14 Machine Learning (ML) courses in Nottingham

This course shows you how to apply various approaches and algorithms to solve business problems through AI and ML, follow a methodical workflow to develop sound solutions, use open-source, off-the-shelf tools to develop, test, and deploy those solutions, and ensure that they protect the privacy of users. This course includes hands-on activities for each topic area.

ABOUT THIS TRAINING COURSE Artificial lift systems are an important part of production operations for the entire lifecycle of an asset. Often, oil and gas wells require artificial lift for most of the life cycle. This 5-day training course offers a thorough treatment of artificial lift techniques including design and operation for production optimization. With the increasing need to optimize dynamic production in highly constrained cost environments, opportunities and issues related to real-time measurements and optimization techniques needs to be discussed and understood. Artificial lift selection and life cycle analysis are covered. These concepts are discussed and reinforced using case studies, quizzing tools, and exercises with software. Participants solve examples and class problems throughout the course. Animations and videos reinforce the concepts under discussion. Understanding of these important production concepts is a must have to exploit the existing assets profitably. Unique Features: * Hands-on usage of SNAP Software to solve gas-lift exercises * Discussion on digital oil field * Machine learning applications in gas-lift optimization Training Objectives After the completion of this training course, participants will be able to: * Understand the basics and advanced concepts of each form of artificial lift systems including application envelope, relative strengths, and weaknesses * Easily recognize the different components from downhole to the surface and their basic structural and operational features * Design and analyze different components using appropriate software tools * Understand challenges facing artificial lift applications and the mitigation of these challenges during selection, design, and operation * Learn about the role of digital oilfield tools and techniques and their applications in artificial lift and production optimization * Learn about use cases of Machine learning and artificial intelligence in the artificial lift Target Audience This training course is suitable and will greatly benefit the following specific groups: * Production, reservoir, completion, drilling and facilities engineers, analysts, and operators * Anyone interested in learning about selection, design, analysis and optimum operation of artificial lift and related production systems will benefit from this course. Course Level * Intermediate * Advanced Training Methods The training instructor relies on a highly interactive training method to enhance the learning process. This method ensures that all participants gain a complete understanding of all the topics covered. The training environment is highly stimulating, challenging, and effective because the participants will learn by case studies which will allow them to apply the material taught in their own organization. Course Duration: 5 days in total (35 hours). Training Schedule 0830 - Registration 0900 - Start of training 1030 - Morning Break 1045 - Training recommences 1230 - Lunch Break 1330 - Training recommences 1515 - Evening break 1530 - Training recommences 1700 - End of Training The maximum number of participants allowed for this training course is 20. This course is also available through our Virtual Instructor Led Training (VILT) format. Prerequisites: * Understanding of petroleum production concepts. * Each participant needs a laptop/PC for solving class examples using software to be provided during class. Laptop/PC needs to have a current Windows operating system and at least 500 MB free disk space. Participants should have administrator rights to install software. Trainer Your expert course leader has over 35 years' work-experience in multiphase flow, artificial lift, real-time production optimization and software development/management. His current work is focused on a variety of use cases like failure prediction, virtual flow rate determination, wellhead integrity surveillance, corrosion, equipment maintenance, DTS/DAS interpretation. He has worked for national oil companies, majors, independents, and service providers globally. He has multiple patents and has delivered a multitude of industry presentations. Twice selected as an SPE distinguished lecturer, he also volunteers on SPE committees. He holds a Bachelor's and Master's in chemical engineering from the Gujarat University and IIT-Kanpur, India; and a Ph.D. in Petroleum Engineering from the University of Tulsa, USA. Highlighted Work Experience: * At Weatherford, consulted with clients as well as directed teams on digital oilfield solutions including LOWIS - a solution that was underneath the production operations of Chevron and Occidental Petroleum across the globe. * Worked with and consulted on equipment's like field controllers, VSDs, downhole permanent gauges, multiphase flow meters, fibre optics-based measurements. * Shepherded an enterprise-class solution that is being deployed at a major oil and gas producer for production management including artificial lift optimization using real time data and deep-learning data analytics. * Developed a workshop on digital oilfield approaches for production engineers. Patents: * Principal inventor: 'Smarter Slug Flow Conditioning and Control' * Co-inventor: 'Technique for Production Enhancement with Downhole Monitoring of Artificially Lifted Wells' * Co-inventor: 'Wellbore real-time monitoring and analysis of fracture contribution' Worldwide Experience in Training / Seminar / Workshop Deliveries: * Besides delivering several SPE webinars, ALRDC and SPE trainings globally, he has taught artificial lift at Texas Tech, Missouri S&T, Louisiana State, U of Southern California, and U of Houston. * He has conducted seminars, bespoke trainings / workshops globally for practicing professionals: * Companies: Basra Oil Company, ConocoPhillips, Chevron, EcoPetrol, Equinor, KOC, ONGC, LukOil, PDO, PDVSA, PEMEX, Petronas, Repsol, , Saudi Aramco, Shell, Sonatrech, QP, Tatneft, YPF, and others. * Countries: USA, Algeria, Argentina, Bahrain, Brazil, Canada, China, Croatia, Congo, Ghana, India, Indonesia, Iraq, Kazakhstan, Kenya, Kuwait, Libya, Malaysia, Oman, Mexico, Norway, Qatar, Romania, Russia, Serbia, Saudi Arabia, S Korea, Tanzania, Thailand, Tunisia, Turkmenistan, UAE, Ukraine, Uzbekistan, Venezuela. * Virtual training provided for PetroEdge, ALRDC, School of Mines, Repsol, UEP-Pakistan, and others since pandemic. 