candidates should have a good understanding of business practices. 1 - Change and the Organization Drivers for change Developing a vision Culture and climate Emergent change and lifecycle Organizational metaphors Models of change Roles required for change 2 - Stakeholders Principles Identification Analysis Influencing and listening Emotion and demonstration Communications Cognitive biases Remaining people focused Improving Communications Communications channels Collaboration Communications Planning Larger workshops 2 - Change Impact Assessing impact McKinsey 7 S Stakeholder impact assessment Assessing change readiness Large change ? how to staff Building a change team Preparing for resistance Building team effectiveness 4 - Individual Change Learning theory Motivation Change Curve Personality differences

About this Training Growing global competitiveness in the refining products' market requires an in-depth knowledge of fuel technology processes, global quality standards and quality monitoring procedures. As the global market turns to cleaner fuels with more stringent specifications, the market in which refiners operate in, is getting more sophisticated and challenging. Training Objectives Upon completion of this course, participants will be able to: Get a clear overview of processing background and how white products are produced and blended Understand the blending impact on product quality and how to deal with quality giveaways, stability of blends and specification margins Get a clear overview of fuel blending operations, blending principles, specifics and operations Understand the role of additives and how additives are selected and used to meet the specification for different products and different markets Realize the importance of specifications, their limitations and how to ensure that the product is fit for purpose Be able to correctly interpret the laboratory results Target Audience The course is intended for individuals who are interested in the field of refining blending. The following personnel will benefit from the knowledge shared in this course: Plant operative planning and scheduling specialists Oil products trading and blending personnel Laboratory supervisors and technical personnel Sales, marketing and product trading personnel Refinery market and research analysts Process and chemical Engineers Personnel from the oil, fuel, biofuel, additive and auto industries Regulatory and policy-makers personnel Course Level Basic or Foundation Trainer Your expert course leader is an experienced manager with more than 25 years of operational experience in the downstream Oil & Gas industry. She is a recognised expert in conventional, biofuels and alternative fuels with extensive experience in the crude selection process and formulation of finished products including product portfolio strategy, product quality road mapping and benchmarking. She is a long-time laboratory manager with comprehensive experience in laboratory processes, including financing, benchmarking, efficiency improvement and total quality management processes. 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

About this training Decarbonization of the Upstream Oil & Gas sector has previously been based on inter-fuel competition. Market actions were seen as the most effective method for reducing the level of emissions. However, the pace of decarbonization is now being led by government policy acting in concert with a coalition of stakeholders such as investors and consumers. The primary focus of this pathway is on the management of carbon emissions to both mitigate and adapt to climate change. Some energy analysts have forecast that global production of oil and natural gas will have to decline annually by 4 to 6 percent in order to meet the global target of Net Zero Emissions by 2050. Oil and gas producers face a difficult challenge in deciding upon the strategy and measures that will best achieve targets set for them while maintaining supply, attracting investments and accessing markets. This 2-day training course will provide participants with an understanding of the strategies and measures for decarbonizing the Upstream Oil and Gas sector within the framework of measures implemented by individual governments through their respective commitments to reduce emissions to achieve their National Determined Contribution under the Paris Agreement. This course offers a unique opportunity to understand the rapidly increasing issues confronting the industry as well as the options for the management of carbon emissions to comply with corporate as well as national policies and the implementation of measures for controlling, reporting and verification. Training Objectives Upon completion of this course, participants will be better equipped to participate in the implementation of measures for the management of carbon emissions in the following areas: Implementation of measures for reducing carbon emissions Establishing systems for monitoring and reporting carbon emissions Evaluating the commerciality of discoveries Reviewing and strategizing future field development plans Meeting Environmental Obligations Target Audience This course has been specifically designed for professionals involved in the international oil and gas industry, whether employed a field operator, national oil company, or government. It offers a unique opportunity to rapidly increase your understanding of the issues confronting the industry as well as the options for the management of carbon emissions to comply with corporate as well as national policies and the implementation of measures for controlling, reporting and verification. Staff with the following roles will find this course particularly useful: Corporate Planners Project Engineers Financial Analysts Environmental Specialists Legal Advisors Regulatory & Compliance Officers Course Level Basic or Foundation Trainer Your expert course leader is an international legal expert in petroleum law who has been listed in the Guide to the World's Leading Energy and Natural Resources Lawyers. In his thirty years of practice, he has been the lead negotiator and acquisitions advisor for oil and gas companies in the US and the Asia-Pacific. These transactions have included both upstream (licences and leases) and downstream (refineries and pipelines) assets. He has been appointed as Distinguished Visiting Professor in Oil and Gas at the University of Wyoming and Honorary Professor at the Centre for Energy, Petroleum & Mineral Law & Policy (CEPMLP) at Dundee University. 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

Enhance your knowledge in petroleum geochemistry with EnergyEdge's course on petroleum exploration. Enroll now!

Gain expertise in IFRS accounting for the oil and gas sector with our industry-focused training course. Enroll today with EnergyEdge.