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 COURSE There are various kinds of geophysical data available. They are separated into seismic and non-seismic (multi-physics) data. Non-seismic or multi-physics data (which includes gravity, magnetics, electrical, electromagnetics, spectral etc - apart from providing complimentary information to seismic) is the main source of information for very shallow subsurface applications such as engineering, mapping pollution, archaeology, geothermal energy, and related areas. This 5 full-day blended course will focus specifically on seismic data which is the main method used in the Oil & Gas industry. In this blended course, participants will be equipped to understand that seismic data represents the movement of the surface, resulting from waves generated by a source, dynamite or vibrator which are reflected by changes in the subsurface rocks. The basic principles of acquisition and processing will be explained and insights into advanced methods, allowing a much more accurate interpretation of seismic data than previously considered possible, will also be provided. This blended course contains an introduction to Machine Learning and its important role in all aspects of seismic acquisition, processing, and interpretation. There is no need to know in detail how the algorithms work internally but it is necessary to know how to use them correctly to achieve optimum results. Training Objectives By attending this course, participants will be able to acquire the following: * Obtain an understanding of the strengths and limitations of geophysical methods, specifically seismic, and the costs and risks involved, and how to reduce these. * Be able to communicate more effectively with staff in other disciplines. * Understand the potential applications of seismic data and know how to formulate the requirements needed for prospect and field evaluation. * Gain an awareness of modern seismic technology. * Apply the learning in a series of practical, illustrative exercises. * Know what types of questions to ask to assess the necessary quality of a seismic project in its role in a sequence of E&P activities Target Audience The blended course is intended for non-geophysicists who have intensive interaction with geophysicists. But it may be of interest to those who want to know about the recent progress made in geophysics, leading to amazing imaging results, which could not be imagined a decade ago. The blended course will bring to the attention of the geologists, petrophysicists and reservoir/petroleum engineers an awareness of how the data they will work with is acquired and processed by the geophysicist. It will introduce the concepts that are of importance in geophysics and thus relevant for non-geophysicists to know and be able to communicate with geophysicists as well as formulate their requests. Course Level * Intermediate Trainer Your expert course leader has degree in Geology (University of Leiden), a Master's degree in Theoretical Geophysics (University of Utrecht) and a PhD in Utrecht on 'Full wave theory and the structure of the lower mantle'. This involved forward modelling of P- and S-waves diffracted around the core-mantle boundary and comparison of the frequency-dependent attenuation of the signal with those obtained from major earthquakes observed at long offsets in the 'shadow zone' of the core. These observations were then translated into rock properties of the D' transition zone. After his PhD, he joined Shell Research in The Netherlands to develop methods to predict lithology and pore-fluid based on seismic, petrophysical and geological data. He subsequently worked for Shell in London to interpret seismic data from the Central North Sea Graben. As part of the Quantitative Interpretation assignment, he was also actively involved in managing, processing and interpreting Offshore Seismic Profiling experiments. After his return to The Netherlands, he headed a team for the development of 3D interpretation methods using multi-attribute statistical and pattern recognition analysis on workstations. After a period of Quality Assurance of 'Contractor' software for seismic processing, he became responsible for Geophysics in the Shell Learning Centre. During that period, he was also a part-time professor in Applied Geophysics at the University of Utrecht. From 2001 to 2005, he worked on the development of Potential Field Methods (Gravity, Magnetics) for detecting oil and gas. Finally, he became a champion on the use of EM methods and became involved in designing acquisition, processing and interpretation methods for Marine Controlled Source EM (CSEM) methods. After his retirement from Shell, he founded his own company, specialising in courses on acquisition, processing and interpretation of geophysical data (seismic, gravity, magnetic and electromagnetic data), providing courses to International and National energy companies. In the last couple of years, he became keenly interested in the use of Machine Learning in Geophysics. Apart from incorporating 'Artificial Intelligence' in his courses, he also developed a dedicated Machine Learning course for geophysics. 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 COURSE Gas-lift is one of the predominant forms of artificial lift used for lifting liquids from conventional, unconventional, onshore and offshore assets. Gas-lift and its various forms (intermittent lift, gas-assisted plunger lift) allows life of well lift-possibilities when selected and applied properly. This 5-day training course is designed to give participants a thorough understanding of gas-lift technology and related application concepts. This training course covers main components such as application envelope, relative strengths and weaknesses of gas-lift and its different forms like intermittent lift, gas-assisted plunger lift. Participants solve examples and class problems throughout the course. Animations and videos reinforce the concepts under discussion. Unique Features: * Hands-on usage of SNAP Software to solve gas-lift exercises * Discussion on digital oil field * Machine learning applications in gas-lift optimization Training Objectives After the completion of this training course, participants will be able to: * Understand the fundamental theories and procedures related to Gas-Lift operations * Easily recognize the different components of the gas-lift system and their basic structural and operational features * Be able to design a gas-lift installation * Comprehend how digital oilfield tools help address ESP challenges * Examine recent advances in real-time approaches to the production monitoring and lift management Target Audience This training course is suitable and will greatly benefit the following specific groups: * Production, reservoir, completion, drilling and facilities engineers, analysts, and operators * Anyone interested in learning about implications of gas-lift systems for their fields and reservoirs Course Level * Intermediate * Advanced Training Methods The training instructor relies on a highly interactive training method to enhance the learning process. This method ensures that all participants gain a complete understanding of all the topics covered. The training environment is highly stimulating, challenging, and effective because the participants will learn by case studies which will allow them to apply the material taught in their own organization. Course Duration: 5 days in total (35 hours). Training Schedule 0830 - Registration 0900 - Start of training 1030 - Morning Break 1045 - Training recommences 1230 - Lunch Break 1330 - Training recommences 1515 - Evening break 1530 - Training recommences 1700 - End of Training The maximum number of participants allowed for this training course is 20. This course is also available through our Virtual Instructor Led Training (VILT) format. Prerequisites: * Understanding of petroleum production concepts. * Each participant needs a laptop/PC for solving class examples using software to be provided during class. Laptop/PC needs to have a current Windows operating system and at least 500 MB free disk space. Participants should have administrator rights to install software. Trainer Your expert course leader has over 35 years' work-experience in multiphase flow, artificial lift, real-time production optimization and software development/management. His current work is focused on a variety of use cases like failure prediction, virtual flow rate determination, wellhead integrity surveillance, corrosion, equipment maintenance, DTS/DAS interpretation. He has worked for national oil companies, majors, independents, and service providers globally. He has multiple patents and has delivered a multitude of industry presentations. Twice selected as an SPE distinguished lecturer, he also volunteers on SPE committees. He holds a Bachelor's and Master's in chemical engineering from the Gujarat University and IIT-Kanpur, India; and a Ph.D. in Petroleum Engineering from the University of Tulsa, USA. Highlighted Work Experience: * At Weatherford, consulted with clients as well as directed teams on digital oilfield solutions including LOWIS - a solution that was underneath the production operations of Chevron and Occidental Petroleum across the globe. * Worked with and consulted on equipment's like field controllers, VSDs, downhole permanent gauges, multiphase flow meters, fibre optics-based measurements. * Shepherded an enterprise-class solution that is being deployed at a major oil and gas producer for production management including artificial lift optimization using real time data and deep-learning data analytics. * Developed a workshop on digital oilfield approaches for production engineers. Patents: * Principal inventor: 'Smarter Slug Flow Conditioning and Control' * Co-inventor: 'Technique for Production Enhancement with Downhole Monitoring of Artificially Lifted Wells' * Co-inventor: 'Wellbore real-time monitoring and analysis of fracture contribution' Worldwide Experience in Training / Seminar / Workshop Deliveries: * Besides delivering several SPE webinars, ALRDC and SPE trainings globally, he has taught artificial lift at Texas Tech, Missouri S&T, Louisiana State, U of Southern California, and U of Houston. * He has conducted seminars, bespoke trainings / workshops globally for practicing professionals: * Companies: Basra Oil Company, ConocoPhillips, Chevron, EcoPetrol, Equinor, KOC, ONGC, LukOil, PDO, PDVSA, PEMEX, Petronas, Repsol, , Saudi Aramco, Shell, Sonatrech, QP, Tatneft, YPF, and others. * Countries: USA, Algeria, Argentina, Bahrain, Brazil, Canada, China, Croatia, Congo, Ghana, India, Indonesia, Iraq, Kazakhstan, Kenya, Kuwait, Libya, Malaysia, Oman, Mexico, Norway, Qatar, Romania, Russia, Serbia, Saudi Arabia, S Korea, Tanzania, Thailand, Tunisia, Turkmenistan, UAE, Ukraine, Uzbekistan, Venezuela. * Virtual training provided for PetroEdge, ALRDC, School of Mines, Repsol, UEP-Pakistan, and others since pandemic. 