Duration 1 Days 6 CPD hours This course is intended for Security operations personnel, including analysts and incident responders Overview By the end of the course, you should be able to meet the following objectives: Utilize Carbon Black EDR throughout an incident Implement a baseline configuration for Carbon Black EDR Determine if an alert is a true or false positive Fully scope out an attack from moment of compromise Describe Carbon Black EDR capabilities available to respond to an incident Create addition detection controls to increase security This course teaches you how to use the VMware Carbon Black© EDR? product during incident response. Using the SANS PICERL framework, you will configure the server and perform an investigation on a possible incident. This course provides guidance on using Carbon Black EDR capabilities throughout an incident with an in-depth, hands-on, scenariobased lab. Course Introduction Introductions and course logistics Course objectives VMware Carbon Black EDR & Incident Response Framework identification and process Preparation Implement the Carbon Black EDR instance according to organizational requirements Identification Use initial detection mechanisms Process alerts Proactive threat hunting Incident determination Containment Incident scoping Artifact collection Investigation Eradication Hash banning Removing artifacts Continuous monitoring Recovery Rebuilding endpoints Getting to a more secure state Lessons Learned Tuning Carbon Black EDR Incident close out

Who is this course suitable for? Required to undertake asbestos fibre counting as part of their work Considering a career in asbestos analysis Responsible for managing asbestos analysts Prior Knowledge and Understanding Candidates for this course are expected to be aware of HSG 248 Asbestos: The Analysts' Guide (July 2021), and in particular Appendix 1, Fibres in air: sampling and evaluation of by phase contrast microscopy. Candidates will preferably have prior experience of analysing fibre count samples and may already be participating in a quality control scheme. In addition, candidates are expected to have had training to cover the core competencies outlined within the foundation material detailed within Table A9.1 of HSG248 Asbestos: The Analysts' Guide (July 2021). This may be achieved by In -house learning or through the P400 foundation module.

Duration 5 Days 30 CPD hours This course is intended for The skills covered in this course converge on four areas-software development, IT operations, applied math and statistics, and business analysis. Target students for this course should be looking to build upon their knowledge of the data science process so that they can apply AI systems, particularly machine learning models, to business problems. So, the target student is likely a data science practitioner, software developer, or business analyst looking to expand their knowledge of machine learning algorithms and how they can help create intelligent decisionmaking products that bring value to the business. A typical student in this course should have several years of experience with computing technology, including some aptitude in computer programming. This course is also designed to assist students in preparing for the CertNexus Certified Artificial Intelligence (AI) Practitioner (Exam AIP-210) certification Overview In this course, you will develop AI solutions for business problems. You will: Solve a given business problem using AI and ML. Prepare data for use in machine learning. Train, evaluate, and tune a machine learning model. Build linear regression models. Build forecasting models. Build classification models using logistic regression and k -nearest neighbor. Build clustering models. Build classification and regression models using decision trees and random forests. Build classification and regression models using support-vector machines (SVMs). Build artificial neural networks for deep learning. Put machine learning models into operation using automated processes. Maintain machine learning pipelines and models while they are in production Artificial intelligence (AI) and machine learning (ML) have become essential parts of the toolset for many organizations. When used effectively, these tools provide actionable insights that drive critical decisions and enable organizations to create exciting, new, and innovative products and services. This course shows you how to apply various approaches and algorithms to solve business problems through AI and ML, all while following a methodical workflow for developing data-driven solutions. Solving Business Problems Using AI and ML Topic A: Identify AI and ML Solutions for Business Problems Topic B: Formulate a Machine Learning Problem Topic C: Select Approaches to Machine Learning Preparing Data Topic A: Collect Data Topic B: Transform Data Topic C: Engineer Features Topic D: Work with Unstructured Data Training, Evaluating, and Tuning a Machine Learning Model Topic A: Train a Machine Learning Model Topic B: Evaluate and Tune a Machine Learning Model Building Linear Regression Models Topic A: Build Regression Models Using Linear Algebra Topic B: Build Regularized Linear Regression Models Topic C: Build Iterative Linear Regression Models Building Forecasting Models Topic A: Build Univariate Time Series Models Topic B: Build Multivariate Time Series Models Building Classification Models Using Logistic Regression and k-Nearest Neighbor Topic A: Train Binary Classification Models Using Logistic Regression Topic B: Train Binary Classification Models Using k-Nearest Neighbor Topic C: Train Multi-Class Classification Models Topic D: Evaluate Classification Models Topic E: Tune Classification Models Building Clustering Models Topic A: Build k-Means Clustering Models Topic B: Build Hierarchical Clustering Models Building Decision Trees and Random Forests Topic A: Build Decision Tree Models Topic B: Build Random Forest Models Building Support-Vector Machines Topic A: Build SVM Models for Classification Topic B: Build SVM Models for Regression Building Artificial Neural Networks Topic A: Build Multi-Layer Perceptrons (MLP) Topic B: Build Convolutional Neural Networks (CNN) Topic C: Build Recurrent Neural Networks (RNN) Operationalizing Machine Learning Models Topic A: Deploy Machine Learning Models Topic B: Automate the Machine Learning Process with MLOps Topic C: Integrate Models into Machine Learning Systems Maintaining Machine Learning Operations Topic A: Secure Machine Learning Pipelines Topic B: Maintain Models in Production