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 COURSE This 5 full-day course presents the most modern statistical and mathematical forecasting frameworks used by practitioners to tackle the load forecasting problem across short time and long time scales. The course presents practical applications to solving forecasting challenges, supported by real life examples from large control areas. It presents the weather impacts on the load forecasts and the methodologies employed to quantify the weather effect and building a repository of weather normal data. A good load forecast methodology must improve its forecasting accuracy and support a consistent load forecasting process. The load forecasting widely used in the power industry has evolved significantly with the advancement and adoption of Artificial Intelligence techniques such as Machine Learning. With the increased penetration of inverter-based resources, the operation of electric grids grew in complexity, leading to load forecasts that are updated more frequently than once a day. Furthermore, several jurisdictions adopted a smaller granularity than the hourly load forecasts in the effort to reduce the forecasting uncertainties. On the generation side, fuel forecasting professionals must meet energy requirements while making allowance for the uncertainty on both the demand and the supply side. This training course will also feature a guest speaker, who is a Ph.D candidate to provide insights into the most modern aspects of Artificial Intelligence in the context of load forecasting. Training Objectives This course offers a comprehensive approach to all aspects of load forecasting: * Gain a perspective of load forecasting from both operators in the generating plant and system operators. * Understand and review the advanced load forecasting concepts and forecasting methodologies * Learn the application of Artificial Neural Networks and Probabilistic Forecasting methods to manage forecasting uncertainties in short time frames * Appreciate market segmentation and econometric framework for long term forecasts * Find out the most recent practical application of load forecasting as examples from large power companies * Get access to recent industry reports and developments Target Audience * Energy load forecasting professionals from power plant and system operators * Energy planners and energy outlook forecasters and plant operators * Fuel procurement professionals * Planners and schedulers of thermal generating units Course Level * Intermediate Trainer Your expert course instructor is a Utility Executive with extensive global experience in power system operation and planning, energy markets, enterprise risk and regulatory oversight. She consults on energy markets integrating renewable resources from planning to operation. She led complex projects in operations and conducted long term planning studies to support planning and operational reliability standards. Specializing in Smart Grids, Operational flexibilities, Renewable generation, Reliability, Financial Engineering, Energy Markets and Power System Integration, she was recently engaged by the Inter-American Development Bank/MHI in Guyana. She was the Operations Expert in the regulatory assessment in Oman. She is a registered member of the Professional Engineers of Ontario, Canada. She is also a contributing member to the IEEE Standards Association, WG Blockchain P2418.5. With over 25 years with Ontario Power Generation (Revenue $1.2 Billion CAD, I/S 16 GW), she served as Canadian representative in CIGRE, committee member in NSERC (Natural Sciences and Engineering Research Council of Canada), and Senior Member IEEE and Elsevier since the 90ties. Our key expert chaired international conferences, lectured on several continents, published a book on Reliability and Security of Nuclear Power Plants, contributed to IEEE and PMAPS and published in the Ontario Journal for Public Policy, Canada. She delivered seminars organized by the Power Engineering Society, IEEE plus seminars to power companies worldwide, including Oman, Thailand, Saudi Arabia, Malaysia, Indonesia, Portugal, South Africa, Japan, Romania, and Guyana. Our Key expert delivered over 60 specialized seminars to executives and engineers from Canada, Europe, South and North America, Middle East, South East Asia and Japan. Few examples are: * Modern Power System in Digital Utilities - The Energy Commission, Malaysia and utilities in the Middle East, GCCIA, June 2020 * Assessment of OETC Control Centre, Oman, December 2019 * Demand Side management, Load Forecasting in a Smart Grid, Oman, 2019 * Renewable Resources in a Smart Grid (Malaysia, Thailand, Indonesia, GCCIA, Saudi Arabia) * The Modern Power System: Impact of the Power Electronics on the Power System * The Digital Utility, AI and Blockchain * Smart Grid and Reliability of Distribution Systems, Cyme, Montreal, Canada * Economic Dispatch in the context of an Energy Market (TNB, Sarawak Energy, Malaysia) * Energy Markets, Risk Assessment and Financial Management, PES, IEEE: Chicago, San Francisco, New York, Portugal, South Africa, Japan. Provided training at CEO and CRO level. * Enterprise Risk methodology, EDP, Portugal * Energy Markets: Saudi Electricity Company, Tenaga National Berhad, Malaysia * Reliability Centre Maintenance (South East Asia, Saudi Electricity Company, KSA) * EUSN, ENERGY & UTILITIES SECTOR NETWORK, Government of Canada, 2016 * Connected+, IOT, Toronto, Canada September 2016 and 2015 * Smart Grid, Smart Home HomeConnect, Toronto, Canada November 2014 * Wind Power: a Cautionary Tale, Ontario Centre for Public Policy, 2010 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 COURSE Business Impact: The main aim is to provide insight and understanding of data analytics and machine learning principles through applications. Field data is used to explain data-analysis workflows. Using easy to follow solution scripts, the participants will assess and extract value from the data sets. Hands-on solution approach will give them confidence to try out applicable techniques on data from their field assets. Data analysis means cleaning, inspecting, transforming, and modeling data with the goal of discovering new, useful information and supporting decision-making. In this hands-on 2-day training course, the participants learn some data analysis and data science techniques and workflows applied to petroleum production (specifically artificial lift) while reviewing code and practicing. The focus is on developing data-driven models while keeping our feet closer to the underlying oil and gas production principles. Unique Features: * Eight business use cases covering their business impact, code walkthroughs for most all and solution approach. * Industry data sets for participants to practice on and take home. * No software or complicated Python frameworks required. Training Objectives After the completion of this training course, participants will be able to: * Understand digital oil field transformation and its impact on business * Examine machine learning methods * Review workflows and code implementations * After completing the course, participants will have a set of tools and some pathways to model and analyze their data in the cloud, find trends, and develop data-driven models Target Audience This training course is suitable and will greatly benefit the following specific groups: * Artificial lift, production and facilities engineers and students to enhance their knowledge base, increase technology awareness, and improve the facility with different data analysis techniques applied on large data sets Course Level * Intermediate * Advanced Training Methods The course discusses several business use-cases that are amenable to data-driven workflows. For each use case, the instructor will show the solution using a data analysis technique with Python code deployed in the Google cloud. Trainees will solve a problem and tweak their solution. Course Duration: 2 days in total (14 hours). Training Schedule 0830 - Registration 0900 - Start of training 1030 - Morning Break 1045 - Training recommences 1230 - Lunch Break 1330 - Training recommences 1515 - Evening break 1530 - Training recommences 1700 - End of Training The maximum number of participants allowed for this training course is 20. This course is also available through our Virtual Instructor Led Training (VILT) format. Prerequisites: * Understanding of petroleum production concepts * Knowledge of Python is not a must but preferred to get the full benefit. * The training will use the Google Collaboratory environment available in Google-Cloud for hands-on exercises * Trainees will need to bring a computer with a Google Chrome browser and a Google email account (available for free) Trainer Your expert course leader has over 35 years' work-experience in multiphase flow, artificial lift, real-time production optimization and software development/management. His current work is focused on a variety of use cases like failure prediction, virtual flow rate determination, wellhead integrity surveillance, corrosion, equipment maintenance, DTS/DAS interpretation. He has worked for national oil companies, majors, independents, and service providers globally. He has multiple patents and has delivered a multitude of industry presentations. Twice selected as an SPE distinguished lecturer, he also volunteers on SPE committees. He holds a Bachelor's and Master's in chemical engineering from the Gujarat University and IIT-Kanpur, India; and a Ph.D. in Petroleum Engineering from the University of Tulsa, USA. Highlighted Work Experience: * At Weatherford, consulted with clients as well as directed teams on digital oilfield solutions including LOWIS - a solution that was underneath the production operations of Chevron and Occidental Petroleum across the globe. * Worked with and consulted on equipment's like field controllers, VSDs, downhole permanent gauges, multiphase flow meters, fibre optics-based measurements. * Shepherded an enterprise-class solution that is being deployed at a major oil and gas producer for production management including artificial lift optimization using real time data and deep-learning data analytics. * Developed a workshop on digital oilfield approaches for production engineers. Patents: * Principal inventor: 'Smarter Slug Flow Conditioning and Control' * Co-inventor: 'Technique for Production Enhancement with Downhole Monitoring of Artificially Lifted Wells' * Co-inventor: 'Wellbore real-time monitoring and analysis of fracture contribution' Worldwide Experience in Training / Seminar / Workshop Deliveries: * Besides delivering several SPE webinars, ALRDC and SPE trainings globally, he has taught artificial lift at Texas Tech, Missouri S&T, Louisiana State, U of Southern California, and U of Houston. * He has conducted seminars, bespoke trainings / workshops globally for practicing professionals: * Companies: Basra Oil Company, ConocoPhillips, Chevron, EcoPetrol, Equinor, KOC, ONGC, LukOil, PDO, PDVSA, PEMEX, Petronas, Repsol, , Saudi Aramco, Shell, Sonatrech, QP, Tatneft, YPF, and others. * Countries: USA, Algeria, Argentina, Bahrain, Brazil, Canada, China, Croatia, Congo, Ghana, India, Indonesia, Iraq, Kazakhstan, Kenya, Kuwait, Libya, Malaysia, Oman, Mexico, Norway, Qatar, Romania, Russia, Serbia, Saudi Arabia, S Korea, Tanzania, Thailand, Tunisia, Turkmenistan, UAE, Ukraine, Uzbekistan, Venezuela. * Virtual training provided for PetroEdge, ALRDC, School of Mines, Repsol, UEP-Pakistan, and others since pandemic. 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 VIRTUAL INSTRUCTOR LED TRAINING (VILT) This 5 half-day Virtual Instructor Led Training (VILT) course will assist energy professionals in the planning and operation of a power system from renewable energy sources. The VILT course will discuss key operating requirements for an integrated, reliable and stable power system. The unique characteristics of renewable energy are discussed from a local, consumer centric and system perspective, bringing to life the ever-changing paradigm in delivering energy to customers. The course will explore the technical challenges associated with interconnecting and integrating hundreds of gigawatts of solar power onto the electricity grid in a safe and reliable way. With references to international case studies, the VILT course will also demonstrate the state of the art methodologies used in forecasting solar power. The flexibility of the invertor-based resources will facilitate higher penetrations of photovoltaic, battery electricity storage systems and demand response while co-optimizing customer resources. The contribution of inverter-based generators that provides voltage support, frequency response and regulation (droop response), reactive power and power quality with a high level of accuracy and fast response will be addressed. Furthermore, this VILT course will also describe how microgrids' controllers can allow for a fully automated energy management. Distributed energy resources are analyzed in detail from a technical and financial aspect and will address the best known cost based methodologies such as project financing and cost recovery. Training Objectives Upon completion of this VILT course, participants will be able to: * Learn about renewable energy resources, their applications and methods of analysis of renewable energy issues. * Review the operational flexibility of renewable energy at grid level, distribution network and grid edge devices. * Understand and analyze energy performance from main renewable energy systems. * Get equipped on the insights into forecasting models for solar energy. * Predict solar generation from weather forecasts using machine learning. * Explore operational aspects of a complex power system with variability from both the supply & demand sides. * Manage the impact of the design of a Power Purchase Agreement (PPA) on the power system operation. Target Audience Engineers, planners and operations professionals from the following organizations: * Energy aggregators who would like to understand the system operations of renewable energy power plants * Renewable energy power system operator * Energy regulatory agencies who aim to derive strategies and plans based on the feedback obtained from the power system operations Course Level * Basic or Foundation Training Methods The VILT course will be delivered online in 5 half-day sessions comprising 4 hours per day, including time for lectures, discussion, quizzes and short classroom exercises. Course Duration: 5 half-day sessions, 4 hours per session (20 hours in total). Trainer Your first expert course leader is a Utility Executive with extensive global experience in power system operation and planning, energy markets, enterprise risk and regulatory oversight. She consults on energy markets integrating renewable resources from planning to operation. She led complex projects in operations and conducted long term planning studies to support planning and operational reliability standards. Specializing in Smart Grids, Operational flexibilities, Renewable generation, Reliability, Financial Engineering, Energy Markets and Power System Integration, she was recently engaged by the Inter-American Development Bank/MHI in Guyana. She was the Operations Expert in the regulatory assessment in Oman. She is a registered member of the Professional Engineers of Ontario, Canada. She is also a contributing member to the IEEE Standards Association, WG Blockchain P2418.5. With over 25 years with Ontario Power Generation (Revenue $1.2 Billion CAD, I/S 16 GW), she served as Canadian representative in CIGRE, committee member in NSERC (Natural Sciences and Engineering Research Council of Canada), and Senior Member IEEE and Elsevier since the 90ties. Our key expert chaired international conferences, lectured on several continents, published a book on Reliability and Security of Nuclear Power Plants, contributed to IEEE and PMAPS and published in the Ontario Journal for Public Policy, Canada. She delivered seminars organized by the Power Engineering Society, IEEE plus seminars to power companies worldwide, including Oman, Thailand, Saudi Arabia, Malaysia, Indonesia, Portugal, South Africa, Japan, Romania, and Guyana. Your second expert course leader is the co-founder and Director of Research at Xesto Inc. Xesto is a spatial computing AI startup based in Toronto, Canada and it has been voted as Toronto's Best Tech Startup 2019 and was named one of the top 10 'Canadian AI Startups to Watch' as well as one of 6th International finalists for the VW Siemens Startup Challenge, resulting in a partnership. His latest app Xesto-Fit demonstrates how advanced AI and machine learning is applied to the e-commerce industry, as a result of which Xesto has been recently featured in TechCrunch. He specializes in both applied and theoretical machine learning and has extensive experience in both industrial and academic research. He is specialized in Artificial Intelligence with multiple industrial applications. At Xesto, he leads projects that focus on applying cutting edge research at the intersection of spatial analysis, differential geometry, optimization of deep neural networks, and statistics to build scalable rigorous and real time performing systems that will change the way humans interact with technology. In addition, he is a Ph.D candidate in the Mathematics department at UofT, focusing on applied mathematics. His academic research interests are in applying advanced mathematical methods to the computational and statistical sciences. He earned a Bachelor's and MSc in Mathematics, both at the University of Toronto. Having presented at research seminars as well as instructing engineers on various levels, he has the ability to distill advanced theoretical concept to diverse audiences on all levels. In addition to research, our key expert is also an avid traveler and plays the violin. 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

ABOUT THIS VIRTUAL INSTRUCTOR LED TRAINING (VILT) This Virtual Instructor Led Training (VILT) course presents advanced methodologies that implement demand response and energy conservation programs in light of the integration of new technologies, regulatory changes and the accelerated penetration of renewable energy resources. This VILT course provides examples and case studies from North American and European jurisdictions covering the operational flexibilities on the demand side including requirements for new building codes to achieve zero net energy. The course describes a public agency's goals and objectives for conserving and otherwise reducing energy consumption and managing its demand for energy. This course presents the demand response implemented for economics and system security such as system balancing and relieving transmission congestion, or for system adequacy. The course also presents the principal attributes of conservation programs and the associated success criteria. In a system with increased penetration of renewable resources, demand response provides flexibility to system operators, helping them to maintain the reliability and the security of supply. Demand response is presented as a competitive alternative to additional power sources, enhancing competition and liquidity in electricity markets. The unique characteristics are discussed from a local, consumer centric and also from a system perspective bringing to life the ever changing paradigm for delivery energy to customers. Interoperability aspects and standards are discussed, as well as the consumer centric paradigm of Transactive Energy with IOT enabled flexibilities at system level, distribution networks and microgrids. The VILT course introduces the blockchain as a new line of defense against cyber threats and its increasing application in P2P transactions and renewable certificates. Our trainer's industry experience spans three decades with one of the largest Canadian utilities where she led or contributed to large operational studies and energy policies and decades of work with IEEE, NSERC and CIGRE. Our key expert also approaches to the cross sectional, interdisciplinary state of the art methodologies brings real life experience of recent industry developments. Training Objectives * Innovative Digital Technologies * How systems Facilitate Operational Flexibility on the Demand Side * The Ecosystem of Demand Side Management Programs * Advanced Machine Learning techniques with examples from CAISO * Regulatory Policy Context and how to reduce regulatory barriers * Industry Examples from NERC and ENTSO * Relevant Industry standards: IEEE and IEC * Manage Congestion with Distributed Operational Flexibilities: Grid to Distribution Controls; examples from NERC (NA) and ENTSO (Europe) * Grid solutions with IEC 61850 communication protocols * Decentralized grid controls * The New Grid with accelerated V2G and Microgrids * How DSM is and will be applied in Your System: Examples and discussions Target Audience * Regulators and government agencies advising on public energy conservation programs * All professionals interested in expanding their expertise, or advancing their career, or take on management and leadership roles in the rapidly evolving energy sector * Energy professionals implementing demand side management, particularly in power systems with increased renewable penetration, to allow the much needed operational flexibility paramount to maintaining the reliability and stability of the power system and in the same time offering all classes of customers flexible and economical choices * Any utility professional interested in understanding the new developments in the power industry Course Level * Basic or Foundation Training Methods The VILT course will be delivered online in 5 half-day sessions comprising 4 hours per day, with 2 x 10 minutes break per day, including time for lectures, discussion, quizzes and short classroom exercises. Course Duration: 5 half-day sessions, 4 hours per session (20 hours in total). Trainer Your first expert course leader is a Utility Executive with extensive global experience in power system operation and planning, energy markets, enterprise risk and regulatory oversight. She consults on energy markets integrating renewable resources from planning to operation. She led complex projects in operations and conducted long term planning studies to support planning and operational reliability standards. Specializing in Smart Grids, Operational flexibilities, Renewable generation, Reliability, Financial Engineering, Energy Markets and Power System Integration, she was recently engaged by the Inter-American Development Bank/MHI in Guyana. She was the Operations Expert in the regulatory assessment in Oman. She is a registered member of the Professional Engineers of Ontario, Canada. She is also a contributing member to the IEEE Standards Association, WG Blockchain P2418.5. With over 25 years with Ontario Power Generation (Revenue $1.2 Billion CAD, I/S 16 GW), she served as Canadian representative in CIGRE, committee member in NSERC (Natural Sciences and Engineering Research Council of Canada), and Senior Member IEEE and Elsevier since the 90ties. Our key expert chaired international conferences, lectured on several continents, published a book on Reliability and Security of Nuclear Power Plants, contributed to IEEE and PMAPS and published in the Ontario Journal for Public Policy, Canada. She delivered seminars organized by the Power Engineering Society, IEEE plus seminars to power companies worldwide, including Oman, Thailand, Saudi Arabia, Malaysia, Indonesia, Portugal, South Africa, Japan, Romania, and Guyana. Your second expert course leader is the co-founder and Director of Research at Xesto Inc. Xesto is a spatial computing AI startup based in Toronto, Canada and it has been voted as Toronto's Best Tech Startup 2019 and was named one of the top 10 'Canadian AI Startups to Watch' as well as one of 6th International finalists for the VW Siemens Startup Challenge, resulting in a partnership. His latest app Xesto-Fit demonstrates how advanced AI and machine learning is applied to the e-commerce industry, as a result of which Xesto has been recently featured in TechCrunch. He specializes in both applied and theoretical machine learning and has extensive experience in both industrial and academic research. He is specialized in Artificial Intelligence with multiple industrial applications. At Xesto, he leads projects that focus on applying cutting edge research at the intersection of spatial analysis, differential geometry, optimization of deep neural networks, and statistics to build scalable rigorous and real time performing systems that will change the way humans interact with technology. In addition, he is a Ph.D candidate in the Mathematics department at UofT, focusing on applied mathematics. His academic research interests are in applying advanced mathematical methods to the computational and statistical sciences. He earned a Bachelor's and MSc in Mathematics, both at the University of Toronto. Having presented at research seminars as well as instructing engineers on various levels, he has the ability to distill advanced theoretical concept to diverse audiences on all levels. In addition to research, our key expert is also an avid traveler and plays the violin. 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

ABOUT THIS VIRTUAL INSTRUCTOR LED TRAINING (VILT) The energy industry has started its journey to be more data centric by embracing the industry 4.0 concept. As a result, data management - which was considered until recently as a back-office service to support geoscience, reservoir management, engineering, production and maintenance - is now given the spotlight! To become an active stakeholder in this important transition in E&P data management, it is necessary to understand the new technical opportunities offered by the Cloud, Artificial Intelligence and how data governance can pave the way towards more reliable and resilient processes within E&P domain. Several key questions that need to be addressed: 1. Why place more focus on data assets? 2. Is data management just about serving geoscientists or engineers with fresh data? 3. What is the value of data management in the E&P sector for decision making? 4. How to convince the data consumers that the data we provide is reliable? 5. Is the data architecture of my organization appropriate and sustainable? The purpose of this 5 half-day Virtual Instructor Led Training (VILT) course is to present the data challenges facing the energy organizations today and see how they practically solve them. The backbone of this course is based on the DAMA Book of Knowledge for Data Management. The main data management activities are described in sequence with a particular focus on recent technological developments. Training Objectives Upon completion of this VILT course, the participants will be able to: * Understand why the data asset is now considered as a main asset by energy organizations * Appreciate the importance of data governance and become an active stakeholder of it * Understand the architecture and implementation of data structure in their professional environment * Get familiarized with the more important data management activities such as data security and data quality * Integrate their subsurface and surface engineering skills with the data managements concepts This VILT course is unique on several points: * All notions are explained by some short presentations. For each of them, a set of video, exercises, quizzes will be provided to help develop an engaging experience between the trainer and the participants * A pre-course questionnaire to help the trainer focus on the participants' needs and learning objectives * A detailed reference manual * A lexicon of terms for data-management * Limited class size to encourage the interactivity Target Audience This VILT course is intended for: * Junior/new data managers * Geoscientists * Reservoir engineers * Producers * Maintenance specialists * Construction specialists * Human resources * Legal Course Level * Basic or Foundation Training Methods The VILT course will be delivered online in 5 half-days consisting 4 hours per day, with 2 breaks of 10 minutes per day. Course Duration: 5 half-day sessions, 4 hours per session (20 hours in total). Trainer Your expert course leader is a geologist by education who has dedicated his career to subsurface data management services. In 2016, he initiated a tech startup dedicated to Data Management using Artificial Intelligence (AI) tools. He is heavily involved in developing business plans, pricing strategies, partnerships, marketing and SEO, and is the co-author of several Machine Learning publications. He also delivers training on Data Management and Data Science to students and professionals. Based in France, he was formerly Vice President, Sales & Marketing at CGG where he was in charge of the Data Management Services strategy, Sales Manager at Spie O&G Services where he initiated the Geoscience technical assistance activities and Product Manager of interactive seismic inversion software design and marketing at Paradigm.       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

This course will enable you to bring value to the business by putting data science concepts into practice. Data is crucial for understanding where the business is and where it's headed. Not only can data reveal insights, but it can also inform - by guiding decisions and influencing day-to-day operations.